tetano
Editor, Senior Moderator
PLoS One
. 2021 Jun 18;16(6):e0253169.
doi: 10.1371/journal.pone.0253169. eCollection 2021.
Association of the past epidemic of Mycobacterium tuberculosis with mortality and incidence of COVID-19
Kazuo Inoue[SUP] 1 [/SUP], Saori Kashima[SUP] 2 [/SUP]
Affiliations
Abstract
The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has created a remarkable and varying impact in every country, inciting calls for broad attention. Recently, the Bacillus Calmette-Guérin (BCG) vaccination has been regarded as a potential candidate to explain this difference. Herein, we hypothesised that the past epidemic of Mycobacterium tuberculosis (M. tuberculosis) may act as a latent explanatory factor for the worldwide differences seen in COVID-19 impact on mortality and incidence. We compared two indicators of past epidemic of M. tuberculosis, specifically, incidence (90 countries in 1990) and mortality (28 countries in 1950), with the mortality and incidence of COVID-19. We determined that an inverse relationship existed between the past epidemic indicators of M. tuberculosis and current COVID-19 impact. The rate ratio of the cumulative COVID-19 mortality per 1 million was 2.70 (95% confidence interval [CI]: 1.09-6.68) per 1 unit decrease in the incidence rate of tuberculosis (per 100,000 people). The rate ratio of the cumulative COVID-19 incidence per 1 million was 2.07 (95% CI: 1.30-3.30). This association existed even after adjusting for potential confounders (rate of people aged 65 over, diabetes prevalence, the mortality rate from cardiovascular disease, and gross domestic product per capita), leading to an adjusted rate ratio of COVID-19 mortality of 2.44, (95% CI: 1.32-4.52) and a COVID-19 incidence of 1.31 (95% CI: 0.97-1.78). After latent infection, Mycobacterium survives in the human body and may continue to stimulate trained immunity. This study suggests a possible mechanism underlying the region-based variation in the COVID-19 impact.
. 2021 Jun 18;16(6):e0253169.
doi: 10.1371/journal.pone.0253169. eCollection 2021.
Association of the past epidemic of Mycobacterium tuberculosis with mortality and incidence of COVID-19
Kazuo Inoue[SUP] 1 [/SUP], Saori Kashima[SUP] 2 [/SUP]
Affiliations
- PMID: 34143810
- DOI: 10.1371/journal.pone.0253169
Abstract
The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has created a remarkable and varying impact in every country, inciting calls for broad attention. Recently, the Bacillus Calmette-Guérin (BCG) vaccination has been regarded as a potential candidate to explain this difference. Herein, we hypothesised that the past epidemic of Mycobacterium tuberculosis (M. tuberculosis) may act as a latent explanatory factor for the worldwide differences seen in COVID-19 impact on mortality and incidence. We compared two indicators of past epidemic of M. tuberculosis, specifically, incidence (90 countries in 1990) and mortality (28 countries in 1950), with the mortality and incidence of COVID-19. We determined that an inverse relationship existed between the past epidemic indicators of M. tuberculosis and current COVID-19 impact. The rate ratio of the cumulative COVID-19 mortality per 1 million was 2.70 (95% confidence interval [CI]: 1.09-6.68) per 1 unit decrease in the incidence rate of tuberculosis (per 100,000 people). The rate ratio of the cumulative COVID-19 incidence per 1 million was 2.07 (95% CI: 1.30-3.30). This association existed even after adjusting for potential confounders (rate of people aged 65 over, diabetes prevalence, the mortality rate from cardiovascular disease, and gross domestic product per capita), leading to an adjusted rate ratio of COVID-19 mortality of 2.44, (95% CI: 1.32-4.52) and a COVID-19 incidence of 1.31 (95% CI: 0.97-1.78). After latent infection, Mycobacterium survives in the human body and may continue to stimulate trained immunity. This study suggests a possible mechanism underlying the region-based variation in the COVID-19 impact.