Laged US CFR

library(tidyverse)
library(rgeos)
library(RcppRoll)
library(rworldmap)

data <- read_csv("https://covid.ourworldindata.org/data/owid-covid-data.csv") %>% 
  filter(location != "World")

plot_df <- data %>% 
  group_by(iso_code) %>% 
  arrange(date) %>% 
  mutate(rolling_deaths = roll_sum(new_deaths, 7, align = "right", fill = NA),
         rolling_cases = roll_sum(new_cases, 7, align = "right", fill = NA),
         lagged_rolling_cfr = rolling_deaths / lag(rolling_cases, 14)) %>%
  filter(date > lubridate::mdy("03-01-2020"))
  
plot_df %>% 
  filter(iso_code %in% c("USA")) %>% 
  filter(date > lubridate::ymd("2020-04-01")) %>% 
  filter(lagged_rolling_cfr < 1) %>% 
  ggplot(aes(x = date, y = lagged_rolling_cfr, facets = location, 
             colour = rolling_deaths)) +
  geom_point() +
  theme_light() +
  scale_y_continuous(labels = scales::percent) +
  scale_color_viridis_c() +
  labs(title = "USA Covid Death Rate",
       subtitle = "Deaths divided by cases 14 days prior",
       colour = "Deaths previous 7 days") +
  xlab("Date") +
  ylab("14 day lagged CFR")