# Plotting Rt for covid-19 of UK by several instantaneous estimation methods # July 13, 2021: Made if (!require(COVID19)) { install.packages("COVID19", dep=TRUE) library(COVID19) } if(!require(EpiEstim)) { install.packages("EpiEstim", dep=TRUE) library(EpiEstim) } # use estimate_R() funtion, which includes Cori et al (2013)'s method # moving average from https://stackoverflow.com/questions/743812/calculating-moving-average ma <- function(x, n=7, s=1) {filter(x, rep(1 / n, n), sides=s)} x <- covid19(country="GBR", level=1, start="2020-01-01", end=Sys.Date()) z <- subset(x, (date>=as.Date("2020-11-01"))&(date=as.Date("2021-01-01")) palette("Okabe-Ito") matplot(as.Date(zz$date, "%d/%m/%y"), cbind(zz$Rt1, zz$Rt2, zz$Rt3, zz$Rt4), xlim=c(min(zz$date), max(zz$date)+20), ylim=c(0, 5), frame=FALSE, col=1:4, lty=1:4, type="l", xlab="Time (Month)", ylab="Rt", main="The changes of Rt in UK by 4 estimating methods [Data] Guidotti E, Ardia D (2020) COVID-19 Data Hub. Working paper https://doi.org/10.13140/RG.2.2.11649.81763", sub=sprintf("Until %s", max(zz$date))) segments(as.Date("2021-01-01"), 1, max(zz$date)+20, 1, col="red") text(as.Date("2021-03-08"), 3, "lockdown", pos=2) segments(as.Date("2021-03-08"), 0, as.Date("2021-03-08"), 5, lty=3, lwd=3, col="navy") text(as.Date("2021-03-08"), 3, "step1", pos=4) segments(as.Date("2021-04-12"), 0, as.Date("2021-04-12"), 5, lty=3, lwd=3, col="navy") text(as.Date("2021-04-12"), 3, "step2", pos=4) segments(as.Date("2021-05-17"), 0, as.Date("2021-05-17"), 5, lty=3, lwd=3, col="navy") text(as.Date("2021-05-17"), 3, "step3", pos=4) segments(as.Date("2021-07-19"), 0, as.Date("2021-07-19"), 5, lty=3, lwd=3, col="navy") text(as.Date("2021-07-19"), 3, "step4", pos=4) legend("topleft", col=1:4, lty=1:4, legend=c("Cori et al (2013)", "Toyo Keizai", "Japan's NIID", "Toyo Keizai w/o adjustment"))