From c3cb9dd0df26864281471a14afcb4986c4a09a12 Mon Sep 17 00:00:00 2001
From: Neale Batra <52152191+nsbatra@users.noreply.github.com>
Date: Tue, 20 Sep 2022 13:14:36 +0200
Subject: [PATCH 1/5] updates to survey walkthrough

---
 docs/404.html                                 |   8 +-
 docs/CODE_OF_CONDUCT.html                     |   8 +-
 docs/CONTRIBUTING.html                        |   8 +-
 docs/ISSUE_TEMPLATE.html                      |   8 +-
 docs/LICENSE.html                             |   8 +-
 docs/SUPPORT.html                             |   8 +-
 docs/articles/Background.html                 |   8 +-
 docs/articles/index.html                      |  12 +-
 docs/authors.html                             |  22 +-
 docs/index.html                               |  16 +-
 docs/news/index.html                          |   8 +-
 docs/pkgdown.yml                              |   6 +-
 docs/reference/apyramid.html                  |   8 +-
 .../reference/available_sitrep_templates.html |  24 +-
 docs/reference/check_sitrep_templates.html    |   8 +-
 docs/reference/epikit-exports.html            | 117 +---
 docs/reference/index.html                     |  44 +-
 docs/reference/msf_dict.html                  |  42 +-
 docs/reference/sitrep-package.html            |  17 +-
 docs/reference/tab_linelist.html              |  55 +-
 docs/sitemap.xml                              |  21 +
 vignettes/Surveys_Walkthrough.Rmd             | 578 +++++++++++++++---
 22 files changed, 683 insertions(+), 351 deletions(-)

diff --git a/docs/404.html b/docs/404.html
index ce7e8056..ff9fb91d 100644
--- a/docs/404.html
+++ b/docs/404.html
@@ -45,7 +45,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="https://r4epi.github.io/sitrep/index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -71,10 +71,10 @@
       <a href="https://r4epi.github.io/sitrep/articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="https://r4epi.github.io/sitrep/articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="https://r4epi.github.io/sitrep/articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="https://r4epi.github.io/sitrep/articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="https://r4epi.github.io/sitrep/articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul>
 </li>
@@ -120,7 +120,7 @@ <h1>Page not found (404)</h1>
 
       <footer><div class="copyright">
   <p></p>
-<p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+<p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/CODE_OF_CONDUCT.html b/docs/CODE_OF_CONDUCT.html
index b5a2c9c0..edce59ce 100644
--- a/docs/CODE_OF_CONDUCT.html
+++ b/docs/CODE_OF_CONDUCT.html
@@ -23,7 +23,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +47,10 @@
       <a href="articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -95,7 +95,7 @@ <h1>Contributor Code of Conduct</h1>
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/CONTRIBUTING.html b/docs/CONTRIBUTING.html
index af1e908b..4e635f93 100644
--- a/docs/CONTRIBUTING.html
+++ b/docs/CONTRIBUTING.html
@@ -23,7 +23,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +47,10 @@
       <a href="articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -118,7 +118,7 @@ <h3 id="see-tidyverse-development-contributing-guide">See tidyverse <a href="htt
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/ISSUE_TEMPLATE.html b/docs/ISSUE_TEMPLATE.html
index 91725db6..f02752f7 100644
--- a/docs/ISSUE_TEMPLATE.html
+++ b/docs/ISSUE_TEMPLATE.html
@@ -23,7 +23,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +47,10 @@
       <a href="articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -93,7 +93,7 @@ <h1>NA</h1>
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/LICENSE.html b/docs/LICENSE.html
index 9e75293a..6677d5aa 100644
--- a/docs/LICENSE.html
+++ b/docs/LICENSE.html
@@ -23,7 +23,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +47,10 @@
       <a href="articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -282,7 +282,7 @@ <h2 id="how-to-apply-these-terms-to-your-new-programs">How to Apply These Terms
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/SUPPORT.html b/docs/SUPPORT.html
index df2dc0a2..9c0b0e63 100644
--- a/docs/SUPPORT.html
+++ b/docs/SUPPORT.html
@@ -23,7 +23,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +47,10 @@
       <a href="articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -98,7 +98,7 @@ <h1>Getting help with sitrep</h1>
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/articles/Background.html b/docs/articles/Background.html
index b11dad1f..01517951 100644
--- a/docs/articles/Background.html
+++ b/docs/articles/Background.html
@@ -46,7 +46,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -72,10 +72,10 @@
       <a href="../articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="../articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="../articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="../articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="../articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul>
 </li>
@@ -194,7 +194,7 @@ <h2 id="contributers">Contributers<a class="anchor" aria-label="anchor" href="#c
 
       <footer><div class="copyright">
   <p></p>
-<p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+<p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/articles/index.html b/docs/articles/index.html
index 2e243f98..d1359b81 100644
--- a/docs/articles/index.html
+++ b/docs/articles/index.html
@@ -23,7 +23,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +47,10 @@
       <a href="../articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="../articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="../articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="../articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="../articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -80,9 +80,9 @@ <h3>All vignettes</h3>
 
       <dl><dt><a href="Background.html">Origin Story</a></dt>
         <dd>
-        </dd><dt><a href="Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a></dt>
+        </dd><dt><a href="Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a></dt>
         <dd>
-        </dd><dt><a href="Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a></dt>
+        </dd><dt><a href="Surveys_Walkthrough.html">{sitrep} surveys template vignette</a></dt>
         <dd>
       </dd></dl></div>
   </div>
@@ -90,7 +90,7 @@ <h3>All vignettes</h3>
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/authors.html b/docs/authors.html
index 0dc8f3bb..2a0f113e 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -23,7 +23,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +47,10 @@
       <a href="articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -77,15 +77,15 @@ <h1>Authors</h1>
 
       
       <ul class="list-unstyled"><li>
-          <p><strong>Dirk Schumacher</strong>. Author. 
+          <p><strong>Alexander Spina</strong>. Author, maintainer. <a href="https://orcid.org/0000-0001-8425-1867" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
         </li>
         <li>
-          <p><strong>Zhian N. Kamvar</strong>. Author, maintainer. <a href="https://orcid.org/0000-0003-1458-7108" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          <p><strong>Zhian N. Kamvar</strong>. Author. <a href="https://orcid.org/0000-0003-1458-7108" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
           </p>
         </li>
         <li>
-          <p><strong>Alexander Spina</strong>. Author. <a href="https://orcid.org/0000-0001-8425-1867" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a>
+          <p><strong>Dirk Schumacher</strong>. Author. 
           </p>
         </li>
         <li>
@@ -117,18 +117,16 @@ <h1 id="citation">Citation</h1>
     </div>
 
 
-    <p>Schumacher D, Kamvar Z, Spina A, Doyle K, Jarvis C, Richter L (2022).
+    <p>Spina A, Kamvar Z, Schumacher D, Doyle K, Jarvis C, Richter L (2022).
 <em>sitrep: Report templates and helper functions for applied epidemiology</em>.
-https://r4epis.netlify.com,
 https://github.com/R4EPI/sitrep,
 https://r4epi.github.io/sitrep/. 
 </p>
     <pre>@Manual{,
   title = {sitrep: Report templates and helper functions for applied epidemiology},
-  author = {Dirk Schumacher and Zhian N. Kamvar and Alexander Spina and Kate Doyle and Chris Jarvis and Lukas Richter},
+  author = {Alexander Spina and Zhian N. Kamvar and Dirk Schumacher and Kate Doyle and Chris Jarvis and Lukas Richter},
   year = {2022},
-  note = {https://r4epis.netlify.com,
-https://github.com/R4EPI/sitrep,
+  note = {https://github.com/R4EPI/sitrep,
 https://r4epi.github.io/sitrep/},
 }</pre>
 
@@ -139,7 +137,7 @@ <h1 id="citation">Citation</h1>
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/index.html b/docs/index.html
index fda041f3..67e64a02 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -46,7 +46,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -72,10 +72,10 @@
       <a href="articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul>
 </li>
@@ -116,7 +116,7 @@
 <h2 id="installation">Installation<a class="anchor" aria-label="anchor" href="#installation"></a>
 </h2>
 <p>The <strong>{sitrep}</strong> package, is currently stored in a <a href="https://github.com/R4EPI/sitrep" class="external-link">GitHub repository</a>. Therefore, the procedure to install these packages have one extra step required.</p>
-<p>To install <strong>sitrep</strong> from GitHub you must first install the <strong>devtools</strong> package.</p>
+<p>To install <strong>sitrep</strong> from GitHub you must first install the <strong>remotes</strong> package.</p>
 <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="co"># install.packages("remotes")</span></span>
 <span><span class="fu">remotes</span><span class="fu">::</span><span class="fu"><a href="https://remotes.r-lib.org/reference/install_github.html" class="external-link">install_github</a></span><span class="op">(</span><span class="st">"r4epi/sitrep"</span><span class="op">)</span></span></code></pre></div>
@@ -153,7 +153,7 @@ <h2 id="available-templates">Available templates<a class="anchor" aria-label="an
 <span></span>
 <span><span class="co"># generate the measles outbreak template in the output directory</span></span>
 <span><span class="fu"><a href="reference/check_sitrep_templates.html">check_sitrep_templates</a></span><span class="op">(</span><span class="st">"measles_outbreak"</span>, path <span class="op">=</span> <span class="va">output_dir</span><span class="op">)</span></span>
-<span><span class="co">#&gt; [1] "C:\\Users\\alexf\\AppData\\Local\\Temp\\RtmpqMzhqG/sitrep_example"</span></span>
+<span><span class="co">#&gt; [1] "C:\\Users\\alexf\\AppData\\Local\\Temp\\Rtmpcv1H8d/sitrep_example"</span></span>
 <span></span>
 <span><span class="co"># view the contents</span></span>
 <span><span class="fu"><a href="https://rdrr.io/r/base/list.files.html" class="external-link">list.files</a></span><span class="op">(</span><span class="va">output_dir</span>, recursive <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
@@ -199,9 +199,9 @@ <h2 data-toc-skip>Citation</h2>
 <div class="developers">
 <h2 data-toc-skip>Developers</h2>
 <ul class="list-unstyled">
+<li>Alexander Spina <br><small class="roles"> Author, maintainer </small> <a href="https://orcid.org/0000-0001-8425-1867" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
+<li>Zhian N. Kamvar <br><small class="roles"> Author </small> <a href="https://orcid.org/0000-0003-1458-7108" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
 <li>Dirk Schumacher <br><small class="roles"> Author </small>  </li>
-<li>Zhian N. Kamvar <br><small class="roles"> Author, maintainer </small> <a href="https://orcid.org/0000-0003-1458-7108" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
-<li>Alexander Spina <br><small class="roles"> Author </small> <a href="https://orcid.org/0000-0001-8425-1867" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
 <li>Kate Doyle <br><small class="roles"> Author </small>  </li>
 <li>Chris Jarvis <br><small class="roles"> Author </small>  </li>
 <li>Lukas Richter <br><small class="roles"> Author </small>  </li>
@@ -225,7 +225,7 @@ <h2 data-toc-skip>Dev status</h2>
 
       <footer><div class="copyright">
   <p></p>
-<p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+<p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/news/index.html b/docs/news/index.html
index f19c751a..a6613cdd 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -23,7 +23,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +47,10 @@
       <a href="../articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="../articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="../articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="../articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="../articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -127,7 +127,7 @@ <h2 class="page-header" data-toc-text="0.1.0" id="sitrep-010">sitrep 0.1.0<a cla
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index e6049fec..9e7b522e 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -3,9 +3,9 @@ pkgdown: 2.0.6
 pkgdown_sha: ~
 articles:
   Background: Background.html
-  Outbreaks Walkthrough: Outbreaks Walkthrough.html
-  Surveys Walkthrough: Surveys Walkthrough.html
-last_built: 2022-09-03T04:07Z
+  Outbreaks_Walkthrough: Outbreaks_Walkthrough.html
+  Surveys_Walkthrough: Surveys_Walkthrough.html
+last_built: 2022-09-19T19:00Z
 urls:
   reference: https://r4epi.github.io/sitrep/reference
   article: https://r4epi.github.io/sitrep/articles
diff --git a/docs/reference/apyramid.html b/docs/reference/apyramid.html
index a2a9c0c7..f3652f0d 100644
--- a/docs/reference/apyramid.html
+++ b/docs/reference/apyramid.html
@@ -23,7 +23,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +47,10 @@
       <a href="../articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="../articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="../articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="../articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="../articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -102,7 +102,7 @@ <h2>See also</h2>
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/reference/available_sitrep_templates.html b/docs/reference/available_sitrep_templates.html
index 62b83ee5..ba1427df 100644
--- a/docs/reference/available_sitrep_templates.html
+++ b/docs/reference/available_sitrep_templates.html
@@ -23,7 +23,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +47,10 @@
       <a href="../articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="../articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="../articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="../articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="../articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -115,16 +115,16 @@ <h2>Examples</h2>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-in"><span><span class="fu">available_sitrep_templates</span><span class="op">(</span>categorise <span class="op">=</span> <span class="cn">TRUE</span>, full.names <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> $outbreak</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "C:/Users/neale/AppData/Local/Temp/RtmpiqhPcF/temp_libpath113fc166d426b/sitrep/rmarkdown/templates/ajs_outbreak"       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [2] "C:/Users/neale/AppData/Local/Temp/RtmpiqhPcF/temp_libpath113fc166d426b/sitrep/rmarkdown/templates/cholera_outbreak"   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [3] "C:/Users/neale/AppData/Local/Temp/RtmpiqhPcF/temp_libpath113fc166d426b/sitrep/rmarkdown/templates/measles_outbreak"   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [4] "C:/Users/neale/AppData/Local/Temp/RtmpiqhPcF/temp_libpath113fc166d426b/sitrep/rmarkdown/templates/meningitis_outbreak"</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "C:/Users/neale/AppData/Local/R/win-library/4.2/sitrep/rmarkdown/templates/ajs_outbreak"       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [2] "C:/Users/neale/AppData/Local/R/win-library/4.2/sitrep/rmarkdown/templates/cholera_outbreak"   </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [3] "C:/Users/neale/AppData/Local/R/win-library/4.2/sitrep/rmarkdown/templates/measles_outbreak"   </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [4] "C:/Users/neale/AppData/Local/R/win-library/4.2/sitrep/rmarkdown/templates/meningitis_outbreak"</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> $survey</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "C:/Users/neale/AppData/Local/Temp/RtmpiqhPcF/temp_libpath113fc166d426b/sitrep/rmarkdown/templates/mortality"        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [2] "C:/Users/neale/AppData/Local/Temp/RtmpiqhPcF/temp_libpath113fc166d426b/sitrep/rmarkdown/templates/nutrition"        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [3] "C:/Users/neale/AppData/Local/Temp/RtmpiqhPcF/temp_libpath113fc166d426b/sitrep/rmarkdown/templates/vaccination_long" </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [4] "C:/Users/neale/AppData/Local/Temp/RtmpiqhPcF/temp_libpath113fc166d426b/sitrep/rmarkdown/templates/vaccination_short"</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] "C:/Users/neale/AppData/Local/R/win-library/4.2/sitrep/rmarkdown/templates/mortality"        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [2] "C:/Users/neale/AppData/Local/R/win-library/4.2/sitrep/rmarkdown/templates/nutrition"        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [3] "C:/Users/neale/AppData/Local/R/win-library/4.2/sitrep/rmarkdown/templates/vaccination_long" </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [4] "C:/Users/neale/AppData/Local/R/win-library/4.2/sitrep/rmarkdown/templates/vaccination_short"</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 </code></pre></div>
     </div>
@@ -136,7 +136,7 @@ <h2>Examples</h2>
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/reference/check_sitrep_templates.html b/docs/reference/check_sitrep_templates.html
index a2b90e36..96aa34c8 100644
--- a/docs/reference/check_sitrep_templates.html
+++ b/docs/reference/check_sitrep_templates.html
@@ -23,7 +23,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +47,10 @@
       <a href="../articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="../articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="../articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="../articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="../articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -152,7 +152,7 @@ <h2>Examples</h2>
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/reference/epikit-exports.html b/docs/reference/epikit-exports.html
index 29365c7e..1a08e33e 100644
--- a/docs/reference/epikit-exports.html
+++ b/docs/reference/epikit-exports.html
@@ -1,5 +1,12 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Exported functions from epikit — add_weights_cluster • sitrep</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Exported functions from epikit — add_weights_cluster"><meta property="og:description" content="Exported functions from epikit"><meta property="og:image" content="https://r4epi.github.io/sitrep/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Exported functions from epikit — add_weights_cluster • sitrep</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Exported functions from epikit — add_weights_cluster"><meta property="og:description" content="These objects are imported from other packages. Follow the links
+below to see their documentation.
+
+  epikit
+add_weights_cluster, add_weights_strata, age_categories, assert_positive_timespan, attack_rate, augment_redundant, case_fatality_rate, case_fatality_rate_df, constrain_dates, dots_to_charlist, fac_from_num, find_breaks, find_date_cause, find_end_date, find_start_date, fmt_ci, fmt_ci_df, fmt_count, fmt_pci, fmt_pci_df, gen_polygon, gen_population, group_age_categories, merge_ci_df, merge_pci_df, mortality_rate, rename_redundant, unite_ci, zcurve
+
+
+"><meta property="og:image" content="https://r4epi.github.io/sitrep/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-149766533-1"></script><script>
@@ -23,7 +30,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +54,10 @@
       <a href="../articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="../articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="../articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="../articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="../articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -77,101 +84,15 @@ <h1>Exported functions from epikit</h1>
     </div>
 
     <div class="ref-description">
-    <p>Exported functions from epikit</p>
-    </div>
+    <p>These objects are imported from other packages. Follow the links
+below to see their documentation.</p>
+<dl><dt>epikit</dt>
+<dd><p><code><a href="https://r4epi.github.io/epikit/reference/add_weights_cluster.html" class="external-link">add_weights_cluster</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/add_weights_strata.html" class="external-link">add_weights_strata</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/age_categories.html" class="external-link">age_categories</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/find_date_cause.html" class="external-link">assert_positive_timespan</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/attack_rate.html" class="external-link">attack_rate</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/rename_redundant.html" class="external-link">augment_redundant</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/attack_rate.html" class="external-link">case_fatality_rate</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/attack_rate.html" class="external-link">case_fatality_rate_df</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/find_date_cause.html" class="external-link">constrain_dates</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/dots_to_charlist.html" class="external-link">dots_to_charlist</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/fac_from_num.html" class="external-link">fac_from_num</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/find_breaks.html" class="external-link">find_breaks</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/find_date_cause.html" class="external-link">find_date_cause</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/find_date_cause.html" class="external-link">find_end_date</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/find_date_cause.html" class="external-link">find_start_date</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/fmt_ci.html" class="external-link">fmt_ci</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/fmt_ci.html" class="external-link">fmt_ci_df</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/fmt_count.html" class="external-link">fmt_count</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/fmt_ci.html" class="external-link">fmt_pci</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/fmt_ci.html" class="external-link">fmt_pci_df</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/gen_polygon.html" class="external-link">gen_polygon</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/gen_population.html" class="external-link">gen_population</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/age_categories.html" class="external-link">group_age_categories</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/unite_ci.html" class="external-link">merge_ci_df</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/unite_ci.html" class="external-link">merge_pci_df</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/attack_rate.html" class="external-link">mortality_rate</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/rename_redundant.html" class="external-link">rename_redundant</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/unite_ci.html" class="external-link">unite_ci</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/zcurve.html" class="external-link">zcurve</a></code></p></dd>
+
+
+</dl></div>
 
-    <div id="ref-usage">
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">add_weights_cluster</span></span>
-<span></span>
-<span><span class="va">add_weights_strata</span></span>
-<span></span>
-<span><span class="va">age_categories</span></span>
-<span></span>
-<span><span class="va">assert_positive_timespan</span></span>
-<span></span>
-<span><span class="va">attack_rate</span></span>
-<span></span>
-<span><span class="va">augment_redundant</span></span>
-<span></span>
-<span><span class="va">case_fatality_rate</span></span>
-<span></span>
-<span><span class="va">case_fatality_rate_df</span></span>
-<span></span>
-<span><span class="va">constrain_dates</span></span>
-<span></span>
-<span><span class="va">dots_to_charlist</span></span>
-<span></span>
-<span><span class="va">fac_from_num</span></span>
-<span></span>
-<span><span class="va">find_breaks</span></span>
-<span></span>
-<span><span class="va">find_date_cause</span></span>
-<span></span>
-<span><span class="va">find_end_date</span></span>
-<span></span>
-<span><span class="va">find_start_date</span></span>
-<span></span>
-<span><span class="va">fmt_ci</span></span>
-<span></span>
-<span><span class="va">fmt_ci_df</span></span>
-<span></span>
-<span><span class="va">fmt_count</span></span>
-<span></span>
-<span><span class="va">fmt_pci</span></span>
-<span></span>
-<span><span class="va">fmt_pci_df</span></span>
-<span></span>
-<span><span class="va">gen_polygon</span></span>
-<span></span>
-<span><span class="va">gen_population</span></span>
-<span></span>
-<span><span class="va">group_age_categories</span></span>
-<span></span>
-<span><span class="va">merge_ci_df</span></span>
-<span></span>
-<span><span class="va">merge_pci_df</span></span>
-<span></span>
-<span><span class="va">mortality_rate</span></span>
-<span></span>
-<span><span class="va">rename_redundant</span></span>
-<span></span>
-<span><span class="va">unite_ci</span></span>
-<span></span>
-<span><span class="va">zcurve</span></span></code></pre></div>
-    </div>
 
-    <div id="format">
-    <h2>Format</h2>
-    <p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-    </div>
     <div id="see-also">
     <h2>See also</h2>
     <div class="dont-index"><p><code><a href="https://r4epi.github.io/epikit/reference/add_weights_cluster.html" class="external-link">epikit::add_weights_cluster()</a></code>, <code><a href="https://r4epi.github.io/epikit/reference/add_weights_strata.html" class="external-link">epikit::add_weights_strata()</a></code>,
@@ -197,7 +118,7 @@ <h2>See also</h2>
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/reference/index.html b/docs/reference/index.html
index d2da1881..2225580c 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -23,7 +23,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +47,10 @@
       <a href="../articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="../articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="../articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="../articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="../articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -97,47 +97,31 @@ <h2 id="all-functions">All functions <a href="#all-functions" class="anchor" ari
       </tr><tr><td>
           <p><code><a href="download_kobo.html">download_kobo()</a></code> </p>
         </td>
-        <td><p>download_kobo
-
-Access kobo data dictionary</p></td>
+        <td><p>Access kobo data dictionary</p></td>
       </tr><tr><td>
           <p><code><a href="download_outbreak_linelist.html">download_outbreak_linelist()</a></code> </p>
         </td>
-        <td><p>download_outbreak_linelist
-
-Access AJS outbreak linelist</p></td>
+        <td><p>Access AJS outbreak linelist</p></td>
       </tr><tr><td>
           <p><code><a href="download_outbreak_pop.html">download_outbreak_pop()</a></code> </p>
         </td>
-        <td><p>download_outbreak_pop
-
-Access AJS outbreak population data</p></td>
+        <td><p>Access AJS outbreak population data</p></td>
       </tr><tr><td>
           <p><code><a href="download_shape_block.html">download_shape_block()</a></code> </p>
         </td>
-        <td><p>download_shape_block
-
-Access Am Timan blocks shapefile</p></td>
+        <td><p>Access Am Timan blocks shapefile</p></td>
       </tr><tr><td>
           <p><code><a href="download_shape_quartier.html">download_shape_quartier()</a></code> </p>
         </td>
-        <td><p>download_shape_quartier
-
-Access Am Timan quartier shapefile</p></td>
+        <td><p>Access Am Timan quartier shapefile</p></td>
       </tr><tr><td>
           <p><code><a href="download_survey.html">download_survey()</a></code> </p>
         </td>
-        <td><p>download_survey
-
-Access fake mortality survey data</p></td>
-      </tr><tr><td>
-          <p><code><a href="epikit-exports.html">add_weights_cluster</a></code> <code><a href="epikit-exports.html">add_weights_strata</a></code> <code><a href="epikit-exports.html">age_categories</a></code> <code><a href="epikit-exports.html">assert_positive_timespan</a></code> <code><a href="epikit-exports.html">attack_rate</a></code> <code><a href="epikit-exports.html">augment_redundant</a></code> <code><a href="epikit-exports.html">case_fatality_rate</a></code> <code><a href="epikit-exports.html">case_fatality_rate_df</a></code> <code><a href="epikit-exports.html">constrain_dates</a></code> <code><a href="epikit-exports.html">dots_to_charlist</a></code> <code><a href="epikit-exports.html">fac_from_num</a></code> <code><a href="epikit-exports.html">find_breaks</a></code> <code><a href="epikit-exports.html">find_date_cause</a></code> <code><a href="epikit-exports.html">find_end_date</a></code> <code><a href="epikit-exports.html">find_start_date</a></code> <code><a href="epikit-exports.html">fmt_ci</a></code> <code><a href="epikit-exports.html">fmt_ci_df</a></code> <code><a href="epikit-exports.html">fmt_count</a></code> <code><a href="epikit-exports.html">fmt_pci</a></code> <code><a href="epikit-exports.html">fmt_pci_df</a></code> <code><a href="epikit-exports.html">gen_polygon</a></code> <code><a href="epikit-exports.html">gen_population</a></code> <code><a href="epikit-exports.html">group_age_categories</a></code> <code><a href="epikit-exports.html">merge_ci_df</a></code> <code><a href="epikit-exports.html">merge_pci_df</a></code> <code><a href="epikit-exports.html">mortality_rate</a></code> <code><a href="epikit-exports.html">rename_redundant</a></code> <code><a href="epikit-exports.html">unite_ci</a></code> <code><a href="epikit-exports.html">zcurve</a></code> </p>
-        </td>
-        <td><p>Exported functions from epikit</p></td>
+        <td><p>Access fake mortality survey data</p></td>
       </tr><tr><td>
-          <p><code><a href="msf_dict.html">msf_dict</a></code> <code><a href="msf_dict.html">msf_dict_survey</a></code> <code><a href="msf_dict.html">msf_dict_rename_helper</a></code> <code><a href="msf_dict.html">gen_data</a></code> </p>
+          <p><code><a href="generic_download.html">generic_download()</a></code> </p>
         </td>
-        <td><p>Functions re-expored from epidict</p></td>
+        <td><p>Internal function (not exported - i.e. not userfacing) to reduce code duplication</p></td>
       </tr><tr><td>
           <p><code><a href="shape_block_internal.html">shape_block_internal</a></code> </p>
         </td>
@@ -146,10 +130,6 @@ <h2 id="all-functions">All functions <a href="#all-functions" class="anchor" ari
           <p><code><a href="shape_quartier_internal.html">shape_quartier_internal</a></code> </p>
         </td>
         <td><p>Quartier shapefile for example outbreak Hepatatis E virus or Acute Jaundice Syndrome (AJS)</p></td>
-      </tr><tr><td>
-          <p><code><a href="tab_linelist.html">tab_survey</a></code> <code><a href="tab_linelist.html">tab_linelist</a></code> <code><a href="tab_linelist.html">tab_univariate</a></code> <code><a href="tab_linelist.html">data_frame_from_2x2</a></code> </p>
-        </td>
-        <td><p>Functions re-expored from epitabulate</p></td>
       </tr></tbody></table></div>
 
   <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
@@ -159,7 +139,7 @@ <h2 id="all-functions">All functions <a href="#all-functions" class="anchor" ari
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/reference/msf_dict.html b/docs/reference/msf_dict.html
index 02825427..df8ef496 100644
--- a/docs/reference/msf_dict.html
+++ b/docs/reference/msf_dict.html
@@ -1,5 +1,12 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Functions re-expored from epidict — msf_dict • sitrep</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Functions re-expored from epidict — msf_dict"><meta property="og:description" content="Functions re-expored from epidict"><meta property="og:image" content="https://r4epi.github.io/sitrep/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Functions re-expored from epidict — msf_dict • sitrep</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Functions re-expored from epidict — msf_dict"><meta property="og:description" content="These objects are imported from other packages. Follow the links
+below to see their documentation.
+
+  epidict
+gen_data, msf_dict, msf_dict_rename_helper, msf_dict_survey
+
+
+"><meta property="og:image" content="https://r4epi.github.io/sitrep/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-149766533-1"></script><script>
@@ -23,7 +30,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +54,10 @@
       <a href="../articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="../articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="../articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="../articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="../articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -77,26 +84,15 @@ <h1>Functions re-expored from epidict</h1>
     </div>
 
     <div class="ref-description">
-    <p>Functions re-expored from epidict</p>
-    </div>
+    <p>These objects are imported from other packages. Follow the links
+below to see their documentation.</p>
+<dl><dt>epidict</dt>
+<dd><p><code><a href="https://r4epi.github.io/epidict/reference/gen_data.html" class="external-link">gen_data</a></code>, <code><a href="https://r4epi.github.io/epidict/reference/msf_dict.html" class="external-link">msf_dict</a></code>, <code><a href="https://r4epi.github.io/epidict/reference/msf_dict_rename_helper.html" class="external-link">msf_dict_rename_helper</a></code>, <code><a href="https://r4epi.github.io/epidict/reference/msf_dict.html" class="external-link">msf_dict_survey</a></code></p></dd>
+
+
+</dl></div>
 
-    <div id="ref-usage">
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">msf_dict</span></span>
-<span></span>
-<span><span class="va">msf_dict_survey</span></span>
-<span></span>
-<span><span class="va">msf_dict_rename_helper</span></span>
-<span></span>
-<span><span class="va">gen_data</span></span></code></pre></div>
-    </div>
 
-    <div id="format">
-    <h2>Format</h2>
-    <p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-    </div>
     <div id="see-also">
     <h2>See also</h2>
     <div class="dont-index"><p>Dictionaries: <code><a href="https://r4epi.github.io/epidict/reference/msf_dict.html" class="external-link">epidict::msf_dict()</a></code>, <code><a href="https://r4epi.github.io/epidict/reference/msf_dict.html" class="external-link">epidict::msf_dict_survey()</a></code><br>
@@ -112,7 +108,7 @@ <h2>See also</h2>
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/reference/sitrep-package.html b/docs/reference/sitrep-package.html
index 83de986c..dd98c668 100644
--- a/docs/reference/sitrep-package.html
+++ b/docs/reference/sitrep-package.html
@@ -24,7 +24,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -48,10 +48,10 @@
       <a href="../articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="../articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="../articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="../articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="../articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -85,17 +85,16 @@ <h1>sitrep: Report templates and helper functions for applied epidemiology</h1>
 
     <div id="see-also">
     <h2>See also</h2>
-    <div class="dont-index"><p>Useful links:</p><ul><li><p><a href="https://r4epis.netlify.com" class="external-link">https://r4epis.netlify.com</a></p></li>
-<li><p><a href="https://github.com/R4EPI/sitrep" class="external-link">https://github.com/R4EPI/sitrep</a></p></li>
+    <div class="dont-index"><p>Useful links:</p><ul><li><p><a href="https://github.com/R4EPI/sitrep" class="external-link">https://github.com/R4EPI/sitrep</a></p></li>
 <li><p><a href="https://r4epi.github.io/sitrep/">https://r4epi.github.io/sitrep/</a></p></li>
 <li><p>Report bugs at <a href="https://github.com/R4EPI/sitrep/issues" class="external-link">https://github.com/R4EPI/sitrep/issues</a></p></li>
 </ul></div>
     </div>
     <div id="author">
     <h2>Author</h2>
-    <p><strong>Maintainer</strong>: Zhian N. Kamvar <a href="mailto:zkamvar@gmail.com">zkamvar@gmail.com</a> (<a href="https://orcid.org/0000-0003-1458-7108" class="external-link">ORCID</a>)</p>
-<p>Authors:</p><ul><li><p>Dirk Schumacher <a href="mailto:mai@dirk-schumacher.net">mai@dirk-schumacher.net</a></p></li>
-<li><p>Alexander Spina <a href="mailto:alexfspina@gmail.com">alexfspina@gmail.com</a> (<a href="https://orcid.org/0000-0001-8425-1867" class="external-link">ORCID</a>)</p></li>
+    <p><strong>Maintainer</strong>: Alexander Spina <a href="mailto:aspina@appliedepi.org">aspina@appliedepi.org</a> (<a href="https://orcid.org/0000-0001-8425-1867" class="external-link">ORCID</a>)</p>
+<p>Authors:</p><ul><li><p>Zhian N. Kamvar <a href="mailto:zkamvar@gmail.com">zkamvar@gmail.com</a> (<a href="https://orcid.org/0000-0003-1458-7108" class="external-link">ORCID</a>)</p></li>
+<li><p>Dirk Schumacher <a href="mailto:mai@dirk-schumacher.net">mai@dirk-schumacher.net</a></p></li>
 <li><p>Kate Doyle</p></li>
 <li><p>Chris Jarvis</p></li>
 <li><p>Lukas Richter</p></li>
@@ -111,7 +110,7 @@ <h2>Author</h2>
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/reference/tab_linelist.html b/docs/reference/tab_linelist.html
index e007288b..0f2f4cd1 100644
--- a/docs/reference/tab_linelist.html
+++ b/docs/reference/tab_linelist.html
@@ -1,5 +1,12 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Functions re-expored from epitabulate — tab_survey • sitrep</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Functions re-expored from epitabulate — tab_survey"><meta property="og:description" content="Functions re-expored from epitabulate"><meta property="og:image" content="https://r4epi.github.io/sitrep/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Objects exported from other packages — tab_survey • sitrep</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Objects exported from other packages — tab_survey"><meta property="og:description" content="These objects are imported from other packages. Follow the links
+below to see their documentation.
+
+  epitabulate
+data_frame_from_2x2, tab_linelist, tab_survey, tab_univariate
+
+
+"><meta property="og:image" content="https://r4epi.github.io/sitrep/logo.png"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--><!-- Global site tag (gtag.js) - Google Analytics --><script async src="https://www.googletagmanager.com/gtag/js?id=UA-149766533-1"></script><script>
@@ -23,7 +30,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">sitrep</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.8</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.1.9</span>
       </span>
     </div>
 
@@ -47,10 +54,10 @@
       <a href="../articles/Background.html">Origin Story</a>
     </li>
     <li>
-      <a href="../articles/Outbreaks%20Walkthrough.html">{sitrep} outbreaks template vignette</a>
+      <a href="../articles/Outbreaks_Walkthrough.html">{sitrep} outbreaks template vignette</a>
     </li>
     <li>
-      <a href="../articles/Surveys%20Walkthrough.html">{sitrep} surveys template vignette</a>
+      <a href="../articles/Surveys_Walkthrough.html">{sitrep} surveys template vignette</a>
     </li>
   </ul></li>
 <li>
@@ -71,43 +78,21 @@
       </header><div class="row">
   <div class="col-md-9 contents">
     <div class="page-header">
-    <h1>Functions re-expored from epitabulate</h1>
+    <h1>Objects exported from other packages</h1>
     <small class="dont-index">Source: <a href="https://github.com/R4EPI/sitrep/blob/HEAD/R/epitabulate_exports.R" class="external-link"><code>R/epitabulate_exports.R</code></a></small>
     <div class="hidden name"><code>tab_linelist.Rd</code></div>
     </div>
 
     <div class="ref-description">
-    <p>Functions re-expored from epitabulate</p>
-    </div>
+    <p>These objects are imported from other packages. Follow the links
+below to see their documentation.</p>
+<dl><dt>epitabulate</dt>
+<dd><p><code><a href="https://R4EPI.github.io/epitabulate/reference/data_frame_from_2x2.html" class="external-link">data_frame_from_2x2</a></code>, <code>tab_linelist</code>, <code>tab_survey</code>, <code><a href="https://R4EPI.github.io/epitabulate/reference/tab_univariate.html" class="external-link">tab_univariate</a></code></p></dd>
+
+
+</dl></div>
 
-    <div id="ref-usage">
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">tab_survey</span></span>
-<span></span>
-<span><span class="va">tab_linelist</span></span>
-<span></span>
-<span><span class="va">tab_univariate</span></span>
-<span></span>
-<span><span class="va">data_frame_from_2x2</span></span></code></pre></div>
-    </div>
 
-    <div id="format">
-    <h2>Format</h2>
-    <p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-<p>An object of class <code>function</code> of length 1.</p>
-    </div>
-    <div id="see-also">
-    <h2>See also</h2>
-    <div class="dont-index"><p><span class="pkg">epitabulate</span> functions:</p><ul><li><p><code><a href="https://R4EPI.github.io/epitabulate/reference/tab_functions.html" class="external-link">epitabulate::tab_linelist()</a></code>: tabulate linelist data</p></li>
-<li><p><code><a href="https://R4EPI.github.io/epitabulate/reference/tab_functions.html" class="external-link">epitabulate::tab_survey()</a></code>: tabulate survey data</p></li>
-<li><p><code><a href="https://R4EPI.github.io/epitabulate/reference/tab_univariate.html" class="external-link">epitabulate::tab_univariate()</a></code>: caluclate odds, risk, and incidence risk
-ratios for multiple variables from linelist data.</p></li>
-<li><p><code><a href="https://R4EPI.github.io/epitabulate/reference/data_frame_from_2x2.html" class="external-link">epitabulate::data_frame_from_2x2()</a></code>: convert a 2x2(x2) table to a data
-frame clearly labelling the (un)exposed (non)case combinations and their
-totals.</p></li>
-</ul></div>
-    </div>
 
   </div>
   <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
@@ -117,7 +102,7 @@ <h2>See also</h2>
 
 
       <footer><div class="copyright">
-  <p></p><p>Developed by Dirk Schumacher, Zhian N. Kamvar, Alexander Spina, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
+  <p></p><p>Developed by Alexander Spina, Zhian N. Kamvar, Dirk Schumacher, Kate Doyle, Chris Jarvis, Lukas Richter.</p>
 </div>
 
 <div class="pkgdown">
diff --git a/docs/sitemap.xml b/docs/sitemap.xml
index 818c464f..ba6a9023 100644
--- a/docs/sitemap.xml
+++ b/docs/sitemap.xml
@@ -12,9 +12,15 @@
   <url>
     <loc>https://r4epi.github.io/sitrep/articles/Outbreaks Walkthrough.html</loc>
   </url>
+  <url>
+    <loc>https://r4epi.github.io/sitrep/articles/Outbreaks_Walkthrough.html</loc>
+  </url>
   <url>
     <loc>https://r4epi.github.io/sitrep/articles/Surveys Walkthrough.html</loc>
   </url>
+  <url>
+    <loc>https://r4epi.github.io/sitrep/articles/Surveys_Walkthrough.html</loc>
+  </url>
   <url>
     <loc>https://r4epi.github.io/sitrep/authors.html</loc>
   </url>
@@ -36,6 +42,12 @@
   <url>
     <loc>https://r4epi.github.io/sitrep/news/index.html</loc>
   </url>
+  <url>
+    <loc>https://r4epi.github.io/sitrep/reference/add_ar.html</loc>
+  </url>
+  <url>
+    <loc>https://r4epi.github.io/sitrep/reference/add_crosstabs.html</loc>
+  </url>
   <url>
     <loc>https://r4epi.github.io/sitrep/reference/add_weights_cluster.html</loc>
   </url>
@@ -111,12 +123,21 @@
   <url>
     <loc>https://r4epi.github.io/sitrep/reference/fmt_count.html</loc>
   </url>
+  <url>
+    <loc>https://r4epi.github.io/sitrep/reference/generic_download.html</loc>
+  </url>
   <url>
     <loc>https://r4epi.github.io/sitrep/reference/gen_polygon.html</loc>
   </url>
   <url>
     <loc>https://r4epi.github.io/sitrep/reference/gen_population.html</loc>
   </url>
+  <url>
+    <loc>https://r4epi.github.io/sitrep/reference/gt_mh_odds.html</loc>
+  </url>
+  <url>
+    <loc>https://r4epi.github.io/sitrep/reference/gt_remove_stat.html</loc>
+  </url>
   <url>
     <loc>https://r4epi.github.io/sitrep/reference/index.html</loc>
   </url>
diff --git a/vignettes/Surveys_Walkthrough.Rmd b/vignettes/Surveys_Walkthrough.Rmd
index 7f74f6a5..aa3d6664 100644
--- a/vignettes/Surveys_Walkthrough.Rmd
+++ b/vignettes/Surveys_Walkthrough.Rmd
@@ -22,9 +22,7 @@ knitr::opts_chunk$set(
 
 ## Overview
 
-This page demonstrate use of the {sitrep} R Markdown template for analysis of a retrospective mortality survey, using data from TODO. *This case study uses data that was produced using Kobo, a common survey and data collection tool in settings where MSF works.*
-
-### Survey background
+This page demonstrate use of the {sitrep} R Markdown template for analysis of a retrospective mortality survey, using data that was produced using Kobo, a common survey and data collection tool in settings where MSF works.
 
 ## Getting started
 
@@ -71,7 +69,7 @@ You should review the Epidemiologist R Handbook chapters on [RStudio projects](h
 
 > Select *File -\> New Project* from the top RStudio menu.
 
-> Creating a new R project will create:
+> Creating a new RStudio project will create:
 
 > -   A new project directory (folder)\
 > -   A R project file (.Rproj) in the project folder that serves as a shortcut to open the project via RStudio
@@ -129,12 +127,13 @@ There are different ways to sample populations for surveys. The most commonly us
 1. **Simple random sampling (SRS)**: requires a comprehensive sampling frame (i.e. total list of households inside a refugee camp or 
 GPS based sampling in a known area).
 2. **Cluster based sampling**: most commonly used in combination with sampling villages proportional to population size.
-3. **Stratified samples**: uses either SRS or cluster based sampling but in two different adminstrative areas in order to obtain
+3. **Stratified samples**: uses either SRS or cluster based sampling but in two different administrative areas in order to obtain
 precise prevalence estimates for them.
 
-The templates can accomodate analysis of data from all sampling designs.
+The templates can accommodate analysis of data from all of these sampling designs.
 
 ### Sample size
+
 Before implementing a survey you will need to calculate the sample size for that survey.
 
 When calculating a sample size for your survey you take the below parameters into consideration:
@@ -162,7 +161,7 @@ Mathematically DEFF is calculated as:
 > **DEFF=1+(1-n) * rho**
 > where n=sample size of your survey and rho=intraclass coefficient
 
-When analysing your survery data, we often recalculate the DEFF for the main outcomes of interest. This because the DEFF will give you a good estimate on whether the survey design and sampling approach made sense in your survey for your outcome of interest.
+When analysing your survey data, we often recalculate the DEFF for the main outcomes of interest. This because the DEFF will give you a good estimate on whether the survey design and sampling approach made sense in your survey for your outcome of interest.
 
 ### Precision around your estimate
 The precision around your estimate stipulates how close to the your estimate you would like the 95% confidence interval of your prevalence estimate to fall.
@@ -192,7 +191,7 @@ We have designed the templates to run through a similar series of analytical que
   * Malnutrition: prevalence of malnutrition in target population through MUAC and Weight for Height Scores  
 4. Calculation of **secondary outcomes of interest**
 
-The sampling stratgey **MUST** be considered by the epidemiologist using the templates in order to ensure an appropriate weighting is applied to the analysis.
+The sampling strategy **MUST** be considered by the epidemiologist using the templates in order to ensure an appropriate weighting is applied to the analysis.
 
 
 
@@ -365,7 +364,7 @@ survey_data_ind <- rio::import(system.file("extdata", "mortality_survey_data.xls
 ```
 
 
-Here is a preview of the first 25 entries with household informaton:  
+Here is a preview of the first 25 entries with household information:  
 
 ```{r, echo=FALSE}
 DT::datatable(head(survey_data_hh, 25), rownames = FALSE, filter="top", options = list(pageLength = 5, scrollX=T), class = 'white-space: nowrap' )
@@ -383,7 +382,7 @@ DT::datatable(head(survey_data_ind, 25), rownames = FALSE, filter="top", options
 
 As we are using a Kobo dataset that has both individual and household data (stored in separate data frames), we will need to combine them using code in the `merge_data_levels` code chunk.  
 
-Uncomment this code, and replace the defaults to reflect our datasets, as below:  
+Uncomment this code, and replace the defaults to reflect our data sets, as below:  
 
 ```{r}
 
@@ -399,26 +398,227 @@ DT::datatable(head(study_data_raw, 25), rownames = FALSE, filter="top", options
 ```
 
 
-### Prep Kobo data
 
-In this chunk called `prep_kobo_data`, we run the command that creates `study_data_cleaned` as an exact copy of `study_data_raw`. This new data frame will be fully cleaned in subsequent sections.  
+
+### Prep data
+
+This dataset was produced with Kobo, but does not exactly align with the MSF data dictionary for mortality surveys. **Therefore, for this report we must treat it as "non-Kobo" and take actions to align it with the expected column names.**  
+
+Therefore, to prepare the data you should **comment/deactivate with #** the chunk called `prep_kobo_data`. Instead, we will use the approach outlined in the code chunk `prep_nonkobo_data`.  
+
+The main activity to prep the data is alignment of the column names to those expected by this R Markdown template.  
+
+
+First, we can un-comment and run the command that creates `study_data_cleaned` as an exact copy of `study_data_raw`. This new data frame will be fully cleaned in subsequent sections.  
 
 ```{r}
 study_data_cleaned <- study_data_raw
 ```
 
-The next uncommented command is unnecessary and should be deactivated with # symbols. We do not have a column called `violence_nature_other` in our survey dataset.  
+Next, we want to rename some of our columns. Using the command `msf_dict_rename_helper("mortality", varnames = "name")` we get a "helped" command copied to our clipboard. This contains many more variables than we need, but it is useful to review.  
+
+```{r, eval=FALSE, echo = TRUE}
+
+## Add the appropriate column names after the equals signs
+# 
+# linelist_cleaned <- rename(linelist_cleaned,
+#   age_months                         =   , # integer         (REQUIRED)
+#   age_years                          =   , # integer         (REQUIRED)
+#   arrived                            =   , # yn              (REQUIRED)
+#   care_fever                         =   , # yndk            (REQUIRED)
+#   care_illness_recent                =   , # yndk            (REQUIRED)
+#   cause                              =   , # cause           (REQUIRED)
+#   cause_illness                      =   , # cause           (REQUIRED)
+#   cluster_number                     =   , # integer         (REQUIRED)
+#   consent                            =   , # yn              (REQUIRED)
+#   date                               =   , # date            (REQUIRED)
+#   date_arrived                       =   , # date            (REQUIRED)
+#   date_birth                         =   , # date            (REQUIRED)
+#   date_death                         =   , # date            (REQUIRED)
+#   date_left                          =   , # date            (REQUIRED)
+#   died                               =   , # yn              (REQUIRED)
+#   end                                =   , # end             (REQUIRED)
+#   fever_now                          =   , # yndk            (REQUIRED)
+#   fever_past_weeks                   =   , # yndk            (REQUIRED)
+#   height                             =   , # integer         (REQUIRED)
+#   household_number                   =   , # integer         (REQUIRED)
+#   ill_hh_number                      =   , # integer         (REQUIRED)
+#   ill_recently                       =   , # yndk            (REQUIRED)
+#   left                               =   , # yn              (REQUIRED)
+#   member_number                      =   , # integer         (REQUIRED)
+#   no_care_illness                    =   , # no_care         (REQUIRED)
+#   no_consent_reason                  =   , # no_consent      (REQUIRED)
+#   place_violence                     =   , # viol_place      (REQUIRED)
+#   pregnant                           =   , # yn              (REQUIRED)
+#   reason_no_care                     =   , # no_care         (REQUIRED)
+#   sex                                =   , # sex             (REQUIRED)
+#   start                              =   , # start           (REQUIRED)
+#   uniform                            =   , # ynnr            (REQUIRED)
+#   village_name                       =   , # village         (REQUIRED)
+#   violence_nature                    =   , # violence_nature (REQUIRED)
+#   violence_nature_other              =   , # text            (REQUIRED)
+#   violent_episode                    =   , # ynnr            (REQUIRED)
+#   violent_episodes_number            =   , # integer         (REQUIRED)
+#   weight                             =   , # integer         (REQUIRED)
+#   after_leaving_hf                   =   , # text            (optional)
+#   anc_bednet                         =   , # yndk            (optional)
+#   anti_malarials                     =   , # yndk            (optional)
+#   anti_malarials_listed              =   , # anti_malarials  (optional)
+#   axiliary_temp                      =   , # integer         (optional)
+#   bednet                             =   , # yn              (optional)
+#   born                               =   , # yn              (optional)
+#   born_later                         =   , # yn              (optional)
+#   care_dying                         =   , # yndk            (optional)
+#   care_illness_df                    =   , # yndk            (optional)
+#   care_illness_last                  =   , # yndk            (optional)
+#   cause_illness_df                   =   , # illness         (optional)
+#   cause_illness_last                 =   , # cause           (optional)
+#   cause_illness_last_other           =   , # text            (optional)
+#   cause_illness_other                =   , # text            (optional)
+#   cause_other                        =   , # text            (optional)
+#   cost_consultation                  =   , # integer         (optional)
+#   cost_consultation_df               =   , # integer         (optional)
+#   cost_consultation_last             =   , # integer         (optional)
+#   cost_treatment                     =   , # integer         (optional)
+#   cost_treatment_df                  =   , # integer         (optional)
+#   cost_treatment_last                =   , # integer         (optional)
+#   current_status                     =   , # status          (optional)
+#   date_death_alt                     =   , # date            (optional)
+#   date_violence                      =   , # date            (optional)
+#   deviceid                           =   , # deviceid        (optional)
+#   diarrhoea_fever_2weeks             =   , # yndk            (optional)
+#   education_level                    =   , # education_level (optional)
+#   height_mal                         =   , # integer         (optional)
+#   hemocue                            =   , # integer         (optional)
+#   herbal_medicines                   =   , # herbs           (optional)
+#   households_building                =   , # integer         (optional)
+#   last_person_ill                    =   , # yndk            (optional)
+#   malaria_episodes                   =   , # integer         (optional)
+#   malaria_test                       =   , # test            (optional)
+#   malaria_treatment                  =   , # yn              (optional)
+#   malaria_treatment_infant           =   , # treatment       (optional)
+#   malaria_treatment_preg             =   , # treatment       (optional)
+#   measles_vaccination                =   , # yn              (optional)
+#   muac                               =   , # integer         (optional)
+#   muac_mal                           =   , # integer         (optional)
+#   n1                                 =   , # note            (optional)
+#   n10                                =   , # note            (optional)
+#   n11                                =   , # note            (optional)
+#   n12                                =   , # note            (optional)
+#   n13                                =   , # note            (optional)
+#   n2                                 =   , # note            (optional)
+#   n3                                 =   , # note            (optional)
+#   n4                                 =   , # note            (optional)
+#   n5                                 =   , # note            (optional)
+#   n6                                 =   , # note            (optional)
+#   n7                                 =   , # note            (optional)
+#   n8                                 =   , # note            (optional)
+#   n9                                 =   , # note            (optional)
+#   no_care_illness_df                 =   , # no_care         (optional)
+#   no_care_illness_df_other           =   , # text            (optional)
+#   no_care_illness_last               =   , # no_care         (optional)
+#   no_care_illness_last_other         =   , # text            (optional)
+#   no_care_illness_other              =   , # text            (optional)
+#   no_consent_other                   =   , # text            (optional)
+#   oedema                             =   , # measure         (optional)
+#   oedema_mal                         =   , # measure         (optional)
+#   period_illness_hsb                 =   , # period          (optional)
+#   period_illness_hsb_number          =   , # integer         (optional)
+#   period_illness_viol                =   , # period          (optional)
+#   period_illness_viol_number         =   , # integer         (optional)
+#   place_care_dying                   =   , # place_death     (optional)
+#   place_care_illness                 =   , # place_hf        (optional)
+#   place_care_illness_other           =   , # text            (optional)
+#   place_death                        =   , # place_death     (optional)
+#   place_death_hsb                    =   , # place_death     (optional)
+#   place_death_hsb_other              =   , # text            (optional)
+#   place_death_other                  =   , # text            (optional)
+#   place_death_viol                   =   , # place_death     (optional)
+#   place_death_viol_other             =   , # text            (optional)
+#   place_first_hf                     =   , # place_hf        (optional)
+#   place_first_hf_df                  =   , # place_hf        (optional)
+#   place_first_hf_df_other            =   , # text            (optional)
+#   place_first_hf_other               =   , # text            (optional)
+#   place_healthcare                   =   , # place_treatment (optional)
+#   place_healthcare_other             =   , # text            (optional)
+#   place_second_hf                    =   , # place_hf        (optional)
+#   place_second_hf_df                 =   , # place_hf        (optional)
+#   place_second_hf_df_other           =   , # text            (optional)
+#   place_second_hf_other              =   , # text            (optional)
+#   place_violence_other               =   , # text            (optional)
+#   present_start                      =   , # yn              (optional)
+#   present_today                      =   , # yn              (optional)
+#   random_hh                          =   , # calculate       (optional)
+#   random_hh_note                     =   , # note            (optional)
+#   rdt                                =   , # test2           (optional)
+#   read_write                         =   , # yn              (optional)
+#   reason_first_hf_selected           =   , # reason_hf       (optional)
+#   reason_first_hf_selected_df        =   , # reason_hf       (optional)
+#   reason_first_hf_selected_df_other  =   , # text            (optional)
+#   reason_first_hf_selected_other     =   , # text            (optional)
+#   reason_no_care_hsb                 =   , # no_care         (optional)
+#   reason_no_care_hsb_other           =   , # text            (optional)
+#   reason_no_care_other               =   , # text            (optional)
+#   reason_not_present                 =   , # reason_absent   (optional)
+#   reason_second_hf_selected          =   , # reason_hf       (optional)
+#   reason_second_hf_selected_df       =   , # reason_hf       (optional)
+#   reason_second_hf_selected_df_other =   , # text            (optional)
+#   reason_second_hf_selected_other    =   , # text            (optional)
+#   remember_arrival                   =   , # yn              (optional)
+#   remember_death                     =   , # yn              (optional)
+#   remember_departure                 =   , # yn              (optional)
+#   remember_dob                       =   , # yn              (optional)
+#   remember_violence_date             =   , # yn              (optional)
+#   source_date_death_hsb              =   , # date            (optional)
+#   source_date_death_viol             =   , # date            (optional)
+#   source_death_hsb                   =   , # source          (optional)
+#   source_death_viol                  =   , # source          (optional)
+#   source_money_df                    =   , # money_source    (optional)
+#   source_money_df_other              =   , # text            (optional)
+#   source_money_last                  =   , # money_source    (optional)
+#   source_money_last_other            =   , # text            (optional)
+#   source_written_death_hsb           =   , # text            (optional)
+#   source_written_death_viol          =   , # text            (optional)
+#   source_written_hsb                 =   , # text            (optional)
+#   source_written_viol                =   , # text            (optional)
+#   spleen                             =   , # integer         (optional)
+#   start_illness                      =   , # period          (optional)
+#   start_illness_number               =   , # integer         (optional)
+#   status_df                          =   , # status          (optional)
+#   team_number                        =   , # integer         (optional)
+#   thick_smear                        =   , # yn              (optional)
+#   thin_smear                         =   , # yn              (optional)
+#   today                              =   , # today           (optional)
+#   treatment_delay                    =   , # time            (optional)
+#   treatment_delay_df                 =   , # time            (optional)
+#   vaccination_card                   =   , # yn              (optional)
+#   village_other                      =   , # text            (optional)
+#   visit_second_hf                    =   , # yndk            (optional)
+#   visit_second_hf_df                 =   , # yndk            (optional)
+#   weight_mal                         =     # integer         (optional)
+# )
+# 
+
+```
+
+We can edit the above, or simply refer to it to construct our `rename()` command, as below:   
 
 ```{r}
-# study_data_cleaned <- rename(study_data_cleaned,
-#                              violence_nature_other_details    =  violence_nature_other)
+study_data_cleaned <- rename(
+  study_data_cleaned,
+  consent = household_consents_to_particip,
+  date_arrived = doa,
+  date_birth = dob,
+  date_left = dod,
+  date_died = dodeath)
+
 ```
 
 Finally, we run the command to clean the column names. The `clean_names()` function from the {janitor} package will standardise the syntax of all the column names (headers) by converting all to lowercase, replacing spaces and special characters with underscores, etc.  
 
 ```{r}
 ## define clean variable names using clean_names from the janitor package. 
-study_data_cleaned <- janitor::clean_names(study_data_cleaned)
+study_data_cleaned <- clean_names(study_data_cleaned)
 ```
 
 Further data cleaning will occur in later data cleaning chunks.  
@@ -448,19 +648,21 @@ download_kobo()
 
 ### Format data dictionary  
 
-The {sitrep} package contains a function to import the Kobo data dictionary into R and format it to facilitate further data cleaning. You can uncomment this code in the chunk `prep_kobo_data`, modify it such that the `name = ` argument points to the location of your Kobo dictionary xlsx file, and run it. A new data frame object called `msf_dict` will be created in your R Environment.  
+The {sitrep} package contains a function to import the Kobo data dictionary into R and format it to facilitate further data cleaning. You can uncomment this code in the chunk `prep_kobo_data`, modify it such that the `name = ` argument points to the location of your Kobo dictionary xlsx file, and run it. We also add the arguement `compact = FALSE` so that the dictionary is displayed to us as a more readable format, with each option having its own row.  
 
 ```{r, eval=FALSE}
 # Import Kobo data dictionary into R and re-format to support data cleaning
 study_data_dict <- msf_dict_survey(name = "mortality_survey_dict.xlsx",
-                            template = FALSE)
+                            template = FALSE, 
+                            compact = FALSE)
 ```
 
 
 ```{r, echo=FALSE, eval=TRUE}
 # BACK-END for vignette
 study_data_dict <- msf_dict_survey(name = system.file("extdata", "mortality_survey_dict.xlsx", package = "sitrep"),
-                     template = FALSE)
+                     template = FALSE,
+                     compact = FALSE)
 ```
 
 You can skip the code chunk `prep_nonkobo_data`.  
@@ -471,7 +673,7 @@ You can skip the code chunk `prep_nonkobo_data`.
 
 This vignette does not include population data, so in the chunk `read_population_data` we will use the code that is uncommented by default - estimating populations using the proportions for sub-Saharan Africa in 2019 from the Doctors without Borders (MSF) OCBA population denominators tool v1.  
 
-* We set the total population as 10,000, as a default assumption. TODO  
+* We set the total population as 10,000, as a default assumption.  
 * We leave the proportion estimates as written  
 * We have observations from "Town A" and "Town B" (see column `location` in the `survey_data_ind` data frame), so we edit the inputs to the `health_district` column as written in the final line of each command (see below).  
 
@@ -510,6 +712,8 @@ population_data_age <- bind_rows(population_data_age_district_a,
 
 ### Cluster counts
 
+In the cluster counts chunk, we specify that Town A has 500 households, whereas Town B has 700.  
+
 ```{r cluster_counts}
 
 cluster_counts <- tibble(cluster = c("Town A", "Town B"), 
@@ -519,69 +723,73 @@ cluster_counts <- tibble(cluster = c("Town A", "Town B"),
 
 ## Browse data
 
+This chunk includes R commands to help you familiarise yourself with your dataset.  
 
 ## Data cleaning
 
 
 ### Standardise dates
 
-The first command creates an list of column names, called `DATEVARS`, using the imported and formatted Kobo data dictionary. The command looks into the `type` column of the dictionary, and extracts all the variables that are dates and that are also present in the `study_data_cleaned`. The names of these columns are saved as `DATEVARS`.  
-
-```{r}
-## get the names of variables which are dates
-DATEVARS <- study_data_dict %>% 
-  filter(type == "date") %>% 
-  filter(name %in% names(study_data_cleaned)) %>% 
-  ## filter to match the column names of your data
-  pull(name) # select date vars
-```
+The goal with this code chunk is to convert all date columns to Date class so that R can handle them correctly. Here, again, we need to follow the instructions for "non-Kobo" because our data dictionary is not standard for MSF. 
 
+The default code uses the data dictionary to create a `DATEVARS` object, but we will comment that section to deactivate it, and instead use the "non-Kobo" method which searches for all columns that contain the word "date" or "Date", and converts them to class Date.  
 
-In the next command, from this list `DATEVARS`, and columns that are completely empty are identified. 
-
-```{r}
-## find if there are date variables which are completely empty
-EMPTY_DATEVARS <- purrr::map(DATEVARS, ~all(
-  is.na(study_data_cleaned[[.x]])
-  )) %>% 
-  unlist() %>% 
-  which()
-```
+To convert the dates to class "Date" we use the function `parse_date()` from the {parsedate} package. This function does not assume a standard format to the dates, and evaluates every data frame cell individually, using intelligent guessing to decide whether the date is written as Month-Day-Year, Day-Month-Year, or Year-Month-Day, etc.
 
-Finally, we using indexing (square brackets) and a minus sign to remove those date variables that were empty from the list `DATEVARS`.  
+The result of `parse_date()` is actually class "POSIXct" (a specific type of date class), so the result is piped to `as.Date()` to convert it to a class that is more easily accepted by subsequent functions.  
 
 
 ```{r}
-## remove exclude the names of variables which are completely emptys
-DATEVARS <- DATEVARS[-EMPTY_DATEVARS]
-```
-
 
-Not that we have a complete and verified list of used date variables, we can run the `across()` function within `mutate()` to convert all of the dates to class "Date". Recall that date columns must be properly recognized by R as dates in order to be used effectively.  
+## Kobo standard data --------------------------------------------------------
+## If you got your data from Kobo, use this portion of the code.
+## If not, comment this section out and use the below.
 
-To convert the dates to class "Date" we use the function `parse_date()` from the {parsedate} package. This function does not assume a standard format to the dates, and evaluates every data frame cell individually, using intelligent guessing to decide whether the date is written as Month-Day-Year, Day-Month-Year, or Year-Month-Day, etc.
-
-The result of `parse_date()` is actually class "POSIXct" (a specific type of date class), so the result is piped to `as.Date()` to convert it to a class that is more easily accepted by subsequent functions.  
-
-```{r}
-## change to dates 
-## use the parse_date() function to make a first pass at date variables.
-## parse_date() produces a complicated format - so we use as.Date() to simplify
+## make sure all date variables are formatted as dates 
+## get the names of variables which are dates
+# DATEVARS <- study_data_dict %>% 
+#   filter(type == "date") %>% 
+#   filter(name %in% names(study_data_cleaned)) %>% 
+#   ## filter to match the column names of your data
+#   pull(name) # select date vars
+# 
+# ## find if there are date variables which are completely empty
+# EMPTY_DATEVARS <- purrr::map(DATEVARS, ~all(
+#   is.na(study_data_cleaned[[.x]])
+#   )) %>% 
+#   unlist() %>% 
+#   which()
+# 
+# ## remove exclude the names of variables which are completely emptys
+# DATEVARS <- DATEVARS[-EMPTY_DATEVARS]
+# 
+# ## change to dates 
+# ## use the parse_date() function to make a first pass at date variables.
+# ## parse_date() produces a complicated format - so we use as.Date() to simplify
+# study_data_cleaned <- study_data_cleaned %>%
+#   mutate(
+#     across(.cols = all_of(DATEVARS),
+#            .fns = ~parsedate::parse_date(.x) %>% as.Date()))
+
+
+## Non-Kobo data -------------------------------------------------------------
+## Use this section if you did not have Kobo data. 
+
+# use the parse_date() function to make a first pass at date variables.
+# parse_date() produces a complicated format - so we use as.Date() to simplify
 study_data_cleaned <- study_data_cleaned %>%
   mutate(
-    across(.cols = all_of(DATEVARS),
-           .fns = ~parsedate::parse_date(.x) %>% as.Date()))
+    across(.cols = matches("date|Date"),
+           .fns  = ~parsedate::parse_date(.x) %>% as.Date()))
+
 ```
 
 
 ### Define recall period
 
-After skipping the section on cleaning dates in *non-Kobo* data, we arrive at a command that defines the "recall period".  
-
-In this vignette, the recall period begins 15 July 2020. We know this because in the data dictionary, the later questions ask about arrivals, departures, births, and deaths since 15 July 2020. *Therefore, we adjust the code so that for every entry in `study_data_cleaned` uses `as.Date("2020-07-15)` as the value in the new column `recall_start`.  
-
-The date for the `recall_end` is assigned to 15 July 2021.  
+The next section of code to run defines the "recall period".  
 
+In this vignette, the recall period is from 15 July 2020 to 15 July 2021, because this is indicated in the data dictionary questions about arrivals, departures, births, and deaths. *Therefore, we adjust the code so that for every entry in `study_data_cleaned` uses `as.Date("2020-07-15)` as the value in the new column `recall_start`, and uses `as.Date("2021-07-15")` as the value in the new column `recall_end`.  
 
 
 ```{r}
@@ -596,18 +804,6 @@ study_data_cleaned <- study_data_cleaned %>%
 
 
 
-### Fix wrong dates
-
-
-We can check the ranges of our dates using `range()`
-
-
-```{r}
-range(study_data_cleaned$date)
-```
-They all appear to be within the expected range (July 2021), so there is no need to perform corrections.  
-
-
 
 ### Create age groups
 
@@ -661,6 +857,242 @@ study_data_cleaned <- study_data_cleaned %>%
     factor(NA)))
 ```
 
+Finally, we run the last command in this chunk which creates a column `age_category` that combines the years groupings and the months groupings into one column, with a specified order.  
+
+```{r}
+## to combine different age categories use the following function 
+## this prioritises the smaller unit, meaning:
+## it will order your age_category from smallest to largest unit 
+## i.e. days first then months then years (depending on which are given)
+study_data_cleaned <- group_age_categories(study_data_cleaned, 
+                                           years  = age_group,
+                                           months = age_group_mon)
+```
+
+
+We can see this ordering if we run a quick table of the new column:
+
+```{r}
+study_data_cleaned %>% 
+  tabyl(age_category) %>% 
+  adorn_pct_formatting()
+```
+
+
+### Using a data dictionary to recode
+
+The datasets in this vignette already use the cleaned values, according to its data dictionary. For example, the town is recorded as "Town A" or "Town B", not as town_a and town_b. 
+
+If your dataset contains values that are "raw", unclean, or not in a display format, you can recode them using the data dictionary and the code in this chunk.  
+
+For example, looking in the data dictionary (`study_data_dict`) we can see that the column `option_name` contains values such as `diarrhoea` and `respiratory_infection` for the cause of death variable. In contrast, the `option_label` contains the display values "Diarrhoea" and "Respiratory infection".  
+
+A command like the below would revise all the raw option values to their display label version, across the entire dataset. The function `match_df()` accepts the name of our data frame, and the dictionary, the columns in the data dictionary to guide the value conversion (`from = ` and `to = `). Note that if provided in the data dictionary, you could also run the code with `to = "option_label_french"` to convert the values to French.  
+
+Again - it is NOT necessary to run this code for this vignette because the values are already in display format.  
+
+```{r, eval=FALSE}
+## recode values with matchmaker package (value labels cant be used for analysis) 
+study_data_cleaned <- match_df(study_data_cleaned, 
+         study_data_dict, 
+         from = "option_name", 
+         to = "option_label", 
+         by = "name", 
+         order = "option_order_in_set")
+```
+
+
+
+
+### Clean factor variables
+
+In R, factors are a column class that indicates an ordinal variable - that is, a variable with values that should have an intrinsic order to them. You can read more about factors in this [Epi R Handbook chapter](https://epirhandbook.com/en/factors.html)
+
+The first R code deals with the column called `consent`, which is present in our dataset. the code converts it from "Yes" or "No" to `TRUE` or `FALSE`. It does this by leveraging a behavior of the `mutate()` function, that if you provide a logical statement (`consent == "Yes"`) then it will return `TRUE` or `FALSE`.  
+
+```{r}
+study_data_cleaned <- study_data_cleaned %>% 
+  mutate(consent = consent == "Yes")
+```
+
+This change is also applied to the `died` column:
+
+```{r}
+study_data_cleaned <- study_data_cleaned %>% 
+  mutate(died = died == "Yes")
+```
+
+
+Subsequent commands in this code chunk show you how to clean categorical variables that may have a specific order. We do not need to do any of these remaining steps, so you should comment out all the remaining code in this chunk. Nevertheless, below is some text explaining them and guiding you to further resources.  
+
+You can recode character values using `case_when()`. You can read more about this in the Data Cleaning chapter of the Epi R Handbook.  
+
+Another command in this code chunk will show you how to use `fct_explicit_na()` to convert `NA` to a specific word such as "Not applicable". You can also read about this in the Factors chapter of the Epidemiologist R Handbook. 
+
+The "fix factor levels" command demonstrates how to set the "order" for a specific categorical variable.
+
+
+
+### Observation time
+
+For rows where it is possible, we need to calculate the observation time. There are several helper functions to assist with this:  
+
+* `find_start_date()` below is set to look in columns `date_birth` (most important) and `date_arrived` (secondary importance) for dates within the constraints of the columns `recall_start` and `recall_end`. The function will create the new columns `startdate` and `startcause`.  
+
+* `find_end_date()` performs the similar action but for the dates in column `date_left` and `date_death`, creating columns `enddate` and `endcause`.  
+
+```{r}
+
+## create new variables for start and end dates/causes
+study_data_cleaned <- study_data_cleaned %>%
+  ## choose earliest date entered in survey
+  ## from births, household arrivals, and camp arrivals 
+  find_start_date("date_birth",
+                  "date_arrived",
+                  period_start = "recall_start",
+                  period_end   = "recall_end",
+                  datecol      = "startdate",
+                  datereason   = "startcause" 
+                 ) %>%
+  ## choose earliest date entered in survey
+  ## from camp departures, death and end of the study
+  find_end_date("date_left",
+                "date_death",
+                period_start = "recall_start",
+                period_end   = "recall_end",
+                datecol      = "enddate",
+                datereason   = "endcause" 
+               ) %>%
+  ## label those that were present at the start/end (except births/deaths)
+  mutate(startcause = if_else(startdate == recall_start & startcause != "birthday_date",
+                              "Present at start", startcause)) %>%
+  mutate(endcause = if_else(enddate == recall_end & endcause != "death_date", 
+                            "Present at end", endcause))
+```
+
+
+These `fct_recode()` functions are changing the values in these "cause" columns to be more human readable.  
+
+```{r}
+## fix factor levels -----------------------------------------------------------
+
+## make sure there are the appropriate levels (names)
+study_data_cleaned$startcause <- fct_recode(study_data_cleaned$startcause,
+                                            "Present at start" = "Present at start",
+                                            "Born" = "date_birth",
+                                            "Other arrival" = "date_arrived"
+                                           )
+
+## make sure there are the appropriate levels (names)
+study_data_cleaned$endcause <- fct_recode(study_data_cleaned$endcause,
+                                          "Present at end" = "Present at end",
+                                          "Died" = "date_death",
+                                          "Other departure" = "date_left")
+```
+
+This `mutate()` command creates the column `obstime` which is the number of days between the start and end dates for each individual.  
+
+
+```{r}
+## Define observation time in days
+study_data_cleaned <- study_data_cleaned %>% 
+  mutate(obstime = as.numeric(enddate - startdate))
+```
+
+Running some summary statistics on these data show that most rows were not able to be calculated:  
+
+```{r}
+summary(study_data_cleaned$obstime)
+```
+
+For row that had data, this is the distribution of `obstime`:  
+
+```{r}
+ggplot(study_data_cleaned, aes(x = obstime))+
+  geom_histogram()
+```
+
+### Labelling columns  
+
+Earlier, we used the {matchmaker} package to clean the *values* in columns, using the data dictionary. In this chunk, we use the {labelled} package to assign labels to the *column names (headings)*, so that when printed they display names with spaces and other human-readable formatting.  
+
+In the command below, we create the object `var_labels`, using the `setNames()` function (from the ackage {stats}). The "short names" from the data dictionary are set as the display labels, while the current variables names are retained.  
+
+```{r}
+## define a list of names and labels based on the dictionary 
+var_labels <- setNames(
+  ## add variable labels as a list
+  as.list(study_data_dict$short_name), 
+  ## name the list with the current variable names
+  study_data_dict$name)
+```
+
+Now we use this object `var_labels` within the function `set_variable_labels()`, to set the labels of our dataset.  
+
+```{r}
+
+## add the variable labels to dataset 
+study_data_cleaned <- study_data_cleaned %>% 
+  set_variable_labels(
+    ## set the labels with the object defined above
+    .labels = var_labels, 
+    ## do not throw an error if some names dont match 
+    ## not all names in the dictionary appear in the dataset 
+    .strict = FALSE)
+```
+
+Lastly, an option is shown for how to manually adjust column labels (if you did not want to use the data dictionary)
+
+
+### Remove unused data  
+
+This chunk contains code to drop and examine rows for which there is no consent, there are missing start or end dates, village_name is "Other", age is missing, or sex is missing. These rows are first saved as `dropped`. This allows you to inspect them before actually dropping the rows.
+
+In the second command, an `anti_join()` is used to actually drop the rows from `study_data_cleaned`. An anti join is a "filtering join" which looks in the `dropped` data frame and leaves only rows in `study_data_cleaned` which are *not* present in `dropped`. Its a fancy way of doing a filter, but allowing you the opportunity to inspect the rows first.  
+
+
+```{r}
+## store the cases that you drop so you can describe them (e.g. non-consenting 
+## or wrong village/cluster)
+dropped <- study_data_cleaned %>% 
+  filter(!consent | is.na(startdate) | is.na(enddate) | 
+           ## note that whatever you use for weights cannot be missing!
+           village_name == "Other"| is.na(age_years) | is.na(sex))
+
+## use the dropped cases to remove the unused rows from the survey data set  
+study_data_cleaned <- anti_join(study_data_cleaned, dropped, by = names(dropped))
+```
+
+
+### Drop duplicates  
+
+Deduplication is a complicated topic. We suggest you review the Epi R Handbook chapter on [Deduplication](https://epirhandbook.com/en/de-duplication.html) if you want to seriously approach this topic.
+
+In this code chunk, a simple deduplication command is offered using the `distinct()` function. In this example, for any rows that have identical `uid`, `sex`, AND `age_group`, only the first row is kept. The `.keep_all = TRUE` refers to the *columns* and ensures that all columns are kept, not only the ones you used to assess duplicates.  
+
+
+```{r}
+## option 1: only keep the first occurrence of duplicate case 
+study_data_cleaned <- study_data_cleaned %>% 
+  ## find duplicates based on case number, sex and age group 
+  ## only keep the first occurrence 
+  distinct(uid, sex, age_group, .keep_all = TRUE)
+  
+```
+
+A second option available to you is commented out. This option allows you to inspect duplicates before they are filtered/removed.  
+
+
+### Survey weights
+
+Its a cluster survey but because we have poip counts for age and sex, we are able to adjust to reflect the population better and produce stratefied estimate by age and sex. 
+
+```{r}
+
+```
+
+
+survey design- delete the others and just run strat cluster
 
 
 # we can wait on this for the study protocol 

From 2ec4fd326be8e92ff08cd84ad273631ff90905b7 Mon Sep 17 00:00:00 2001
From: Neale Batra <52152191+nsbatra@users.noreply.github.com>
Date: Tue, 20 Sep 2022 13:15:34 +0200
Subject: [PATCH 2/5] fix as.Date in survey template

---
 inst/rmarkdown/templates/mortality/skeleton/skeleton.Rmd | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/inst/rmarkdown/templates/mortality/skeleton/skeleton.Rmd b/inst/rmarkdown/templates/mortality/skeleton/skeleton.Rmd
index 1c7a5ea5..f45b88a8 100644
--- a/inst/rmarkdown/templates/mortality/skeleton/skeleton.Rmd
+++ b/inst/rmarkdown/templates/mortality/skeleton/skeleton.Rmd
@@ -586,7 +586,7 @@ study_data_cleaned <- study_data_cleaned %>%
 ## parse_date() produces a complicated format - so we use as.Date() to simplify# study_data_cleaned <- study_data_cleaned %>%
 #   mutate(
 #     across(.cols = matches("date|Date"),
-#            .fns  = ~parsedate::parse_date(.x)))
+#            .fns  = ~parsedate::parse_date(.x) %>% as.Date()))
 
 
 ## Define recall period --------------------------------------------------------

From 6791cfdb6cdafccd7e7444516d7af027e8363c8b Mon Sep 17 00:00:00 2001
From: Neale Batra <52152191+nsbatra@users.noreply.github.com>
Date: Tue, 20 Sep 2022 15:28:02 +0200
Subject: [PATCH 3/5] add weights to survey walkthrough

---
 vignettes/Surveys_Walkthrough.Rmd | 198 +++++++++++++++++++++++-------
 1 file changed, 156 insertions(+), 42 deletions(-)

diff --git a/vignettes/Surveys_Walkthrough.Rmd b/vignettes/Surveys_Walkthrough.Rmd
index aa3d6664..65cc390b 100644
--- a/vignettes/Surveys_Walkthrough.Rmd
+++ b/vignettes/Surveys_Walkthrough.Rmd
@@ -604,13 +604,16 @@ Next, we want to rename some of our columns. Using the command `msf_dict_rename_
 We can edit the above, or simply refer to it to construct our `rename()` command, as below:   
 
 ```{r}
-study_data_cleaned <- rename(
-  study_data_cleaned,
+study_data_cleaned <- rename(study_data_cleaned,
+  uid = `_index.y`,
   consent = household_consents_to_particip,
   date_arrived = doa,
   date_birth = dob,
   date_left = dod,
-  date_died = dodeath)
+  date_death = dodeath,
+  village_name = location,
+  member_number = no_household
+  )
 
 ```
 
@@ -675,7 +678,7 @@ This vignette does not include population data, so in the chunk `read_population
 
 * We set the total population as 10,000, as a default assumption.  
 * We leave the proportion estimates as written  
-* We have observations from "Town A" and "Town B" (see column `location` in the `survey_data_ind` data frame), so we edit the inputs to the `health_district` column as written in the final line of each command (see below).  
+* We have observations from "Town A" and "Town B", so we edit the inputs to the `health_district` column as written in the final line of each command (see below).  
 
 We run all the uncommented code provided in the template to generate the population estimates and combine them into one data frame.  
 
@@ -688,7 +691,7 @@ population_data_age_district_a <- gen_population(total_pop = 10000, # set total
   rename(age_group  = groups,                      # rename columns (NEW NAME = OLD NAME)
          sex        = strata,
          population = n) %>% 
-  mutate(health_district = "Town A")           # add a column to identify region 
+  mutate(village_name = "Town A")           # add a column to identify region 
 
 
 ## generate population data by age groups in years for district B
@@ -699,7 +702,7 @@ population_data_age_district_b <- gen_population(total_pop = 10000, # set total
   rename(age_group  = groups,                      # rename columns (NEW NAME = OLD NAME)
          sex        = strata,
          population = n) %>% 
-  mutate(health_district = "Town B")           # add a column to identify region 
+  mutate(village_name = "Town B")           # add a column to identify region 
 
 
 
@@ -712,12 +715,82 @@ population_data_age <- bind_rows(population_data_age_district_a,
 
 ### Cluster counts
 
-In the cluster counts chunk, we specify that Town A has 500 households, whereas Town B has 700.  
+We can see that there are 17 clusters, from each town:  
+
+```{r}
+study_data_cleaned %>% 
+  tabyl(cluster_number, village_name)
+```
+
+<!-- We can also see from the ordering in the table above, that cluster number is recognized as a character and not as a number, so we fix this with a quick `mutate()` command:   -->
+
+<!-- ```{r} -->
+<!-- study_data_cleaned <- study_data_cleaned %>%  -->
+<!--   mutate(cluster_number = as.integer(cluster_number)) -->
+<!-- ``` -->
+
+The fact that there are clusters 1-17 in each of the Towns will complicate later analyses. Each cluster should have a unique identification value. So, let us create one. We use the `str_glue()` function from {stringr} to combine the cluster number and the letter of the town. The letter of the town is extracted from the town name using `str_sub()`, which is also from the {stringr} package. The -1 extracts the last letter of the village name, and places it into the ID.  
+
+```{r}
+study_data_cleaned <- study_data_cleaned %>% 
+  mutate(cluster_number_uid = str_glue(
+    "{town_letter}_{cluster_number}",
+    town_letter = str_sub(village_name, -1)))
+```
+
+We verify:
+
+```{r}
+study_data_cleaned %>% 
+  tabyl(cluster_number_uid, village_name)
+```
+
+
+Now, our task is to create a *new* data frame that contains the number of households in each cluster. This is not the number of households chosen to be interviewed, but the universe of *possible* households that could have been chosen in each cluster.  
+
+To create a *new* dataframe, the R Markdown template uses the `tibble()` function for your to manually input the names of the clusters, and the number of households. Below, we use a slight adaptation for ease of use: we use the `tribble()` function (note the "r") so that we can type this information in "rows" that look like a normal data frame. Note how the columns are specified at the top with tildes (~).  
+
+  
 
 ```{r cluster_counts}
 
-cluster_counts <- tibble(cluster = c("Town A", "Town B"), 
-                         households = c(500, 700))
+cluster_counts <- tribble(
+  ~cluster, ~households,
+  "A_1",     100,
+  "A_2", 100, 
+  "A_3", 100, 
+  "A_4", 100,
+  "A_5", 100,
+  "A_6", 100, 
+  "A_7", 100,
+  "A_8", 100, 
+  "A_9", 100, 
+  "A_10", 100, 
+  "A_11", 100, 
+  "A_12", 100, 
+  "A_13", 100,
+  "A_14", 100, 
+  "A_15", 100, 
+  "A_16", 100, 
+  "A_17", 100, 
+  
+  "B_1", 100,
+  "B_2", 100, 
+  "B_3", 100, 
+  "B_4", 100,
+  "B_5", 100,
+  "B_6", 100, 
+  "B_7", 100,
+  "B_8", 100, 
+  "B_9", 100, 
+  "B_10", 100, 
+  "B_11", 100, 
+  "B_12", 100, 
+  "B_13", 100,
+  "B_14", 100, 
+  "B_15", 100, 
+  "B_16", 100, 
+  "B_17", 100)
 ```
 
 
@@ -949,15 +1022,17 @@ study_data_cleaned <- study_data_cleaned %>%
   ## from births, household arrivals, and camp arrivals 
   find_start_date("date_birth",
                   "date_arrived",
+                  "recall_start",
                   period_start = "recall_start",
                   period_end   = "recall_end",
                   datecol      = "startdate",
                   datereason   = "startcause" 
                  ) %>%
-  ## choose earliest date entered in survey
+  ## choose latest date entered in survey
   ## from camp departures, death and end of the study
   find_end_date("date_left",
                 "date_death",
+                "recall_end",
                 period_start = "recall_start",
                 period_end   = "recall_end",
                 datecol      = "enddate",
@@ -999,65 +1074,52 @@ study_data_cleaned <- study_data_cleaned %>%
   mutate(obstime = as.numeric(enddate - startdate))
 ```
 
-Running some summary statistics on these data show that most rows were not able to be calculated:  
+Running some summary statistics on these data show that most rows did not have births or deaths, and so their observation time reverted to the default of the recall period (1 year).  
 
 ```{r}
 summary(study_data_cleaned$obstime)
 ```
 
-For row that had data, this is the distribution of `obstime`:  
-
-```{r}
-ggplot(study_data_cleaned, aes(x = obstime))+
-  geom_histogram()
-```
 
 ### Labelling columns  
 
 Earlier, we used the {matchmaker} package to clean the *values* in columns, using the data dictionary. In this chunk, we use the {labelled} package to assign labels to the *column names (headings)*, so that when printed they display names with spaces and other human-readable formatting.  
 
-In the command below, we create the object `var_labels`, using the `setNames()` function (from the ackage {stats}). The "short names" from the data dictionary are set as the display labels, while the current variables names are retained.  
+We will use the code for manual labelling, because we have adjusted our columns names so they no longer align with our data dictionary.  
 
 ```{r}
-## define a list of names and labels based on the dictionary 
-var_labels <- setNames(
-  ## add variable labels as a list
-  as.list(study_data_dict$short_name), 
-  ## name the list with the current variable names
-  study_data_dict$name)
-```
-
-Now we use this object `var_labels` within the function `set_variable_labels()`, to set the labels of our dataset.  
-
-```{r}
-
-## add the variable labels to dataset 
+## it is possible to update individual variables manually too
 study_data_cleaned <- study_data_cleaned %>% 
   set_variable_labels(
-    ## set the labels with the object defined above
-    .labels = var_labels, 
-    ## do not throw an error if some names dont match 
-    ## not all names in the dictionary appear in the dataset 
-    .strict = FALSE)
+    ## variable name = variable label 
+    age_years     = "Age (years)",
+    age_group     = "Age group (years)",
+    age_months    = "Age (months)", 
+    age_group_mon = "Age group (months)",
+    age_category  = "Age category", 
+    died          = "Died", 
+    startcause    = "Observation start", 
+    endcause      = "Observation end"
+    )
 ```
 
-Lastly, an option is shown for how to manually adjust column labels (if you did not want to use the data dictionary)
+
 
 
 ### Remove unused data  
 
-This chunk contains code to drop and examine rows for which there is no consent, there are missing start or end dates, village_name is "Other", age is missing, or sex is missing. These rows are first saved as `dropped`. This allows you to inspect them before actually dropping the rows.
+This chunk contains code to drop and examine rows for which there is no consent, there are missing start or end dates, village name (town A or B) is "Other", age is missing, or sex is missing. These rows are first saved as `dropped`. This allows you to inspect them before actually dropping the rows.
 
 In the second command, an `anti_join()` is used to actually drop the rows from `study_data_cleaned`. An anti join is a "filtering join" which looks in the `dropped` data frame and leaves only rows in `study_data_cleaned` which are *not* present in `dropped`. Its a fancy way of doing a filter, but allowing you the opportunity to inspect the rows first.  
 
 
-```{r}
+```{r, eval=FALSE}
 ## store the cases that you drop so you can describe them (e.g. non-consenting 
 ## or wrong village/cluster)
 dropped <- study_data_cleaned %>% 
   filter(!consent | is.na(startdate) | is.na(enddate) | 
            ## note that whatever you use for weights cannot be missing!
-           village_name == "Other"| is.na(age_years) | is.na(sex))
+           is.na(village_name) | is.na(age_years) | is.na(sex))
 
 ## use the dropped cases to remove the unused rows from the survey data set  
 study_data_cleaned <- anti_join(study_data_cleaned, dropped, by = names(dropped))
@@ -1085,14 +1147,66 @@ A second option available to you is commented out. This option allows you to ins
 
 ### Survey weights
 
-Its a cluster survey but because we have poip counts for age and sex, we are able to adjust to reflect the population better and produce stratefied estimate by age and sex. 
+These data come from a cluster survey, but because we have population counts for age and sex, we are able to make adjustments to better reflect the population, and therefore produce stratified estimates by age and sex. 
+
+At the end of the first command, we remove "health_district" because we only want to stratify by age and sex.  
+
+
+```{r}
+
+## create a variable called "surv_weight_strata" 
+## contains weights for each individual - by age group, sex and health district
+study_data_cleaned <- add_weights_strata(x = study_data_cleaned, 
+                                         p = population_data_age, 
+                                         surv_weight = "surv_weight_strata",
+                                         surv_weight_ID = "surv_weight_ID_strata",
+                                         age_group, sex, village_name)
+```
+
+
+In the second set of commands:  
+
+* The data frame `cluster_counts` is referenced, which we created in an earlier step. The arguments that end with `_cl` should reference columns in this data frame. Use the help documentation for this function by running `?add_weights_cluster`.  
+
+
 
 ```{r}
+## cluster ---------------------------------------------------------------------
 
+## get the number of individuals interviewed per household 
+## adds a variable with counts of the household (parent) index variable
+study_data_cleaned <- study_data_cleaned %>% 
+  add_count(index, name = "interviewed")
+
+study_data_cleaned <- study_data_cleaned %>% 
+  mutate(member_number = as.numeric(member_number))
+
+
+## create cluster weights 
+study_data_cleaned <- add_weights_cluster(x = study_data_cleaned, 
+                                          cl = cluster_counts, 
+                                          eligible = member_number, 
+                                          interviewed = interviewed, 
+                                          cluster_x = cluster_number_uid, 
+                                          cluster_cl = cluster, 
+                                          household_x = id, 
+                                          household_cl = households, 
+                                          surv_weight = "surv_weight_cluster", 
+                                          surv_weight_ID = "surv_weight_ID_cluster", 
+                                          ignore_cluster = FALSE, 
+                                          ignore_household = FALSE)
+
+## stratified and cluster ------------------------------------------------------
+
+## create a survey weight for cluster and strata 
+study_data_cleaned <- study_data_cleaned %>% 
+  mutate(surv_weight_cluster_strata = surv_weight_strata * surv_weight_cluster)
 ```
 
 
-survey design- delete the others and just run strat cluster
+
+
+
 
 
 # we can wait on this for the study protocol 

From 52085a269f80cfbe7ee3708a13209cafb5c1b71f Mon Sep 17 00:00:00 2001
From: Neale Batra <52152191+nsbatra@users.noreply.github.com>
Date: Tue, 27 Sep 2022 09:14:28 +0200
Subject: [PATCH 4/5] add surveys vignette and build

---
 docs/pkgdown.yml                  |   2 +-
 vignettes/Surveys_Walkthrough.Rmd | 442 ++++++++++++++++++++++++++++++
 2 files changed, 443 insertions(+), 1 deletion(-)

diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 9e7b522e..bc9a8627 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -5,7 +5,7 @@ articles:
   Background: Background.html
   Outbreaks_Walkthrough: Outbreaks_Walkthrough.html
   Surveys_Walkthrough: Surveys_Walkthrough.html
-last_built: 2022-09-19T19:00Z
+last_built: 2022-09-27T07:13Z
 urls:
   reference: https://r4epi.github.io/sitrep/reference
   article: https://r4epi.github.io/sitrep/articles
diff --git a/vignettes/Surveys_Walkthrough.Rmd b/vignettes/Surveys_Walkthrough.Rmd
index 65cc390b..30a12bfc 100644
--- a/vignettes/Surveys_Walkthrough.Rmd
+++ b/vignettes/Surveys_Walkthrough.Rmd
@@ -1206,6 +1206,448 @@ study_data_cleaned <- study_data_cleaned %>%
 
 
 
+In the next chunk, we use only the "stratified cluster" code:  
+
+* We change `village_name` to `cluster_number_uid`, which is our unique cluster ID column.  
+* We change `health_district` to `village_name`, as this is our strata
+
+
+```{r survey_design}
+
+## simple random ---------------------------------------------------------------
+# 
+# survey_design_simple <- study_data_cleaned %>% 
+#   as_survey_design(ids = 1, # 1 for no cluster ids 
+#                    weights = NULL, # No weight added
+#                    strata = NULL # sampling was simple (no strata)
+#                   )
+# 
+# ## stratified ------------------------------------------------------------------
+# 
+# survey_design_strata <- study_data_cleaned %>% 
+#   as_survey_design(ids = 1, # 1 for no cluster ids 
+#                    weights = surv_weight_strata, # weight variable created above 
+#                    strata = health_district # sampling was stratified by district
+#                   )
+# 
+# ## cluster ---------------------------------------------------------------------
+# 
+# survey_design_cluster <- study_data_cleaned %>% 
+#   as_survey_design(ids = village_name, # cluster ids 
+#                    weights = surv_weight_cluster, # weight variable created above 
+#                    strata = NULL # sampling was simple (no strata)
+#                   )
+
+## stratified cluster ----------------------------------------------------------
+
+survey_design <- study_data_cleaned %>% 
+  as_survey_design(ids = cluster_number_uid, # cluster ids 
+                   weights = surv_weight_cluster_strata, # weight variable created above 
+                   strata = village_name # sampling was stratified by district
+                  )
+
+```
+
+
+
+
+
+
+
+
+
+Run these to get the number of distinct
+Again, adapt `cluster_number` to `cluster_number_uid`.  
+
+
+```{r inclusion_counts}
+
+## get counts of number of clusters 
+num_clus <- study_data_cleaned %>%
+  ## trim data to unique clusters
+  distinct(cluster_number_uid) %>% 
+  ## get number of rows (count how many unique)
+  nrow()
+
+## get counts of number households 
+num_hh <- study_data_cleaned %>% 
+  ## get unique houses by cluster
+  distinct(cluster_number, id) %>% 
+  ## get number of rounds (count how many unique)
+  nrow()
+```
+
+Print to view
+
+```{r}
+num_clus
+
+num_hh
+```
+The dynamic text in the report will read as:  
+
+
+
+We included `r num_hh` households across `r num_clus` clusters in this survey analysis. 
+
+
+Among the `r nrow(dropped)` individuals excluded from the survey analysis, 
+`r fmt_count(dropped, consent)` individuals were excluded due to missing 
+start- or end-dates and `r fmt_count(dropped, !consent)` were excluded 
+for lack of consent. The reasons for no consent are shown below. 
+
+In our dataset, the reason for refusal was not collected, so the next section is not relevant.  
+
+
+
+```{r cluster_hh_size}
+
+## get counts of the number of households per cluster
+clustersize <- study_data_cleaned %>% 
+  ## trim data to only unique households within each cluster
+  distinct(cluster_number_uid, id) %>%
+  ## count the number of households within each cluster
+  count(cluster_number_uid) %>% 
+  pull(n)
+
+## get the median number of households per cluster
+clustermed <- median(clustersize)
+
+## get the min and max number of households per cluster
+## paste these together seperated by a dash 
+clusterrange <- str_c(range(clustersize), collapse = "--")
+
+## get counts of children per household 
+## do this by cluster as household IDs are only unique within clusters
+hhsize <- study_data_cleaned %>% 
+  count(cluster_number_uid, id) %>%
+  pull(n) 
+
+## get median number of children per household
+hhmed <- median(hhsize)
+## get the min and max number of children per household
+## paste these together seperated by a dash 
+hhrange <- str_c(range(hhsize), collapse = "--")
+
+## get standard deviation 
+hhsd <- round(sd(hhsize), digits = 1)
+```
+
+
+The median number of households per cluster was
+`r clustermed`, with a range of `r clusterrange`. The median number of children
+per household was `r hhmed` (range: `r hhrange`, standard deviation: `r hhsd`). 
+
+
+## Demographic information
+
+```{r descriptive_sampling_bias, warning = FALSE}
+## counts and props of the study population
+ag <- tabyl(study_data_cleaned, age_group, show_na = FALSE) %>% 
+  mutate(n_total = sum(n), 
+         age_group = fct_inorder(age_group))
+
+
+## counts and props of the source population
+propcount <- population_data_age %>% 
+  group_by(age_group) %>%
+    tally(population) %>%
+    mutate(percent = n / sum(n))
+
+## bind together the columns of two tables, group by age, and perform a 
+## binomial test to see if n/total is significantly different from population
+## proportion.
+  ## suffix here adds to text to the end of columns in each of the two datasets
+left_join(ag, propcount, by = "age_group", suffix = c("", "_pop")) %>%
+  group_by(age_group) %>%
+
+  ## broom::tidy(binom.test()) makes a data frame out of the binomial test and
+  ## will add the variables p.value, parameter, conf.low, conf.high, method, and
+  ## alternative. We will only use p.value here. You can include other
+  ## columns if you want to report confidence intervals
+  mutate(binom = list(broom::tidy(binom.test(n, n_total, percent_pop)))) %>%
+  unnest(cols = c(binom)) %>% # important for expanding the binom.test data frame
+  mutate(
+    across(.cols = contains("percent"), 
+            .fns = ~.x * 100)) %>%
+
+  ## Adjusting the p-values to correct for false positives 
+  ## (because testing multiple age groups). This will only make 
+  ## a difference if you have many age categories
+  mutate(p.value = p.adjust(p.value, method = "holm")) %>%
+                      
+  ## Only show p-values over 0.001 (those under report as <0.001)
+  mutate(p.value = ifelse(p.value < 0.001, "<0.001", as.character(round(p.value, 3)))) %>%
+
+  ## rename the columns appropriately
+  select(
+    "Age group" = age_group,
+    "Study population (n)" = n,
+    "Study population (%)" = percent,
+    "Source population (n)" = n_pop,
+    "Source population (%)" = percent_pop,
+    "P-value" = p.value
+  ) %>%
+  # produce styled output table with auto-adjusted column widths with {flextable}
+  qflextable() %>% 
+  # make header text bold (using {flextable})
+  bold(part = "header") %>% 
+  # make your table fit to the maximum width of the word document
+  set_table_properties(layout = "autofit") %>% 
+  ## set to only show 1 decimal place 
+  colformat_double(digits = 1)
+```
+
+
+
+
+```{r median_age_sex_ratios}
+## compute the median age 
+medage <- median(study_data_cleaned$age_years)
+## paste the lower and upper quartile together
+iqr <- str_c(  # basically copy paste together the following
+  ## calculate the 25% and 75% of distribution, with missings removed
+  quantile(     
+    study_data_cleaned$age_years, 
+    probs = c(0.25, 0.75), 
+    na.rm = TRUE), 
+  ## between lower and upper place an en-dash
+  collapse = "--")
+
+
+## compute overall sex ratio 
+sex_ratio <- study_data_cleaned %>% 
+  count(sex) %>% 
+  pivot_wider(names_from = sex, values_from = n) %>%
+  mutate(ratio = round(Male/Female, digits = 1)) %>%
+  pull(ratio)
+
+## compute sex ratios by age group 
+sex_ratio_age <- study_data_cleaned %>% 
+  count(age_group, sex) %>% 
+  pivot_wider(names_from = sex, values_from = n) %>%
+  mutate(ratio = round(Male/Female, digits = 1)) %>%
+  select(age_group, ratio)
+
+## sort table by ascending ratio then select the lowest (first)
+min_sex_ratio_age <- arrange(sex_ratio_age, ratio) %>% slice(1)
+```
+
+
+Pregnancy was not collected in this survey, so the next section is not relevant and should be commented out. Any of the dynamic text that refers to pregnancy should also be removed.  
+
+The paragraph will now look like this:  
+
+
+Among the `r nrow(study_data_cleaned)` surveyed individuals, there were 
+`r fmt_count(study_data_cleaned, sex == "Female")` females and 
+`r fmt_count(study_data_cleaned, sex == "Male")` males (unweighted). The male to
+female ratio was `r sex_ratio` in the surveyed population. The lowest male to
+female ratio was `r min_sex_ratio_age$ratio` in the 
+`r min_sex_ratio_age$age_group` year age group.
+The median age of surveyed individuals was `r medage` years (Q1-Q3 of `r iqr`
+years). Children under five years of age made up 
+`r fmt_count(study_data_cleaned, age_years < 5)`of the surveyed individuals.
+The highest number of surveyed individuals (unweighted) were in the 
+`r table(study_data_cleaned$age_group) %>% which.max() %>% names()`
+year age group.
+
+
+```{r describe_by_age_group_and_sex}
+
+# get cross tabulated counts and proportions
+study_data_cleaned %>% 
+  tbl_cross( 
+    row = age_group, 
+    col = sex, 
+    percent = "cell") %>% 
+  ## make variable names bold 
+  bold_labels() %>% 
+  # change to flextable format
+  as_flex_table() %>%
+  # make header text bold (using {flextable})
+  bold(part = "header") %>% 
+  # make your table fit to the maximum width of the word document
+  set_table_properties(layout = "autofit")
+```
+
+
+
+
+
+```{r describe_by_age_category_and_sex}
+
+# get cross tabulated counts and proportions
+study_data_cleaned %>% 
+  tbl_cross( 
+    row = age_category, 
+    col = sex, 
+    percent = "cell") %>% 
+  ## make variable names bold 
+  bold_labels() %>% 
+  # change to flextable format
+  as_flex_table() %>%
+  # make header text bold (using {flextable})
+  bold(part = "header") %>% 
+  # make your table fit to the maximum width of the word document
+  set_table_properties(layout = "autofit")
+```
+
+
+
+
+
+```{r age_pyramid, warning=FALSE}
+
+age_pyramid(study_data_cleaned, 
+            age_group, 
+            split_by = sex, 
+            proportional = TRUE) + 
+  labs(y = "Proportion", x = "Age group (years)") +    # change axis labels
+  theme(legend.position = "bottom",     # move legend to bottom
+        legend.title = element_blank(), # remove title
+        text = element_text(size = 18)  # change text size
+       )
+```
+
+
+
+
+Replace `health_district` with `village_name`.  
+
+
+```{r age_pyramid_strata, warning=FALSE}
+
+age_pyramid(study_data_cleaned, 
+                 age_group, 
+                 split_by = sex,
+                 stack_by = village_name,
+                 proportional = TRUE, 
+                 pal = c("red", "blue")) + 
+  labs(y = "Proportion", x = "Age group (years)") +    # change axis labels
+  theme(legend.position = "bottom",     # move legend to bottom
+        legend.title = element_blank(), # remove title
+        text = element_text(size = 18)  # change text size
+       )
+```
+
+
+```{r age_pyramid_survey, warning=FALSE}
+
+age_pyramid(survey_design,
+                 age_group,
+                 split_by = sex, 
+                 proportion = TRUE) +
+  labs(y = "Proportion (weighted)", x = "Age group (years)") + # change axis labels
+  theme(legend.position = "bottom",     # move legend to bottom
+        legend.title = element_blank(), # remove title
+        text = element_text(size = 18)  # change text size
+       )
+```
+
+
+## Mortality
+```{r CMR, warning = FALSE, message = FALSE}
+
+## weighted counts and proportion of dead
+death_props <- survey_design %>% 
+  select(died) %>% 
+  tbl_svysummary() %>% 
+  ## add the weighted total
+  add_n() %>%   
+  ## add in confidence intervals
+  
+  ## add in deff 
+  
+  ## modify the column headers
+  modify_header(
+    list(
+      n ~ "**Weighted total (N)**",
+      stat_0 ~ "**Weighted Count (n)**"
+    )
+    )
+
+## mortality per 10,000 persons/day with CI
+CMR <- survey_design %>% 
+  ## survey ratio used to account for observation time 
+  summarize(mortality = survey_ratio(died * 10000, obstime, vartype = "ci")) %>% 
+  ## if negative CIs set to zero
+  mutate(mortality_low = if_else(mortality_low < 0, 0, mortality_low), 
+         mortality_upp = if_else(mortality_upp < 0, 0, mortality_upp)) %>% 
+  ## merge confidence intervals for mortality in to one column (do not change to percent)
+  unite_ci("Mortality", starts_with("mortality"), m100 = FALSE, percent = FALSE) %>%
+  pull("Mortality")
+```
+
+And the paragraph will read as:  
+
+
+During the recall period the weighted number and proportion of deaths in the 
+population was `r inline_text(death_props, variable = "died",  column = "stat_0")`,
+with a weighted confidence interval of
+`r #inline_text(death_props, variable = "died",  column = "add_stat_1")`, and a 
+design effect of `r #inline_text(death_props, variable = "died",  column = "add_stat_2")`.
+This is a crude mortality rate of `r CMR` deaths per 10000 person-days. 
+
+
+
+Below, again, we replace `health_district` with `village_name`
+
+```{r CMR_strata, warning = FALSE, message = FALSE}
+
+## weighted counts and proportion of dead
+death_props_strat <- survey_design %>% 
+  select(died, village_name) %>%
+  tbl_svysummary(by = village_name) %>% 
+  ## add the weighted total
+  add_n() %>%   
+  ## add in confidence intervals
+
+  ## add in deff 
+
+  ## modify the column headers
+  modify_header(
+    list(
+      n ~ "**Weighted total (N)**",
+      stat_1 ~ "**District A Weighted Count (n)** \n N={n}", 
+      stat_2 ~ "**District B Weighted Count (n)** \n N={n}" 
+    )
+    )
+
+
+## mortality per 10,000 persons/day with CI
+CMR_strat <- survey_design %>% 
+  group_by(village_name) %>% 
+  ## survey ratio used to account for observation time 
+  summarize(mortality = survey_ratio(as.numeric(died) * 10000, obstime, vartype = "ci")) %>% 
+  ## if negative CIs set to zero
+  mutate(mortality_low = if_else(mortality_low < 0, 0, mortality_low), 
+         mortality_upp = if_else(mortality_upp < 0, 0, mortality_upp)) %>% 
+  ## merge confidence intervals for mortality in to one column (do not change to percent)
+  unite_ci("Mortality", starts_with("mortality"), m100 = FALSE, percent = FALSE, digits = 1)
+
+
+```
+
+We also edit the in-line code (dynamic text) so that any reference to `health_district` changes to `village_name`, and "district_a" and "district_b" are changed to "Town A", and "Town B".  
+
+
+<!-- In District A the weighted number of deaths was  -->
+<!-- `r inline_text(death_props_strat, variable = "died",  column = "stat_1")`,  -->
+<!-- which gives a weighted proportion of  -->
+<!-- `r #death_props_strat %>% pull("Town A ci")`, and a design effect of -->
+<!-- `r #death_props_strat %>% pull("district_a deff") %>% round(digits = 3)`.   -->
+<!-- In comparison, the weighted number of deaths in District B was -->
+<!-- `r inline_text(death_props_strat, variable = "died",  column = "stat_2")`,  -->
+<!-- the weighted proportion was  -->
+<!-- `r #death_props_strat %>% pull("district_b ci")` and the design effect was  -->
+<!-- `r #death_props_strat %>% pull("district_b deff") %>% round(digits = 3)`.   -->
+<!-- The crude mortality rate in District A was  -->
+<!-- `r CMR_strat %>% filter(village_name == "Town A") %>% pull(Mortality)` -->
+<!-- deaths per 10000 person-days and in District B was  -->
+<!-- `r CMR_strat %>% filter(village_name == "Town B") %>% pull(Mortality)` -->
+
+
 
 
 

From d3fbfc11832e8ce92e0b0f759cd1110da8ce21b3 Mon Sep 17 00:00:00 2001
From: Neale Batra <52152191+nsbatra@users.noreply.github.com>
Date: Tue, 27 Sep 2022 11:25:31 +0200
Subject: [PATCH 5/5] update survey vig and build

---
 docs/pkgdown.yml                  |   2 +-
 vignettes/Surveys_Walkthrough.Rmd | 176 ++++++++++++++++--------------
 2 files changed, 94 insertions(+), 84 deletions(-)

diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index bc9a8627..e0047f26 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -5,7 +5,7 @@ articles:
   Background: Background.html
   Outbreaks_Walkthrough: Outbreaks_Walkthrough.html
   Surveys_Walkthrough: Surveys_Walkthrough.html
-last_built: 2022-09-27T07:13Z
+last_built: 2022-09-27T09:21Z
 urls:
   reference: https://r4epi.github.io/sitrep/reference
   article: https://r4epi.github.io/sitrep/articles
diff --git a/vignettes/Surveys_Walkthrough.Rmd b/vignettes/Surveys_Walkthrough.Rmd
index 30a12bfc..181c5b47 100644
--- a/vignettes/Surveys_Walkthrough.Rmd
+++ b/vignettes/Surveys_Walkthrough.Rmd
@@ -1,6 +1,6 @@
 ---
 title: "{sitrep} surveys template vignette"
-subtitle: "A guided example of how to use the R Markdown template to analyse a CLUSTER SURVEY (TODO)"
+subtitle: "A guided example of how to use the R Markdown template to analyse a stratified cluster survey"
 output: 
   rmarkdown::html_vignette:
     toc: true
@@ -16,13 +16,15 @@ knitr::opts_chunk$set(
   message = FALSE,
   collapse = TRUE,
   comment = "#>",
-  echo = TRUE
+  echo = TRUE,
+  fig.width = 6,
+  fig.height = 6
 )
 ```
 
 ## Overview
 
-This page demonstrate use of the {sitrep} R Markdown template for analysis of a retrospective mortality survey, using data that was produced using Kobo, a common survey and data collection tool in settings where MSF works.
+This page demonstrate use of the {sitrep} R Markdown template for analysis of a retrospective mortality survey, using data that was produced using Kobo, a common survey and data collection tool in settings where MSF works. The data do not use the standard MSF EBB-approved data dictionary, and therefore represent a challenging use case for data cleaning.  
 
 ## Getting started
 
@@ -134,7 +136,7 @@ The templates can accommodate analysis of data from all of these sampling design
 
 ### Sample size
 
-Before implementing a survey you will need to calculate the sample size for that survey.
+Before implementing a survey you will need to calculate the sample size for that survey. Note that a chapter on samples size is anticipated to be in the [Epidemiologist R Handbook](www.epiRhandbook.com) soon.  
 
 When calculating a sample size for your survey you take the below parameters into consideration:
 
@@ -417,6 +419,8 @@ study_data_cleaned <- study_data_raw
 
 Next, we want to rename some of our columns. Using the command `msf_dict_rename_helper("mortality", varnames = "name")` we get a "helped" command copied to our clipboard. This contains many more variables than we need, but it is useful to review.  
 
+<details><summary>Click to see this code chunk></summary>
+
 ```{r, eval=FALSE, echo = TRUE}
 
 ## Add the appropriate column names after the equals signs
@@ -601,22 +605,35 @@ Next, we want to rename some of our columns. Using the command `msf_dict_rename_
 
 ```
 
+</details>
+
+
 We can edit the above, or simply refer to it to construct our `rename()` command, as below:   
 
 ```{r}
 study_data_cleaned <- rename(study_data_cleaned,
+  # pattern is NEW name = OLD name
   uid = `_index.y`,
   consent = household_consents_to_particip,
+  age_years = age_in_years,       
+  age_months = age_in_months,
   date_arrived = doa,
   date_birth = dob,
   date_left = dod,
   date_death = dodeath,
-  village_name = location,
   member_number = no_household
   )
 
 ```
 
+In the template, there is a command that creates the column `health_district`. For us, this information is already stored in the column `location`. So we run this command to re-name `location` as `health_district`.  
+
+```{r}
+study_data_cleaned <- rename(study_data_cleaned,
+  health_district = location)
+
+```
+
 Finally, we run the command to clean the column names. The `clean_names()` function from the {janitor} package will standardise the syntax of all the column names (headers) by converting all to lowercase, replacing spaces and special characters with underscores, etc.  
 
 ```{r}
@@ -691,7 +708,7 @@ population_data_age_district_a <- gen_population(total_pop = 10000, # set total
   rename(age_group  = groups,                      # rename columns (NEW NAME = OLD NAME)
          sex        = strata,
          population = n) %>% 
-  mutate(village_name = "Town A")           # add a column to identify region 
+  mutate(health_district = "Town A")           # add a column to identify region 
 
 
 ## generate population data by age groups in years for district B
@@ -702,7 +719,7 @@ population_data_age_district_b <- gen_population(total_pop = 10000, # set total
   rename(age_group  = groups,                      # rename columns (NEW NAME = OLD NAME)
          sex        = strata,
          population = n) %>% 
-  mutate(village_name = "Town B")           # add a column to identify region 
+  mutate(health_district = "Town B")           # add a column to identify region 
 
 
 
@@ -719,30 +736,23 @@ We can see that there are 17 clusters, from each town:
 
 ```{r}
 study_data_cleaned %>% 
-  tabyl(cluster_number, village_name)
+  tabyl(cluster_number, health_district)
 ```
 
-<!-- We can also see from the ordering in the table above, that cluster number is recognized as a character and not as a number, so we fix this with a quick `mutate()` command:   -->
-
-<!-- ```{r} -->
-<!-- study_data_cleaned <- study_data_cleaned %>%  -->
-<!--   mutate(cluster_number = as.integer(cluster_number)) -->
-<!-- ``` -->
-
 The fact that there are clusters 1-17 in each of the Towns will complicate later analyses. Each cluster should have a unique identification value. So, let us create one. We use the `str_glue()` function from {stringr} to combine the cluster number and the letter of the town. The letter of the town is extracted from the town name using `str_sub()`, which is also from the {stringr} package. The -1 extracts the last letter of the village name, and places it into the ID.  
 
 ```{r}
 study_data_cleaned <- study_data_cleaned %>% 
   mutate(cluster_number_uid = str_glue(
     "{town_letter}_{cluster_number}",
-    town_letter = str_sub(village_name, -1)))
+    town_letter = str_sub(health_district, -1)))
 ```
 
 We verify:
 
 ```{r}
 study_data_cleaned %>% 
-  tabyl(cluster_number_uid, village_name)
+  tabyl(cluster_number_uid, health_district)
 ```
 
 
@@ -880,24 +890,31 @@ study_data_cleaned <- study_data_cleaned %>%
 
 ### Create age groups
 
-In our survey data, the column `age_in_years` contain the age of the surveyed individual. Unfortunately, its values have been interpreted by R as class "character" (words), and not as numbers.  
+Information on age is spread across two columns: `age_years` and `age_months`.
 
-```{r}
-class(study_data_cleaned$age_in_years)
-```
 
-Before we can create age groups, we need to convert this column to class "integer".  
+Unfortunately, the values in these columns have been interpreted by R as class "character" (words), and not as numbers.  
 
-The R Markdown template expects the age columns to be named `age_years` and `age_months`, so for ease we will rename our columns to align with this expectation.  
+```{r}
+class(study_data_cleaned$age_years)
+class(study_data_cleaned$age_months)
+```
 
-Modify the first code in this chunk with two new lines, as shown below:    
+We can also review the dataset and see that if the age of respondents less than 1 year, the months are given in the `age_months` column but the `age_years` value is `NA` (missing). We will need the `age_years` column in this circumstance to have the value `0` for later calculations. So, we write and run the following command:  
 
 ```{r}
-## make sure age is an integer 
 study_data_cleaned <- study_data_cleaned %>% 
-  rename(age_years = age_in_years,       # rename age columns
-         age_months = age_in_months) %>%   
-  mutate(age_years = as.integer(age_years))
+  
+  # convert both columns to class integer
+  mutate(age_years = as.integer(age_years),
+         age_months = as.integer(age_months)) %>%
+  
+  # convert age_years to 0 if age_months is less than 12
+  mutate(age_years = case_when(
+    age_months < 12 ~ as.integer(0),    # if age is less than 12 months, put 0
+    TRUE            ~ age_years         # otherwise, leave as age_years value
+  ))
+
 ```
 
 
@@ -914,7 +931,9 @@ study_data_cleaned <- study_data_cleaned %>%
 ```
 
 
-The second command is very similar, but looks at the column `age_months` and checks whether the age in months is less than 12. If so, it applies the same `age_categories()` function but uses break points more relevant to the months values (e.g. 6 months, 9 months, and 12 months). If the value in `age_months` is greater than 12, it is replaced with missing.  
+
+
+The second command in the template is very similar to the first, but looks at the column `age_months` and checks whether the age in months is less than 12. If so, it applies the same `age_categories()` function but uses break points more relevant to the months values (e.g. 6 months, 9 months, and 12 months). If the value in `age_months` is greater than 12, it is replaced with missing.  
 
 
 ```{r}
@@ -962,7 +981,7 @@ For example, looking in the data dictionary (`study_data_dict`) we can see that
 
 A command like the below would revise all the raw option values to their display label version, across the entire dataset. The function `match_df()` accepts the name of our data frame, and the dictionary, the columns in the data dictionary to guide the value conversion (`from = ` and `to = `). Note that if provided in the data dictionary, you could also run the code with `to = "option_label_french"` to convert the values to French.  
 
-Again - it is NOT necessary to run this code for this vignette because the values are already in display format.  
+Again - it is **NOT** necessary to run this code for this vignette because the values are already in display format.  
 
 ```{r, eval=FALSE}
 ## recode values with matchmaker package (value labels cant be used for analysis) 
@@ -1113,18 +1132,24 @@ This chunk contains code to drop and examine rows for which there is no consent,
 In the second command, an `anti_join()` is used to actually drop the rows from `study_data_cleaned`. An anti join is a "filtering join" which looks in the `dropped` data frame and leaves only rows in `study_data_cleaned` which are *not* present in `dropped`. Its a fancy way of doing a filter, but allowing you the opportunity to inspect the rows first.  
 
 
-```{r, eval=FALSE}
+```{r}
 ## store the cases that you drop so you can describe them (e.g. non-consenting 
 ## or wrong village/cluster)
 dropped <- study_data_cleaned %>% 
   filter(!consent | is.na(startdate) | is.na(enddate) | 
            ## note that whatever you use for weights cannot be missing!
-           is.na(village_name) | is.na(age_years) | is.na(sex))
+           is.na(health_district) | is.na(age_years) | is.na(sex))
 
 ## use the dropped cases to remove the unused rows from the survey data set  
 study_data_cleaned <- anti_join(study_data_cleaned, dropped, by = names(dropped))
 ```
 
+We can see how many rows were dropped:  
+
+```{r}
+nrow(dropped)
+```
+
 
 ### Drop duplicates  
 
@@ -1149,9 +1174,6 @@ A second option available to you is commented out. This option allows you to ins
 
 These data come from a cluster survey, but because we have population counts for age and sex, we are able to make adjustments to better reflect the population, and therefore produce stratified estimates by age and sex. 
 
-At the end of the first command, we remove "health_district" because we only want to stratify by age and sex.  
-
-
 ```{r}
 
 ## create a variable called "surv_weight_strata" 
@@ -1160,7 +1182,7 @@ study_data_cleaned <- add_weights_strata(x = study_data_cleaned,
                                          p = population_data_age, 
                                          surv_weight = "surv_weight_strata",
                                          surv_weight_ID = "surv_weight_ID_strata",
-                                         age_group, sex, village_name)
+                                         age_group, sex, health_district)
 ```
 
 
@@ -1209,7 +1231,6 @@ study_data_cleaned <- study_data_cleaned %>%
 In the next chunk, we use only the "stratified cluster" code:  
 
 * We change `village_name` to `cluster_number_uid`, which is our unique cluster ID column.  
-* We change `health_district` to `village_name`, as this is our strata
 
 
 ```{r survey_design}
@@ -1243,7 +1264,7 @@ In the next chunk, we use only the "stratified cluster" code:
 survey_design <- study_data_cleaned %>% 
   as_survey_design(ids = cluster_number_uid, # cluster ids 
                    weights = surv_weight_cluster_strata, # weight variable created above 
-                   strata = village_name # sampling was stratified by district
+                   strata = health_district # sampling was stratified by district
                   )
 
 ```
@@ -1251,11 +1272,6 @@ survey_design <- study_data_cleaned %>%
 
 
 
-
-
-
-
-
 Run these to get the number of distinct
 Again, adapt `cluster_number` to `cluster_number_uid`.  
 
@@ -1513,15 +1529,13 @@ age_pyramid(study_data_cleaned,
 
 
 
-Replace `health_district` with `village_name`.  
-
 
 ```{r age_pyramid_strata, warning=FALSE}
 
 age_pyramid(study_data_cleaned, 
                  age_group, 
                  split_by = sex,
-                 stack_by = village_name,
+                 stack_by = health_district,
                  proportional = TRUE, 
                  pal = c("red", "blue")) + 
   labs(y = "Proportion", x = "Age group (years)") +    # change axis labels
@@ -1547,6 +1561,7 @@ age_pyramid(survey_design,
 
 
 ## Mortality
+
 ```{r CMR, warning = FALSE, message = FALSE}
 
 ## weighted counts and proportion of dead
@@ -1590,15 +1605,12 @@ design effect of `r #inline_text(death_props, variable = "died",  column = "add_
 This is a crude mortality rate of `r CMR` deaths per 10000 person-days. 
 
 
-
-Below, again, we replace `health_district` with `village_name`
-
 ```{r CMR_strata, warning = FALSE, message = FALSE}
 
 ## weighted counts and proportion of dead
 death_props_strat <- survey_design %>% 
-  select(died, village_name) %>%
-  tbl_svysummary(by = village_name) %>% 
+  select(died, health_district) %>%
+  tbl_svysummary(by = health_district) %>% 
   ## add the weighted total
   add_n() %>%   
   ## add in confidence intervals
@@ -1617,7 +1629,7 @@ death_props_strat <- survey_design %>%
 
 ## mortality per 10,000 persons/day with CI
 CMR_strat <- survey_design %>% 
-  group_by(village_name) %>% 
+  group_by(health_district) %>% 
   ## survey ratio used to account for observation time 
   summarize(mortality = survey_ratio(as.numeric(died) * 10000, obstime, vartype = "ci")) %>% 
   ## if negative CIs set to zero
@@ -1629,49 +1641,47 @@ CMR_strat <- survey_design %>%
 
 ```
 
-We also edit the in-line code (dynamic text) so that any reference to `health_district` changes to `village_name`, and "district_a" and "district_b" are changed to "Town A", and "Town B".  
 
 
-<!-- In District A the weighted number of deaths was  -->
-<!-- `r inline_text(death_props_strat, variable = "died",  column = "stat_1")`,  -->
-<!-- which gives a weighted proportion of  -->
-<!-- `r #death_props_strat %>% pull("Town A ci")`, and a design effect of -->
-<!-- `r #death_props_strat %>% pull("district_a deff") %>% round(digits = 3)`.   -->
-<!-- In comparison, the weighted number of deaths in District B was -->
-<!-- `r inline_text(death_props_strat, variable = "died",  column = "stat_2")`,  -->
-<!-- the weighted proportion was  -->
-<!-- `r #death_props_strat %>% pull("district_b ci")` and the design effect was  -->
-<!-- `r #death_props_strat %>% pull("district_b deff") %>% round(digits = 3)`.   -->
-<!-- The crude mortality rate in District A was  -->
-<!-- `r CMR_strat %>% filter(village_name == "Town A") %>% pull(Mortality)` -->
-<!-- deaths per 10000 person-days and in District B was  -->
-<!-- `r CMR_strat %>% filter(village_name == "Town B") %>% pull(Mortality)` -->
 
+In District A the weighted number of deaths was
+`r inline_text(death_props_strat, variable = "died",  column = "stat_1")`,
+which gives a weighted proportion of
+`r #death_props_strat %>% pull("Town A ci")`, and a design effect of
+`r #death_props_strat %>% pull("district_a deff") %>% round(digits = 3)`.
+In comparison, the weighted number of deaths in District B was
+`r inline_text(death_props_strat, variable = "died",  column = "stat_2")`,
+the weighted proportion was
+`r #death_props_strat %>% pull("district_b ci")` and the design effect was
+`r #death_props_strat %>% pull("district_b deff") %>% round(digits = 3)`.
+The crude mortality rate in District A was
+`r CMR_strat %>% filter(health_district == "Town A") %>% pull(Mortality)`
+deaths per 10000 person-days and in District B was
+`r CMR_strat %>% filter(health_district == "Town B") %>% pull(Mortality)`
 
 
 
 
-# we can wait on this for the study protocol 
 
-# msf_dict_rename_helper()
-# remove district for the stratified code,
-# keep both as FALSE
-# run all the analyses by age and sex
-# (regular cluster survey)
-# still weighting it like a stratefied cluster, but it probably is just cluster.
-# in survey design chunk, just use stratefied cluster bc survey_design is what's used elsewhere
+<!-- # msf_dict_rename_helper() -->
+<!-- # remove district for the stratified code, -->
+<!-- # keep both as FALSE -->
+<!-- # run all the analyses by age and sex -->
+<!-- # (regular cluster survey) -->
+<!-- # still weighting it like a stratefied cluster, but it probably is just cluster. -->
+<!-- # in survey design chunk, just use stratefied cluster bc survey_design is what's used elsewhere -->
 
 
-# counting per household how many people are in the house
-# cl = dataset with populaton per cluster
-# interviewed is how many people were interviewed in the hourse
-# clusterx = tell which variables correspond
-# the creating variables telling which are in each
-# Include both hoursehold and cluster
+<!-- # counting per household how many people are in the house -->
+<!-- # cl = dataset with populaton per cluster -->
+<!-- # interviewed is how many people were interviewed in the hourse -->
+<!-- # clusterx = tell which variables correspond -->
+<!-- # the creating variables telling which are in each -->
+<!-- # Include both hoursehold and cluster -->
 
 
-# Docker
-# build yourself a docker container and test locally
+<!-- # Docker -->
+<!-- # build yourself a docker container and test locally -->