In CBDRH/COVIDreconnoitR: Pulls and Analyses COVID data

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(covidrecon)
library(dplyr)
library(ggplot2)

covid <- covid_latest()
covid_highest <- covid_high_incidence(covid)
covid_changepoint <- add_covid_change_point(covid_highest)

highlight_countries <- c("Japan",
                         "South_Korea",
                         "Singapore",
                         "Italy",
                         "Iran",
                         "China",
                         "France",
                         "United_Kingdom",
                         "Sweden",
                         "Australia")

covid_highlighted <- covid_changepoint %>% 
  filter(country_region %in%  c(highlight_countries,
                                "United_States_of_America", 
                                "Germany", 
                                "Denmark"))

Incident Cases

gg_covid_cases(covid_highlighted) +
  facet_grid(country_region ~ ., 
             scales = "free_y") +
  geom_vline(aes(xintercept = change_point_date),
             colour = "salmon")

Cumulative Cases

gg_covid_cumulative_cases(covid_highlighted) +
  facet_grid(country_region ~ ., 
             scales = "free_y") +
  geom_vline(aes(xintercept = change_point_date),
                 colour = "salmon")

align countries along changepoint

covid_highlighted %>% 
  group_by(country_region) %>% 
  filter(date >= change_point_date) %>%
  mutate(days_since_change_point = diff_days(date, change_point_date)) %>% 
  ggplot(aes(x = days_since_change_point,
             y = cumulative_cases,
             colour = country_region)) +
    geom_line() +
    scale_y_log10()