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Estimate asymptomatic cases in Italy during the COVID-19 pandemic

library(asymptor)

Let’s start by loading the example data. It’s bundled in the package but originally comes from https://github.com/GoogleCloudPlatform/covid-19-open-data (Apache License 2.0).

df <- readRDS(system.file("extdata", "covid19_italy.rds", package = "asymptor"))
head(df)
#>         date new_cases new_deaths
#> 1 2020-01-02         0          0
#> 2 2020-01-03         0          0
#> 3 2020-01-04         0          0
#> 4 2020-01-05         0          0
#> 5 2020-01-06         0          0
#> 6 2020-01-07         0          0

We can feed this data directly to the estimate_asympto() function. This function requires 3 columns, labelled as date, new_cases, new_deaths, containing the daily counts (not the cumulated total!)

asy <- estimate_asympto(df$date, df$new_cases, df$new_deaths)
head(asy)
#>         date lower upper
#> 1 2020-01-02    NA    NA
#> 2 2020-01-03     0    NA
#> 3 2020-01-04     0    NA
#> 4 2020-01-05     0    NA
#> 5 2020-01-06     0    NA
#> 6 2020-01-07     0    NA

We may want to visualise these estimations alongside the empirical data. So, we start by merging the two datasets:

res <- merge(df, asy)
head(res)
#>         date new_cases new_deaths lower upper
#> 1 2020-01-02         0          0    NA    NA
#> 2 2020-01-03         0          0     0    NA
#> 3 2020-01-04         0          0     0    NA
#> 4 2020-01-05         0          0     0    NA
#> 5 2020-01-06         0          0     0    NA
#> 6 2020-01-07         0          0     0    NA

Alternatively, we can directly use a tidyverse-compatible syntax:

library(dplyr)
res <- df %>%
  mutate(lower = estimate_asympto(date, new_cases, new_deaths, "lower")$lower,
         upper = estimate_asympto(date, new_cases, new_deaths, "upper")$upper)
head(res)
#>         date new_cases new_deaths lower upper
#> 1 2020-01-02         0          0    NA    NA
#> 2 2020-01-03         0          0     0    NA
#> 3 2020-01-04         0          0     0    NA
#> 4 2020-01-05         0          0     0    NA
#> 5 2020-01-06         0          0     0    NA
#> 6 2020-01-07         0          0     0    NA

Then, we can the ggplot2 package to plot the result:

library(ggplot2)
ggplot(res, aes(x = date)) +
  geom_line(aes(y = new_cases+lower), col = "grey30") +
  geom_ribbon(aes(ymin = new_cases+lower, 
                  ymax = new_cases+upper), 
              fill = "grey30") +
  geom_line(aes(y = new_cases), color = "red") +
  labs(title = "Estimated total vs detected cases of COVID-19 in Italy",
       y = "Cases") +
  theme_minimal()
#> Warning: Removed 1 row(s) containing missing values (geom_path).

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.