google vs. rt

google_mob.r

library("tidyverse")
library("ggplot2")
library("cowplot")

## get mobility data
dm <- read_csv("https://www.gstatic.com/covid19/mobility/Global_Mobility_Report.csv") %>%
  mutate(date = as.Date(date, format = "%d/%m/%Y")) %>%
  filter(is.na(sub_region_1)) %>%
  rename(country = country_region) %>%
  gather(type, value, 6:ncol(.)) %>%
  mutate(type = sub("_percent.*$", "", type),
         type = stringi::stri_trans_totitle(gsub("_", " ", type)))

## get reproduction numers
rt <- read_csv("https://raw.githubusercontent.com/epiforecasts/covid-global/37c8b2a94618681c280f55f581b4e83663ca130c/national-summary/rt.csv") %>%
  left_join(dm, by = c("country", "date"))

ggplot(rt, aes(x = median, y = value, colour = type, fill = type)) +
  geom_jitter(alpha=0.1) +
  geom_smooth() +
  xlab("R") + ylab("Mobility") +
  cowplot::theme_cowplot() +
  coord_cartesian(ylim = c(-100, 100)) +
  expand_limits(x = 0) +
  scale_color_brewer("", palette = "Dark2") +
  scale_fill_brewer("", palette = "Dark2") +
  theme(legend.position = "bottom")