code for NZ vs UK to show similarity in early progression

NZvsUK.R

library(dplyr)
library(lubridate)
library(ggplot2)

EUcdc <- read.csv("https://opendata.ecdc.europa.eu/covid19/casedistribution/csv",
                  stringsAsFactors = FALSE, fileEncoding = "UTF-8-BOM")
# NZ level 4 lockdown 26 March
#Boris Handshakes 3 March,
EUcdc %>%
  filter(countriesAndTerritories %in% c("United_Kingdom", "New_Zealand")) %>%
  mutate(ReportDate = dmy(dateRep)) %>%
  arrange(countriesAndTerritories, ReportDate) %>%
  group_by(countriesAndTerritories) %>%
  mutate(total_cases = cumsum(cases)) %>%
  filter(total_cases > 19)  %>%
  mutate(days = as.integer(difftime(ReportDate, min(ReportDate), units="day"))) %>% 
  slice(1:21) %>%
  ungroup() %>%
  select(countriesAndTerritories, days, ReportDate, total_cases) %>%
  ggplot(aes(x=days, y=total_cases, colour=countriesAndTerritories)) +
  geom_line() + theme_minimal() +
  scale_colour_manual(name="Country", values=c("#377eb8","#ff7f00")) +
  annotate("segment", x=2, xend=2, y=40, yend=4000,
           colour="#ff7f00", linetype=2) +
  annotate("segment", x=8, xend=8, y=262, yend=4000,
           colour="#377eb8", linetype=2) +
  annotate("text", x=2.9, y=4000, angle=90, colour="#ff7f00", hjust=1,
           label="Boris shaking hands with covid-19 patients") +
  annotate("text", x=8.9, y=4000, angle=90, colour="#377eb8", hjust=1,
           label="New Zealand goes to level 4 lockdown") +
  xlab("Days since 20th case") + ylab("Total confirmed cases")+
  labs(title="Covid-19 timeline over 3 weeks after the 20th case",
       caption="Data:European Centre for Disease Control and Prevention")