In rplzzz/CovMitigation: COVID-19 infection model for Virginia

suppressPackageStartupMessages(library(dplyr))
library(tidyr)
library(ggplot2)
library(CovMitigation)
library(vacovdata)
library(ggthemes)
library(NYTimesCOVID19)

April growth rates by county

gr <- function(date, cases) {
  imax <- length(date)
  stopifnot(imax == length(cases))
  (log(cases[imax]) - log(cases[1])) / as.numeric(date[imax]-date[1])
}
aprildata <- 
  filter(cov19county, state == 'Virginia',
         !is.na(fips),
         date >= as.Date('2020-04-01'),
         date <= as.Date('2020-04-30')
         )
growthrates <- 
  group_by(aprildata, county, fips) %>%
  summarise(rate=gr(date, cases), cases=max(cases)) %>%
  mutate(td=log(2)/rate) %>%
  arrange(desc(rate))

#hist(filter(growthrates, rate>0)$td, breaks=25)
ggplot(growthrates, aes(x=td)) + geom_histogram(bins=50, alpha=0.7) + theme_bw()

Counties in the UVA catchment:

uvacounties <- filter(growthrates, fips %in% sampleCounties$fips)
print(uvacounties)

Counties with doubling times less than 10:

print(filter(growthrates, td <= 10))

Counties with doubling times between 10 and 20

print(filter(growthrates, td > 10, td<=20))

Counties with doubling times greater than 20

print(filter(growthrates, td >20, rate>0))

No growth or no cases observed

print(filter(growthrates, rate==0))

rplzzz/CovMitigation documentation built on June 7, 2021, 8:48 a.m.