COVID-19 statistics: more people have become infected with the coronavirus

More people have become infected with the coronavirus

The official statistics announced by medical committees around the world regarding the incidence of coronavirus are actually incorrect. The immunologists of the Planck Institute say that statistics do not consider undetected cases at all. Around the world, the number of people with undiagnosed cases varies significantly. At the Institute, the specialists developed a demographic scaling model. It allows to evaluate the actual number of COVID-19 cases using a minimum of data.

That model shows: for example, in Germany, the number of cases is 1.8 times the official registered number. And in Italy, the number of infected residents of the country exceeded the officially registered figures six times.

The leading experts from the Institute used the model created for the ten countries most affected by the pandemic. Thus, they were able to estimate the number of unregistered infections. The distorted statistics are actually such that on average there are actually 4 times more infected people than confirmed cases. In Italy, approximately 1.4 million people are infected.

And that is 6 times higher than officially confirmed data. In the United States, nearly 3.2 million people are infected, and that is 2 times more than actually infected. And in all these ten countries, the number of official deaths is demonstrated by the fact that there were more people infected with the virus than statistics show.

But the created model can have significant errors from 1 to 12%. In fact, the incidence rate is even higher. The differences in infection spreading in different countries also varies significantly. That depends on the level of medicine, social responsibility, self-isolation and quarantine measures taken.

Since the death rate from COVID-19 infection in most countries is not yet known, the researchers transferred that from one control country to other countries, the researchers use different demographic parameters to calculate approximate data on deaths.

The model assumes that the death toll from COVID-19 is close to what it really is. But there are exceptions when concomitant diseases are considered the cause of death. That is only an assumption and not always applicable.