Covid-19: Correlation Between Confirmed Cases and Deaths

Covid-19: Correlation Between Confirmed Cases and Deaths

Covid-19: Correlation Between Confirmed Cases and Deaths. After how many days we reach the Maximum Correlation between Confirmed (Covid-19) Cases and Deaths

What is the daily correlation of *Confirmed *versus *Death *Cases in Covid-19. In other words, the people who have passed away, on average, how many days ago they have been reported (i.e. “Confirmed”) as Covid-19 new cases.

To answer this question, we can take the correlation between the Daily Confirmed vs Daily Deaths and trying different lag values of the confirmed cases, since the assumption is that it will take some days for someone to pass away since has been diagnosed with Covid-19.

The problem with the data is that is affected by the number of tests and also during some days like weekends they do not report all the cases. This implies that our analysis is not valid, but we will try to see what get. We will analyze Italy.

Italy: Correlation Between Confirmed Cases and Deaths

## https://github.com/RamiKrispin/coronavirus
devtools::install_github("RamiKrispin/coronavirus")
#checks if there is data update on the Github version
coronavirus::update_datasets(silence = TRUE)

library(coronavirus) 
library(tidyverse)
library(lubridate)

data("coronavirus")
df<-coronavirus%>%filter(country=='Italy', date>='2020-02-15')%>%select(date, country, type, cases)%>%
  group_by(date, country, type) %>%pivot_wider(names_from =type, values_from=cases) %>%ungroup()
correlations<-c()
lags<-c(0:20)
for (k in lags) {
tmp<-df%>%mutate(lagk=lag(confirmed,k))%>%select(death,lagk)%>%na.omit()

  correlations<-c(correlations,cor(tmp$death, tmp$lagk))
}
data.frame(lags, correlations)
data.frame(lags, correlations)%>%ggplot(aes(x=lags, y=correlations))+geom_point()

rstats correlation r covid19 ai

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