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Estimating sars-cov-2 infection fatality rate using data from one of the most affected areas worldwide
Signa Vitae ; 17(5):30-33, 2021.
Article in English | Scopus | ID: covidwho-1438977
ABSTRACT
The real estimate of the infection fatality rate of SARS-CoV-2 is a pivotal aspect of the COVID-19 pandemic. However, this number is still debated, since both the numerator and the denominator are uncertain. Data analysis from the most affected areas in the world minimizes computational errors and represents a unique approach for estimating infection fatality rate. We first extracted data from PubMed/Medline, Google, traditional media and social media to obtain the rate of SARS-CoV-2 antibodies seroprevalence in the most affected and best-studied areas in the world Val Seriana (Italy), Ischgl (Austria) and Manaus (Brasil). We then searched mortality data from national institutes of statistics and calculated excess mortality. We estimated the infection fatality rate considering several scenarios according to the mortality attributable to COVID-19 and the proportion of the population infected with the virus. We found that the seropositivity was surprisingly close to 40% in all the considered areas. We calculated the SARS-CoV-2 infection fatality rate for Val Seriana, using from half to the entire excess mortality (1208 deaths) and considering from 40% to 80% of the population as being infected with SARS-CoV-2. In the most conservative scenario, infection fatality rate was as low as 0.55%, while in the worst-case one it was 2.2%. We found that the seroconversion rate in the most affected areas worldwide is about 40%. We consequently estimated the infection fatality rate to be between 0.55% and 2.2% in an area with a relatively elderly population. © 2021 The Author(s). Published by MRE Press.

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Signa Vitae Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Signa Vitae Year: 2021 Document Type: Article