A US study shows that 2.4 billion may have already been infected with COVID-19


A new American study involving researchers from Washington University in St. Louis, University of California, University of Washington, and the Medical College of Georgia at Augusta University has found that far more people have been infected with the SARS-CoV-2 virus, with possible amounts even reaching 2.4 billion people compared what was reported officially.

The study findings were published in the peer reviewed journal: Current Science.

Globally, the number of reported COVID- 19 cases from December 2019 to 6 May 2022 was 513,955,910 and the reported number of deaths during this period was 6,190,349 (ref. 1). The number of hospitali- zed cases all over the world due to the pandemic started declining at the begin- ning of April 2022 (ref. 2).

Globally, the number of fully vaccinated individuals as of 6 May 2022 was 5.1 billion (ref. 1). Vaccinated individuals have higher chances of not being hospitalized2, but they still have some probability of acquiring the virus3.

This indicates that COVID-19 transmission occurs between vaccinated and unvaccinated individuals.

The present study aims to provide a range of model-based estimates of the total number of COVID-19 cases in the world from the beginning of the pandemic to 6 May 2022 and the proportion of the reported cases. The methodology used is similar to the model-based estimation of underreporting of COVID-19 cases in eight countries through 31 March 2020 (ref. 4).

The degree of underreporting could have varied over the period 2020–22. There could be one or more rea- sons for this, namely (i) all COVID-19 positive cases have not been tested, and (ii) not all those who tested positive for COVID-19 have been reported. In the past, there have been methods to understand the extent of underreporting in various epidemics. How- ever, the supportive data collection for such purposes is limited5–8.

The estimated world population in 2022 is 7.954 billion (ref. 8). This is divided into 1.989 billion (aged 0–14 years), 5.170 bil- lion (aged 15–65 years) and 795 million (more than 65 years)9. The estimated world population in 2020 was 7.794 billion. The average population for 2020–22 is 7.874 billion and the average annual exponential growth rate of the population during this

tributed to infections at the rate of 0.065 during 2020–22. This rough estimate  of the global average force of infection sug- gests that every 1000 individuals in the world contributed 65 new infections. This average estimate will vary on several factors, such as demographic characteristics (e.g. age, sex, race), socio-economic status (e.g. occupation, income and education), public health measures (e.g. mask-wearing, clo- sures and lockdowns) and medical conditions (e.g. congestive heart failure and diabetes). The figure 65/1000 only indicates the glo- bal reported number, which is underreported. We have generated model-based COVID- 19 infection data as of 6 May 2022 (Table 1).  We have adopted the   methodology in

our previous study on underreporting4. The transmission parameter b was initially con- sidered 2.0 ´ 1011 and simulations were per- formed for 121 weeks from 1 January 2020. The transmission parameter indicates the average number of susceptible people that one infected person will infect during a unit period. We have provided ten additional model-based   simulations   performed   for b ± b × k% for k = 1, 2, …, 5 (Table 1). The Appendix provides technical details.

With an approximate population of 5.1 billion fully vaccinated in the world, the spread of COVID-19 might have been re- duced. Yet the debate on the actual magni- tude and number of infected individuals during 2020–22 is still not over. We esti- mate that the number of COVID-19 infec- tions from December 2019 to 6 May 2022 is between 601 million and 2.4 billion.

This wide range is indicative of the factors that have affected the reporting of COVID-19 cases across different countries, which include deliberate data-tampering, both mali- cious and otherwise, the inability to conduct accurate case tracking and the lack of uni- formity in reporting, among others8.

Our goal here is to provide model-based estimates and predictions of global under- reporting of COVID-19 cases during a criti- cal period of the pandemic. There is evidence that the widely advertised global case counts are quite inaccurate because of the lack of information. We have explored and explained some of these phenomena.


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