epidatr 1.0.0

Author: dajmcdon

vignettes/epipredict.Rmd

@@ -2,7 +2,7 @@
 title: "Get started with epipredict"
 output: rmarkdown::html_vignette
 vignette: >
-  %\VignetteIndexEntry{epipredict}
+  %\VignetteIndexEntry{Get started with epipredict}
   %\VignetteEngine{knitr::rmarkdown}
   %\VignetteEncoding{UTF-8}
 ---

vignettes/preprocessing-and-models.Rmd

@@ -63,24 +63,22 @@ regression, the textbook example for modeling count data, as an illustration
 for using the `epipredict` package with other existing tidymodels packages. 
 
 ```{r poisson-reg-data}
-x <- covidcast(
+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(
+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")) %>%
@@ -244,24 +242,22 @@ in public in the past 7 days maintained a distance of at least 6 feet.
 State-wise population data from the 2019 U.S. Census is included in this package
 and will be used in `layer_population_scaling()`. 
 ```{r}
-behav_ind_mask <- covidcast(
+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(
+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)