knitr::opts_chunk$set(echo = TRUE)
library("xlsx")
library("readxl")

The evolution of the coronavirus has been analyzed since April 27, 2020, when the Government modifies the accounting criteria for hospitalized patients and new cases. Before that date, the Spanish Government counted the new positives both by antibodies and by PCR, and how hospitalized only the positives by PCR. On April 26, nearly 24,000 hospitalized patients were included in the statistics and only those verified by PCR began to count as positive.

In this study we will count how cases both confirmed by antibodies and by PCR, taking advantage of the fact that, although the Government does not compute the former, the “Instituto de Salud Carlos III” provides both data.

I select my excel file, made with data from the “Instituto de Salud Carlos III”, the data that we will use in the analysis, and I save it in the variable “coronadata”.

knitr::opts_chunk$set(echo = TRUE)
coronadata<-read_excel("C:/Users/JoséIgnacio/AppData/Roaming/Microsoft/Windows/Network Shortcuts/coronavirus 12-05-pcr+ag datos claros.xlsx")

We make a graph of the ratio of Total hospitalized / total detected, both magnitudes being data accumulated since the start of the pandemic in Spain, where a clear downward trend can be seen.

plot(coronadata$Fecha,coronadata$`hosp/casos acum.`,
      type='s',
      pch=19,
     col="blue",
      main = "Total Hosp Evolution/total detected cases",
     xlab = "Date")

We make a graph of the active cases, where a downward trend can also be observed.

knitr::opts_chunk$set(echo = TRUE)
plot(coronadata$Fecha,coronadata$`casos act.`,
     type='s',
      pch=19,
    col="orange",
      main = "Active cases evolution",
      xlab = "Date",
      ylab = "Active cases")

We make a graph of the ratio of new hospitalized cases / total new cases daily.

knitr::opts_chunk$set(echo = TRUE)
plot(coronadata$Fecha,coronadata$`Hosp/casos (nuevos)`,
     type='b',
      pch=19,
    col="blue",
      main = "Evolution Hospitalized / Cases (new)",
      xlab = "Date",
      ylab = "Hospitalized/Cases(new)")
      abline(h=mean(coronadata$`Hosp/casos (nuevos)`), col="red")

We can see that the mean (horizontal line) is slightly higher than 30%. It has been estimated that 20% of those infected require hospitalization. We attribute this higher percentage to the fact that tests are carried out mainly on people with symptoms, how we actually know what is happening.

It is also known that approximately 25% of those admitted require an ICU. Let’s see what the ratio is in Spain in recent weeks.

knitr::opts_chunk$set(echo = TRUE)
plot(coronadata$Fecha,coronadata$`UCI/Hosp (nuevos)`,
                 type='b',
                 pch=19,
                  col="orange",
                  main = "Evolution ICU/Hospitalized(new)",
                 xlab = "Date",
                ylab = "ICU/Hospitalized(new)")
 abline(h=mean(coronadata$`UCI/Hosp (nuevos)`, col="red"))

We can see that the mean (horizontal line) is slightly above 10%, indicating that the severity of the disease is now much lower.

We conclude from the study that the coronavirus is decreasing both in incidence (active cases) and in severity, so it is possible that it may disappear or become a disease with very little mortality without the need for a vaccine.