Algorithm estimates COVID-19 infections within the US are 3 times above reported


An algorithm developed at the UT Southwestern center has estimated that there are almost 3 times as many COVID-19 infections within the US than the amount of confirmed cases.

The model makes daily predictions of both total and current infections across the US and within the 50 countries worst suffering from the virus.

It calculated that quite 71 million people within the US had contracted COVID-19 by February 4 when there have been only 26.7 million confirmed cases.

The model also estimated that 7 million people within the country currently have infections and are potentially contagious.

In other countries, the algorithm also calculated far higher numbers of infections than those reported. In the UK it calculated that there have been nearly 25 million instead of around 4 million confirmed cases while in Mexico. It predicted that there have been almost 27.6 million rather than 1.9 million.

The estimates of actual infections reveal for the primary time truth severity of COVID-19 across the U.S. and in countries worldwide said study author Jungsik Noh during a statement.

The algorithm’s calculations are derived from the amount of reported deaths, instead of the quantity of lab-confirmed cases.

It then assumes that the infection deathrate is 0.66%, supported early pandemic data in China.

It also examines other factors, like the typical days it takes for somebody with symptoms to either die or recover.

Finally, it compares its predictions with the amount of publicly-reported cases to calculate a ratio of confirmed-to-estimated infections.

Noh compared his early findings with existing prevalence rates found in studies that used blood tests to see for antibodies to the SARS-CoV-2 virus.

He found that the algorithm’s estimates closely corresponded to the share of individuals who tested positive for antibodies.

Noh admits that the estimates are rough, thanks to the uncertainty of things like the COVID-19 death rate. Nonetheless, he says they’re more accurate than the confirmed cases wont to guide public health policies:

Knowing truth severity in several regions will help us effectively fight against the virus spreading. The currently infected population is that the explanation for future infections and deaths. Its actual size during a region may be a crucial variable required when determining the severity of COVID-19 and building strategies against regional outbreaks.

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