Long-Term Exposure to Fine and Coarse Particulate Matter and COVID-19 Incidence and Mortality Rate in Chile during 2020
Background: Several countries have documented the relationship between long-term exposure to air pollutants and epidemiological indicators of the COVID-19 pandemic, such as incidence and mortality. This study aims to explore the association between air pollutants, such as PM<sub>2.5</sub>...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-07-01
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Series: | International Journal of Environmental Research and Public Health |
Subjects: | |
Online Access: | https://www.mdpi.com/1660-4601/18/14/7409 |
Summary: | Background: Several countries have documented the relationship between long-term exposure to air pollutants and epidemiological indicators of the COVID-19 pandemic, such as incidence and mortality. This study aims to explore the association between air pollutants, such as PM<sub>2.5</sub> and PM<sub>10</sub>, and the incidence and mortality rates of COVID-19 during 2020. Methods: The incidence and mortality rates were estimated using the COVID-19 cases and deaths from the Chilean Ministry of Science, and the population size was obtained from the Chilean Institute of Statistics. A chemistry transport model was used to estimate the annual mean surface concentration of PM<sub>2.5</sub> and PM<sub>10</sub> in a period before the current pandemic. Negative binomial regressions were used to associate the epidemiological information with pollutant concentrations while considering demographic and social confounders. Results: For each microgram per cubic meter, the incidence rate increased by 1.3% regarding PM<sub>2.5</sub> and 0.9% regarding PM<sub>10</sub>. There was no statistically significant relationship between the COVID-19 mortality rate and PM<sub>2.5</sub> or PM<sub>10</sub>. Conclusions: The adjusted regression models showed that the COVID-19 incidence rate was significantly associated with chronic exposure to PM<sub>2.5</sub> and PM<sub>10</sub>, even after adjusting for other variables. |
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ISSN: | 1661-7827 1660-4601 |