diff --git a/DESCRIPTION b/DESCRIPTION
index 8b80431c..f149e29e 100755
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -53,7 +53,6 @@ Imports:
     vctrs,
     waldo
 Suggests:
-    covidcast,
     devtools,
     epidatr,
     knitr,
diff --git a/data-raw/jhu_csse_county_level_subset.R b/data-raw/jhu_csse_county_level_subset.R
index faed75e8..d64e3f4a 100644
--- a/data-raw/jhu_csse_county_level_subset.R
+++ b/data-raw/jhu_csse_county_level_subset.R
@@ -1,10 +1,8 @@
 library(epidatr)
-library(covidcast)
 library(epiprocess)
 library(dplyr)
 
-# Use covidcast::county_census to get the county and state names
-y <- covidcast::county_census %>%
+y <- read_csv("https://github.com/cmu-delphi/covidcast/raw/c89e4d295550ba1540d64d2cc991badf63ad04e5/Python-packages/covidcast-py/covidcast/geo_mappings/county_census.csv") %>%
   filter(STNAME %in% c("Massachusetts", "Vermont"), STNAME != CTYNAME) %>%
   select(geo_value = FIPS, county_name = CTYNAME, state_name = STNAME)
 
diff --git a/vignettes/aggregation.Rmd b/vignettes/aggregation.Rmd
index 9d205f53..a627a441 100644
--- a/vignettes/aggregation.Rmd
+++ b/vignettes/aggregation.Rmd
@@ -14,12 +14,11 @@ COVID-19 cases in MA and VT.
 
 ```{r, message = FALSE, eval= FALSE, warning= FALSE}
 library(epidatr)
-library(covidcast)
 library(epiprocess)
 library(dplyr)
 
 # Use covidcast::county_census to get the county and state names
-y <- covidcast::county_census %>%
+y <- y <- read_csv("https://github.com/cmu-delphi/covidcast/raw/c89e4d295550ba1540d64d2cc991badf63ad04e5/Python-packages/covidcast-py/covidcast/geo_mappings/county_census.csv") %>%
   filter(STNAME %in% c("Massachusetts", "Vermont"), STNAME != CTYNAME) %>%
   select(geo_value = FIPS, county_name = CTYNAME, state_name = STNAME)
 
@@ -41,7 +40,6 @@ The data contains 16,212 rows and 5 columns.
 
 ```{r, echo=FALSE, warning=FALSE, message=FALSE}
 library(epidatr)
-library(covidcast)
 library(epiprocess)
 library(dplyr)