Title BCG epidemiology supports its protection against COVID-19? A word of caution /
Authors Szigeti, Reka ; Kellermayer, Domos ; Trakimas, Giedrius ; Kellermayer, Richard
DOI 10.1371/journal.pone.0240203
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Is Part of PLOS One.. San Francisco : Public Library Science. 2020, vol. 15, iss. 10, art. no. e0240203, p. 1-9.. ISSN 1932-6203
Keywords [eng] Bacillus Calmette-Guerin ; Coronavirus ; COVID-19 ; SARS-CoV-2
Abstract [eng] The COVID-19 pandemic, caused by type 2 Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2), puts all of us to the test. Epidemiologic observations could critically aid the development of protective measures to combat this devastating viral outbreak. Recent observations, linked nation based universal Bacillus Calmette-Guerin (BCG) vaccination to potential protection against morbidity and mortality from SARS-CoV-2, and received much attention in public media. We wished to validate the findings by examining the country based association between COVID-19 mortality per million population, or daily rates of COVID-19 case fatality (i.e. Death Per Case/Days of the endemic [dpc/d]) and the presence of universal BCG vaccination before 1980, or the year of the establishment of universal BCG vaccination. These associations were examined in multiple regression modeling based on publicly available databases on both April 3(rd)and May 15(th)of 2020. COVID-19 deaths per million negatively associated with universal BCG vaccination in a country before 1980 based on May 15(th)data, but this was not true for COVID-19 dpc/d on either of days of inquiry. We also demonstrate possible arbitrary selection bias in such analyses. Consequently, caution should be exercised amidst the publication surge on COVID-19, due to political/economical-, arbitrary selection-, and fear/anxiety related biases, which may obscure scientific rigor. We argue that global COVID-19 epidemiologic data is unreliable and therefore should be critically scrutinized before using it as a nidus for subsequent hypothesis driven scientific discovery.
Published San Francisco : Public Library Science
Type Journal article
Language English
Publication date 2020
CC license CC license description