diff --git a/DESCRIPTION b/DESCRIPTION
index 0fdef78..def2039 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -6,7 +6,7 @@ Authors@R:
     person(c("Daniel", "J."), "McDonald", , "daniel@stat.ubc.ca", role = c("cre", "aut"))
 Description: This package contains data sets used to compile vignettes and
     other documentation in Delphi R Packages. The goal is to avoid calls
-    to the Delphi Epidata API, and deposit some examples here for easy
+    to the Delphi Epidata API, and to deposit some examples here for easy
     offline use.
 License: MIT + file LICENSE
 Depends:
@@ -15,15 +15,16 @@ Suggests:
     covidcast,
     dplyr,
     epidatr,
-    epipredict,
+    epiprocess,
     here,
+    httr,
+    jsonlite,
     lubridate,
     magrittr,
     purrr,
     readr
 Remotes:
     cmu-delphi/epidatr,
-    cmu-delphi/epipredict,
     cmu-delphi/epiprocess
 Encoding: UTF-8
 LazyData: true
diff --git a/R/epipredict-data.R b/R/epipredict-data.R
index 9d78952..0663fb1 100644
--- a/R/epipredict-data.R
+++ b/R/epipredict-data.R
@@ -80,3 +80,26 @@
 #' by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering.
 #' Copyright Johns Hopkins University 2020.
 "counts_subset"
+
+#' Canadian COVID-19 case rates
+#'
+#' Data set for all Canadian provinces and territories containing COVID-19
+#' case rates (COVID-19 cases per 100,000 people) derived from COVID-19 case
+#' counts as reported by the
+#' \href{https://opencovid.ca/}{COVID-19 Canada Open Data Working Group (CCODWG)}.
+#' Data is available both through the archived
+#' \href{https://github.com/ccodwg/Covid19Canada}{ccodwg/Covid19Canada GitHub repository}
+#' and the newer
+#' \href{https://github.com/ccodwg/CovidTimelineCanada}{ccodwg/CovidTimelineCanada GitHub repository},
+#' which also reports vaccine-related signals.
+#'
+#' This dataset contains versioned data covering the period from April 2020 to
+#' December 2021 and is used in the [epipredict] slide vignette.
+#'
+#' @source This object contains a modified part of the COVID-19 Canada Open
+#' Data Working Group's
+#' \href{https://github.com/ccodwg/Covid19Canada}{Covid19Canada data repository} (archived).
+#' This data set is licensed under the terms of the
+#' \href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license}
+#' by the COVID-19 Canada Open Data Working Group.
+"can_prov_cases"
diff --git a/data-raw/archive_cases_dv_subset.R b/data-raw/archive_cases_dv_subset_dt.R
similarity index 88%
rename from data-raw/archive_cases_dv_subset.R
rename to data-raw/archive_cases_dv_subset_dt.R
index 3aefd93..6f505c1 100644
--- a/data-raw/archive_cases_dv_subset.R
+++ b/data-raw/archive_cases_dv_subset_dt.R
@@ -1,5 +1,9 @@
-dv_subset <- covidcast(
-  data_source = "doctor-visits",
+library(dplyr)
+library(epidatr)
+library(epiprocess)
+
+dv_subset <- pub_covidcast(
+  source = "doctor-visits",
   signals = "smoothed_adj_cli",
   time_type = "day",
   geo_type = "state",
@@ -7,14 +11,13 @@ dv_subset <- covidcast(
   geo_values = "ca,fl,ny,tx",
   issues = epirange(20200601, 20211201)
 ) %>%
-  fetch() %>%
   select(geo_value, time_value, version = issue, percent_cli = value) %>%
   # We're using compactify=FALSE here and below to avoid some testthat test
   # failures on tests that were based on a non-compactified version.
   as_epi_archive(compactify = FALSE)
 
-case_rate_subset <- covidcast(
-  data_source = "jhu-csse",
+case_rate_subset <- pub_covidcast(
+  source = "jhu-csse",
   signals = "confirmed_7dav_incidence_prop",
   time_type = "day",
   geo_type = "state",
@@ -22,7 +25,6 @@ case_rate_subset <- covidcast(
   geo_values = "ca,fl,ny,tx",
   issues = epirange(20200601, 20211201)
 ) %>%
-  fetch() %>%
   select(geo_value, time_value, version = issue, case_rate_7d_av = value) %>%
   as_epi_archive(compactify = FALSE)
 
diff --git a/data-raw/can_prov_cases.R b/data-raw/can_prov_cases.R
new file mode 100644
index 0000000..5dce2cf
--- /dev/null
+++ b/data-raw/can_prov_cases.R
@@ -0,0 +1,148 @@
+## code to prepare `can_prov_cases` dataset goes here
+
+library(dplyr)
+library(epiprocess)
+library(readr)
+library(purrr)
+library(httr)
+library(jsonlite)
+
+
+# Look for a GitHub API token.
+# Returns an empty string "" if env variable not found.
+gh_token <- Sys.getenv("GITHUB_PAT")
+if (gh_token == "") {
+  # Try again with the secondary name.
+  gh_token <- Sys.getenv("GITHUB_TOKEN")
+}
+if (gh_token == "") {
+  warning("Token is not set or is not able to be fetched from the environment.",
+          " Proceeding without authentication, but the requests may be blocked", 
+          " due to GitHub API rate limits.")
+}
+
+# Construct a header to send with GET requests
+if (gh_token == "") {
+  # Empty header
+  auth_header <- httr::add_headers()
+} else {
+  auth_header <- httr::add_headers(Authorization = paste("Bearer", gh_token))
+}
+
+## Get list of new and modified files to download
+# The `path` field filters commits to only those that modifying the listed dir
+# From https://www.github.com/ccodwg/Covid19Canada
+BASE_URL <- "https://api.github.com/repos/ccodwg/Covid19Canada/commits?sha=%s&per_page=%s&path=timeseries_prov/cases_timeseries_prov.csv&until=%s&page=%s"
+ITEMS_PER_PAGE <- 100
+BRANCH <- "master"
+
+
+
+# We want to fetch all commits made since Mar 13 2022 (version the original
+# dataset was created from).
+#
+# Timestamp should be in ISO 8601 format. See
+# https://docs.github.com/en/rest/reference/commits#list-commits--parameters for
+# details.
+since_date <- strftime("2022-03-13", "%Y-%m-%dT%H:%M:%SZ", tz = "UTC")
+
+page <- 0
+commit_pages <- list()
+
+# Fetch list of commits from API, one page at a time. Each page contains up to
+# 100 commits. If a page contains 100 commits, assume that there are more
+# results and fetch the next page.
+while (page == 0 || nrow(commit_page) == 100) {
+  page <- page + 1
+  # Construct the URL
+  commits_url <- sprintf(BASE_URL, BRANCH, ITEMS_PER_PAGE, since_date, page)
+  
+  request <- GET(commits_url, auth_header)
+  # Convert any HTTP errors to R errors automatically.
+  stop_for_status(request)
+  
+  # Convert results from nested JSON/list to dataframe. If no results returned,
+  # `commit_page` will be an empty list.
+  commit_page <- content(request, as = "text") %>%
+    fromJSON(simplifyDataFrame = TRUE, flatten = TRUE) %>% 
+    # Trim message down a bit.
+    mutate(message = substr(commit.message, 1, 40)) %>% 
+    select(sha, url = commit.url, message)
+  
+  # No more results are being returned.
+  if (identical(commit_page, list())) {
+    break
+  }
+  
+  commit_pages[[page]] <- commit_page
+}
+
+# Combine all requested pages of commits into one dataframe
+commit_pages <- bind_rows(commit_pages)
+
+# Missing value `%s` to be filled in with a commit sha or branch name.
+BASE_DATA_URL <- "https://raw.githubusercontent.com/ccodwg/Covid19Canada/%s/timeseries_prov/cases_timeseries_prov.csv"
+
+fc_time_values <- seq(as.Date("2021-02-01"), as.Date("2021-12-01"),
+                      by = "1 month")
+commit_pages <- mutate(
+  commit_pages,
+  data_url = sprintf(BASE_DATA_URL, sha),
+  date = strsplit(message, " ") %>% map_chr(~ substr(.x[3], start=1, stop=10)) %>% as.Date()
+) %>% 
+  # select(data_url, date) %>% 
+  na.omit() %>% 
+  filter(date %in% fc_time_values)
+
+# From https://github.com/mountainMath/BCCovidSnippets/blob/main/data/prov_pop.csv
+ca_pop_url <- "https://raw.githubusercontent.com/mountainMath/BCCovidSnippets/main/data/prov_pop.csv"
+ca_pop <- read_csv(
+  ca_pop_url,
+  col_types = cols(
+    Province = col_character(),
+    shortProvince = col_character(),
+    Population = col_integer()
+  )
+) %>% 
+  rename(province = Province, abbreviation = shortProvince, population = Population)
+abbrev_map <- setNames(ca_pop$province, ca_pop$abbreviation)
+
+# Read in data and convert to `epi_df`s.
+can_prov_cases <- purrr::map2(commit_pages$data_url, commit_pages$date, function(url, date) {
+  raw <- readr::read_csv(
+    url,
+    col_types = cols(
+      province = col_character(),
+      date_report = col_character(),
+      cases = col_double(),
+      cumulative_cases = col_double()
+    )
+  )
+  
+  # Raw data uses a mix of full names and abbreviations. Switch to using only full names.
+  raw$province <- case_when(
+    raw$province == "NWT" ~ abbrev_map["NT"],
+    raw$province == "PEI" ~ abbrev_map["PE"],
+    raw$province %in% ca_pop$province ~ raw$province,
+    raw$province %in% ca_pop$abbreviation ~ abbrev_map[raw$province],
+    # Mark everything else as missing. Only applies to "Repatriated" region.
+    TRUE ~ NA
+  )
+  
+  result <- raw %>% 
+    mutate(time_value = lubridate::dmy(date_report)) %>%
+    left_join(ca_pop, by="province") %>%
+    filter(!is.na(province), time_value > "2020-04-01") %>%
+    mutate(geo_value = province,
+           case_rate = cases / population * 1e5) %>%
+    select(geo_value, time_value, case_rate) %>%
+    as_epi_df(geo_type = "province", as_of = date)
+  
+  return(result)
+})
+names(can_prov_cases) <- commit_pages$date
+can_prov_cases <- can_prov_cases %>% bind_rows(.id = "version") %>%
+  mutate(version = lubridate::ymd(version)) %>% 
+  arrange(version)
+
+usethis::use_data(can_prov_cases, overwrite = TRUE)
diff --git a/data-raw/cancovid.R b/data-raw/cancovid.R
deleted file mode 100644
index 8fe5a8a..0000000
--- a/data-raw/cancovid.R
+++ /dev/null
@@ -1,25 +0,0 @@
-## code to prepare `cancovid` dataset goes here
-
-path_to_csvs <- here::here("../../COVID-BC/Covid19Canada/updates.nosync/")
-files <- list.files(path_to_csvs)
-ca_as_ofs <- as.Date(substr(files, 1, 10)) %>%
-  intersect(fc_time_values) %>%
-  as.Date(origin = "1970-01-01")
-
-can <- purrr::map(ca_as_ofs, ~ {
-  readr::read_csv(here::here(path_to_csvs, paste0(.x, ".csv"))) %>%
-    left_join(ca_pop) %>%
-    mutate(time_value = lubridate::dmy(date_report)) %>%
-    filter(province %in% ca_pop$province, time_value > "2020-04-01") %>%
-    mutate(geo_value = province,
-           case_rate = cases / population * 1e5) %>%
-    select(geo_value, time_value, case_rate) %>%
-    as_epi_df(geo_type = "province", as_of = .x)
-})
-names(can) <- ca_as_ofs
-can <- can %>% bind_rows(.id = "version") %>%
-  mutate(version = lubridate::ymd(version))
-saveRDS(can, "inst/extdata/can_prov_cases.rds")
-
-
-usethis::use_data(cancovid, overwrite = TRUE)
diff --git a/data-raw/cases_deaths_subset.R b/data-raw/cases_deaths_subset.R
index 06e2259..184a5c3 100644
--- a/data-raw/cases_deaths_subset.R
+++ b/data-raw/cases_deaths_subset.R
@@ -1,48 +1,48 @@
-confirmed_7dav_incidence_prop <- covidcast(
-  data_source = "jhu-csse",
+library(dplyr)
+library(epidatr)
+library(epiprocess)
+
+confirmed_7dav_incidence_prop <- pub_covidcast(
+  source = "jhu-csse",
   signals = "confirmed_7dav_incidence_prop",
   time_type = "day",
   geo_type = "state",
   time_values = epirange(20200301, 20211231),
   geo_values = "ca,fl,ny,tx,ga,pa"
 ) %>%
-  fetch() %>%
   select(geo_value, time_value, case_rate_7d_av = value) %>%
   arrange(geo_value, time_value)
 
-deaths_7dav_incidence_prop <- covidcast(
-  data_source = "jhu-csse",
+deaths_7dav_incidence_prop <- pub_covidcast(
+  source = "jhu-csse",
   signals = "deaths_7dav_incidence_prop",
   time_type = "day",
   geo_type = "state",
   time_values = epirange(20200301, 20211231),
   geo_values = "ca,fl,ny,tx,ga,pa"
 ) %>%
-  fetch() %>%
   select(geo_value, time_value, death_rate_7d_av = value) %>%
   arrange(geo_value, time_value)
 
-confirmed_incidence_num <- covidcast(
-  data_source = "jhu-csse",
+confirmed_incidence_num <- pub_covidcast(
+  source = "jhu-csse",
   signals = "confirmed_incidence_num",
   time_type = "day",
   geo_type = "state",
   time_values = epirange(20200301, 20211231),
   geo_values = "ca,fl,ny,tx,ga,pa"
 ) %>%
-  fetch() %>%
   select(geo_value, time_value, cases = value) %>%
   arrange(geo_value, time_value)
 
-confirmed_7dav_incidence_num <- covidcast(
-  data_source = "jhu-csse",
+confirmed_7dav_incidence_num <- pub_covidcast(
+  source = "jhu-csse",
   signals = "confirmed_7dav_incidence_num",
   time_type = "day",
   geo_type = "state",
   time_values = epirange(20200301, 20211231),
   geo_values = "ca,fl,ny,tx,ga,pa"
 ) %>%
-  fetch() %>%
   select(geo_value, time_value, cases_7d_av = value) %>%
   arrange(geo_value, time_value)
 
diff --git a/data-raw/counts_subset.R b/data-raw/counts_subset.R
index 83d5461..7cf9bc1 100644
--- a/data-raw/counts_subset.R
+++ b/data-raw/counts_subset.R
@@ -1,23 +1,25 @@
 ## code to prepare jhu_incidence_num dataset goes here
 
-x <- covidcast(
-  data_source = "jhu-csse",
+library(dplyr)
+library(epidatr)
+library(epiprocess)
+
+x <- pub_covidcast(
+  source = "jhu-csse",
   signals = "confirmed_incidence_num",
   time_type = "day",
   geo_type = "state",
   time_values = epirange(20210604, 20211231),
   geo_values = "ca,fl,tx,ny,nj") %>%
-  fetch() %>%
   select(geo_value, time_value, cases = value)
 
-y <- covidcast(
-  data_source = "jhu-csse",
+y <- pub_covidcast(
+  source = "jhu-csse",
   signals = "deaths_incidence_num",
   time_type = "day",
   geo_type = "state",
   time_values = epirange(20210604, 20211231),
   geo_values = "ca,fl,tx,ny,nj") %>%
-  fetch() %>%
   select(geo_value, time_value, deaths = value)
 
 counts_subset <- full_join(x, y, by = c("geo_value", "time_value")) %>%
diff --git a/data-raw/covid_case_death_rates.R b/data-raw/covid_case_death_rates.R
index 1f9af3d..ceab111 100644
--- a/data-raw/covid_case_death_rates.R
+++ b/data-raw/covid_case_death_rates.R
@@ -1,27 +1,29 @@
-x <- covidcast(
-  data_source = "jhu-csse",
+library(dplyr)
+library(epidatr)
+library(epiprocess)
+
+x <- pub_covidcast(
+  source = "jhu-csse",
   signals = "confirmed_7dav_incidence_prop",
   time_type = "day",
   geo_type = "state",
   time_values = epirange(20200301, 20211231),
   geo_values = "*"
 ) %>%
-  fetch() %>%
   select(geo_value, time_value, case_rate = value)
 
-y <- covidcast(
-  data_source = "jhu-csse",
+y <- pub_covidcast(
+  source = "jhu-csse",
   signals = "deaths_7dav_incidence_prop",
   time_type = "day",
   geo_type = "state",
   time_values = epirange(20200301, 20211231),
   geo_values = "*"
 ) %>%
-  fetch() %>%
   select(geo_value, time_value, death_rate = value)
 
-case_death_rate_subset <- x %>%
+covid_case_death_rates <- x %>%
   full_join(y, by = c("geo_value", "time_value")) %>%
   as_epi_df()
 
-usethis::use_data(case_death_rate_subset, overwrite = TRUE)
+usethis::use_data(covid_case_death_rates, overwrite = TRUE)
diff --git a/data-raw/covid_incidence_county_subset.R b/data-raw/covid_incidence_county_subset.R
index 35dce13..cc94485 100644
--- a/data-raw/covid_incidence_county_subset.R
+++ b/data-raw/covid_incidence_county_subset.R
@@ -1,18 +1,22 @@
 # Use covidcast::county_census to get the county and state names
+library(dplyr)
+library(covidcast)
+library(epidatr)
+library(epiprocess)
+
 y <- covidcast::county_census %>%
   filter(STNAME %in% c("Massachusetts", "Vermont"), STNAME != CTYNAME) %>%
   select(geo_value = FIPS, county_name = CTYNAME, state_name = STNAME)
 
 # Fetch only counties from Massachusetts and Vermont, then append names columns as well
-covid_incidence_county_subset <- covidcast(
-  data_source = "jhu-csse",
+covid_incidence_county_subset <- pub_covidcast(
+  source = "jhu-csse",
   signals = "confirmed_incidence_num",
   time_type = "day",
   geo_type = "county",
   time_values = epirange(20200601, 20211231),
   geo_values = paste(y$geo_value, collapse = ",")
 ) %>%
-  fetch() %>%
   select(geo_value, time_value, cases = value) %>%
   full_join(y, by = "geo_value") %>%
   as_epi_df()
diff --git a/data-raw/covid_incidence_outliers.R b/data-raw/covid_incidence_outliers.R
index 3903fe6..a81bf8a 100644
--- a/data-raw/covid_incidence_outliers.R
+++ b/data-raw/covid_incidence_outliers.R
@@ -1,5 +1,9 @@
-incidence_num_outlier_example <- covidcast(
-  data_source = "jhu-csse",
+library(dplyr)
+library(epidatr)
+library(epiprocess)
+
+covid_incidence_outliers <- pub_covidcast(
+  source = "jhu-csse",
   signals = "confirmed_incidence_num",
   time_type = "day",
   geo_type = "state",
@@ -7,7 +11,6 @@ incidence_num_outlier_example <- covidcast(
   geo_values = "fl,nj",
   as_of = 20211028
 ) %>%
-  fetch() %>%
   select(geo_value, time_value, cases = value) %>%
   as_epi_df()
 
diff --git a/data-raw/ctis_covid_behaviours.R b/data-raw/ctis_covid_behaviours.R
index 6ce2e65..e0336de 100644
--- a/data-raw/ctis_covid_behaviours.R
+++ b/data-raw/ctis_covid_behaviours.R
@@ -1,27 +1,26 @@
 ## code to prepare `ctis_covid_behaviours` dataset goes here
 
-behav_ind_mask <- covidcast(
-  data_source = "fb-survey",
+library(dplyr)
+library(epidatr)
+
+behav_ind_mask <- pub_covidcast(
+  source = "fb-survey",
   signals = "smoothed_wwearing_mask_7d",
   time_type = "day",
   geo_type = "state",
   time_values = epirange(20210604, 20211231),
   geo_values = "ca,fl,tx,ny,nj")  %>%
-  fetch() %>%
   select(geo_value, time_value, masking = value)
 
-behav_ind_distancing <- covidcast(
-  data_source = "fb-survey",
+behav_ind_distancing <- pub_covidcast(
+  source = "fb-survey",
   signals = "smoothed_wothers_distanced_public",
   time_type = "day",
   geo_type = "state",
   time_values = epirange(20210604, 20211231),
   geo_values = "ca,fl,tx,ny,nj")  %>%
-  fetch() %>%
   select(geo_value, time_value, distancing = value)
 
-pop_dat <- state_census %>% select(abbr, pop)
-
 ctis_covid_behaviours <- behav_ind_mask %>%
   full_join(behav_ind_distancing, by = c("geo_value", "time_value"))
 
diff --git a/data-raw/jhu_confirmed_cumulative_num.R b/data-raw/jhu_confirmed_cumulative_num.R
index 16b16bf..2610d69 100644
--- a/data-raw/jhu_confirmed_cumulative_num.R
+++ b/data-raw/jhu_confirmed_cumulative_num.R
@@ -1,13 +1,13 @@
-## code to prepare `jhu_confirmed_cumulative_num` dataset goes here
+library(dplyr)
+library(epidatr)
 
-jhu_confirmed_cumulative_num <- covidcast(
-  data_source = "jhu-csse",
+jhu_confirmed_cumulative_num <- pub_covidcast(
+  source = "jhu-csse",
   signals = "confirmed_cumulative_num",
   time_type = "day",
   geo_type = "state",
   time_values = epirange(20200301, 20220131),
   geo_values = "ca,fl,ny,tx"
-) %>% fetch()
-
+)
 
 usethis::use_data(jhu_confirmed_cumulative_num, overwrite = TRUE)
diff --git a/data-raw/state_census.R b/data-raw/state_census.R
index 54f6a8f..c5ecb75 100644
--- a/data-raw/state_census.R
+++ b/data-raw/state_census.R
@@ -1,8 +1,10 @@
+library(dplyr)
+library(covidcast)
+
 state_census <- covidcast::state_census %>%
   select(STATE, NAME, POPESTIMATE2019, ABBR) %>%
   rename(abbr = ABBR, name = NAME, pop = POPESTIMATE2019, fips = STATE) %>%
   mutate(abbr = tolower(abbr)) %>%
   as_tibble()
 
-
 usethis::use_data(state_census, overwrite = TRUE)
diff --git a/data/can_prov_cases.rda b/data/can_prov_cases.rda
new file mode 100644
index 0000000..40aa917
Binary files /dev/null and b/data/can_prov_cases.rda differ
diff --git a/man/can_prov_cases.Rd b/man/can_prov_cases.Rd
new file mode 100644
index 0000000..c3e5cd7
--- /dev/null
+++ b/man/can_prov_cases.Rd
@@ -0,0 +1,36 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/epipredict-data.R
+\docType{data}
+\name{can_prov_cases}
+\alias{can_prov_cases}
+\title{Canadian COVID-19 case rates}
+\format{
+An object of class \code{epi_df} (inherits from \code{tbl_df}, \code{tbl}, \code{data.frame}) with 65299 rows and 4 columns.
+}
+\source{
+This object contains a modified part of the COVID-19 Canada Open
+Data Working Group's
+\href{https://github.com/ccodwg/Covid19Canada}{Covid19Canada data repository} (archived).
+This data set is licensed under the terms of the
+\href{https://creativecommons.org/licenses/by/4.0/}{Creative Commons Attribution 4.0 International license}
+by the COVID-19 Canada Open Data Working Group.
+}
+\usage{
+can_prov_cases
+}
+\description{
+Data set for all Canadian provinces and territories containing COVID-19
+case rates (COVID-19 cases per 100,000 people) derived from COVID-19 case
+counts as reported by the
+\href{https://opencovid.ca/}{COVID-19 Canada Open Data Working Group (CCODWG)}.
+Data is available both through the archived
+\href{https://github.com/ccodwg/Covid19Canada}{ccodwg/Covid19Canada GitHub repository}
+and the newer
+\href{https://github.com/ccodwg/CovidTimelineCanada}{ccodwg/CovidTimelineCanada GitHub repository},
+which also reports vaccine-related signals.
+}
+\details{
+This dataset contains versioned data covering the period from April 2020 to
+December 2021 and is used in the [epipredict] slide vignette.
+}
+\keyword{datasets}