cdc_vaccine_data.Rmd

---
title: "CDC vaccine data - NICAR22"
output: html_notebook
---


```{r}
library(tidyverse)
library(janitor)
library(MMWRweek)
library(RSocrata)

```


```{r}
#data source: https://data.cdc.gov/Vaccinations/COVID-19-Vaccinations-in-the-United-States-Jurisdi/unsk-b7fc

# Set up required before you can run this
# First sign up for CDC Socrata account here: https://data.cdc.gov/signup. 
#Then follow these directions to get an app token: https://dev.socrata.com/docs/app-tokens.html

#Install the token, your email and the password into REnviron as follows.
# this assumes you have the usethis package installed (which was needed for tidycensus)
#if it's not yet installed, uncomment the next line of code and run it:
# install.packages("usethis")


# In the Console area type:   usethis::edit_r_environ()

# replace the x's below with the appropriate information and then paste that (without the comment hashtag) into REnviron file
#cdc_token="xxx"
#cdc_pw = "xxx"
#cdc_email ="xxx"

# Close RStudio and restart




```

```{r}
#this code should work just fine as long as you set your Renviron variables to match as shows here (i.e. "cdc_token" in all lowercase)

vax_download <- read.socrata(
  "https://data.cdc.gov/resource/unsk-b7fc.json",
  app_token = Sys.getenv("cdc_token"),
  email     = Sys.getenv("cdc_email"),
  password  = Sys.getenv("cdc_pw")
) 
```


```{r}

# Notice all the data comes down as character except the date field
str(vax_download)
```


```{r}

# here's how to fix the formatting problems after the data comes in

vax <-  vax_download %>% 
  mutate_at(vars(4:80), as.numeric) %>%   # this converts columns 4 through 80 to numeric
  mutate(date = as.Date(date), mmwr_week=as.numeric(mmwr_week)) # this converts the date field and the mmwr_week field accordingly



```



# Apply MMWR year

```{r}
# The CDC does all it's weekly reporting based on MMWR weeks
#The first day of any MMWR week is Sunday. MMWR week numbering is sequential beginning with 1 and
#incrementing with each week to a maximum of 52 or 53. MMWR week #1 of an MMWR year is the first week of
#the year that has at least four days in the calendar year. For example, if January 1 occurs on a Sunday, Monday,
#Tuesday or Wednesday, the calendar week that includes January 1 would be MMWR week #1. If January 1
#occurs on a Thursday, Friday, or Saturday, the calendar week that includes January 1 would be the last MMWR
#week of the previous year (#52 or #53). Because of this rule, December 29, 30, and 31 could potentially fall into
#MMWR week #1 of the following MMWR year. 

#this uses the MMWRweek package to assign the month, week and day from each date
# the MMWRweek package creates a whole new dataframe first


#generate MMWR year, week, day variables
mmwrdates_vax <- MMWRweek(vax$date)

#join the year, week, day variables to the vax data
#NOTE: the CDC data has a field called "mmwr_week" (note the R is in the first part) and this just
#added the week, day and year. The new week is "mmw_rweek" 
vax <- cbind(vax, mmwrdates_vax) %>% clean_names() 


#this creates a lookup table with the start and end dates of each MMWR week so you can add them back to the data (next step)
week_start_end <-  vax %>%
  group_by(mmw_ryear, mmw_rweek) %>%
  summarise(start_date = min(date),
            end_date = max(date),
            .groups='drop')



# apply the start_date and end_date to vax table by  joining
 vax <-  left_join(vax, week_start_end %>% select(mmw_ryear, mmw_rweek, start_date, end_date), by=c("mmw_ryear"="mmw_ryear", "mmw_rweek"="mmw_rweek" ))
 

```