In CBDRH/covidrecon: Pulls and Analyses COVID data

knitr::opts_chunk$set(echo = TRUE)

library(dplyr)
library(tibble)
library(ggplot2)
library(lubridate)
library(patchwork)
library(EpiEstim)

a <- tibble(R= (2.5 - (1:100)/50), 
            I=round((1:100)^R),
            dates=ymd("2020-01-01") + days(1:100),
            cumI=cumsum(I),
            col = if_else(I == max(I), 1, 0))

estR <- estimate_R(select(a, dates, I),
                  method="parametric_si",
                  config = make_config(list(
                                       mean_si = 7.0, 
                                       std_si = 3.0)))


p0 <- ggplot(a, aes(x=cumI, y=I, col=col)) + geom_point() +
   scale_y_log10() + scale_x_log10() +
   labs(title="Log-log")

p1 <- ggplot(a, aes(x=cumI, y=I, col=col)) + geom_point() +
   scale_y_continuous() + 
   scale_x_continuous() +
   labs(title="Lin-Lin")


p2 <- ggplot(a, aes(x=dates, y=I, col=col)) + geom_point() +
         labs(title="Linear incidence vs time")


p3 <- ggplot(a, aes(x=dates, y=R, col=col)) + geom_point() +
           labs(title="Generating R vs time")


p0 / p1 / p2 / p3 / plot(estR, "R") + scale_y_log10() 

CBDRH/covidrecon documentation built on May 27, 2020, 9:41 a.m.