Are we dead yet?

Clarification: This a slightly different version of Pavel Rojtbergs wonderful Are we dead yet plots. This version here uses "Days since reaching 1 confirmed case per million residents" as x-axis instead of "Days since 500 confirmed".

I am quite frustrated with corona graphs in the news, since most reporters seem to have skipped math classes back then. For instance, just plotting the number of confirmed infections at the respective dates does not tell you anything due to the different time point of outbreak. So lets fix that first.

The following charts are based on live data from https://github.com/pomber/covid19, which in turn sources jhu.edu.

Countries to compare

Korea, South; Germany; US; China

Italy; Spain; France; China

Custom

This is still pretty useless as the countries differ in total population and population density, lets turn to something actually comparable.

The values are smoothed using a moving average over four days. This numbers actually allow comparing how well the different countries are doing in their corona countermeasurements, regardless of the population size.

An infection rate of 1.0 means no new infections.

# However, confirmed does not mean the same between different countries and even in the same country at different time points of the epidemic. This is due to the sampling bias induced by the limited amount of corona test kits. In the early days of the epidemic there are enough kits to test everyone, so many cases that do not yet show symptoms are tested. With ongoing spread, we hit limits on test-kit and health-system capacities and the focus shifts to testing severe cases only. This in turn pushes the fatality rate.

A significant increase of the fatality rate indicates that

the confirmed count is being under-estimated.
the health-system capacites being exhausted.

We are only talking about an estimate of fatality rate here, as we cannot measure the true fatality rate while the epidemic is ongoing. For us the relative rate between countries is sufficient. Therefore we simpliy chose the optimisitic deaths by confirmed ratio here.

# In contrast to the fatality rate, the mortality rate below is shown in dead per million inhabitants. This makes it independant of whether the confirmed count is estimated correctly. In most cases both will be correlated.

However, the mortality rate is a better indicator of the influence of the pandepic on a countries society and economy - especially when the health-system is exhausted.

The population count to compute the mortality is based on data from wikipedia

# To close with something positive, lets look at the absolute number of infections. That is, cases which are neither recovered nor died yet and are potentially infectious. If there are no such cases left, we can assume the epidemic to be stopped.

Notably, when this graph reaches zero you can not assume that the epidemic is stopped due to the stochastic nature of the data. However, a rise of the graph after a decline can indicate that a second wave is coming.