Initial Quarto page created

_quarto.yml

@@ -206,6 +206,7 @@ book:
     - new_pages/reportfactory.qmd #done
     - new_pages/flexdashboard.qmd #done
     - new_pages/shiny_basics.qmd #done
+    - new_pages/quarto.qmd #done
 
   # MISCELLANEOUS
   - part: "Miscellaneous"

data/quarto/outbreak_dashboard.qmd

@@ -0,0 +1,90 @@
+---
+title: "Outbreak dashboard"
+output: 
+  flexdashboard::flex_dashboard:
+    orientation: columns
+    vertical_layout: fill
+---
+
+```{r setup, echo=FALSE}
+pacman::p_load(rio, here, tidyverse, flexdashboard,       # load packages
+               flextable, incidence2, epicontacts, DT, janitor)
+
+linelist <- import(here("data", "case_linelists", "linelist_cleaned.rds")) # import data
+```
+
+## Column 1 {data-width=500}
+### Summary and action items 
+
+This report is for the Incident Command team of the fictional outbreak of Ebola cases. **As of `r format(max(linelist$date_hospitalisation, na.rm=T), "%d %B")` there have been `r nrow(linelist)` cases reported as hospitalized.**  
+
+* Several previously-unaffected areas to the West are now reporting cases  
+* Internal reviews suggest that better communication is needed between district and provincial level data management teams  
+* Safe and dignified burial teams are reporting difficulties  
+
+### Review data
+#### Cases by hospital
+```{r}
+linelist %>%
+  count(hospital) %>%
+  adorn_totals() %>%
+  rename("Hospital" = hospital,
+         "Cases" = n) %>% 
+  knitr::kable()
+```
+
+
+## Column 2 {data-width=500}
+### Epidemic curve by age
+
+```{r}
+age_outbreak <- incidence(linelist, "date_onset", "week", groups = "age_cat")
+plot(age_outbreak, fill = "age_cat", col_pal = muted, title = "") %>% 
+  plotly::ggplotly()
+```
+
+### Transmission chain (select cases)
+```{r}
+# load package
+pacman::p_load(epicontacts)
+
+## generate contacts
+contacts <- linelist %>%
+  transmute(
+    infector = infector,
+    case_id = case_id,
+    location = sample(c("Community", "Nosocomial"), n(), TRUE),
+    duration = sample.int(10, n(), TRUE)
+  ) %>%
+  drop_na(infector)
+
+## generate epicontacts object
+epic <- make_epicontacts(
+  linelist = linelist,
+  contacts = contacts,
+  id = "case_id",
+  from = "infector",
+  to = "case_id",
+  directed = TRUE
+)
+
+## subset epicontacts object
+sub <- epic %>%
+  subset(
+    node_attribute = list(date_onset = c(as.Date(c("2014-06-30", "2014-06-01"))))
+  ) %>%
+ thin("contacts")
+
+# temporal plot
+plot(
+  sub,
+  x_axis = "date_onset",
+  node_color = "outcome",
+  col_pal = c(Death = "firebrick", Recover = "green"),
+  arrow_size = 0.5,
+  node_size = 13,
+  label = FALSE,
+  height = 700,
+  width = 700
+)
+```

data/quarto/outbreak_report.qmd

@@ -0,0 +1,40 @@
+---
+title: "Outbreak Situation Report"
+date: "4/24/2021"
+output: pdf_document
+---
+
+```{r setup, echo=FALSE, warning =FALSE, message=F}
+pacman::p_load(rio, here, tidyverse, janitor, incidence2, flextable)
+linelist <- rio::import(here::here("data", "case_linelists", "linelist_cleaned.rds"))
+set_flextable_defaults(fonts_ignore=TRUE)
+```
+
+This report is for the Incident Command team of the fictional outbreak of Ebola cases. **As of `r format(max(linelist$date_hospitalisation, na.rm=T), "%d %B")` there have been `r nrow(linelist)` cases reported as hospitalized.**  
+
+## Summary table of cases by hospital 
+
+```{r, echo=F, out.height="75%"}
+linelist %>% 
+  filter(!is.na(hospital)) %>% 
+  group_by(hospital) %>% 
+  summarise(cases = n(),
+    deaths = sum(outcome == "Death", na.rm=T),
+    recovered = sum(outcome == "Recover", na.rm=T)) %>% 
+  adorn_totals() %>% 
+  qflextable()
+```
+
+## Epidemic curve by age  
+
+```{r, echo=F, warning=F, message=F, out.height = "50%", out.width="75%"}
+# create epicurve
+age_outbreak <- incidence(
+  linelist,
+  date_index = "date_onset",   # date of onset for x-axis
+  interval = "week",         # weekly aggregation of cases
+  groups = "age_cat")
+     
+# plot
+plot(age_outbreak, n_breaks = 3, fill = "age_cat", col_pal = muted, title = "Epidemic curve by age group")
+```