Relationship between COVID-19 Cases and Environmental Contaminants in Quito, Ecuador

Andrea Damaris Hernández-Allauca (), Carlos Gabriel Pérez Castillo, Juan Federico Villacis Uvidia, Paula Abdo-Peralta, Catherine Frey, Guicela Margoth Ati-Cutiupala, Juan Ureña-Moreno and Theofilos Toulkeridis
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Andrea Damaris Hernández-Allauca: Faculty of Natural Resources, Escuela Superior Politecnica de Chimborazo, Panamericana Sur, km 1 ½, Riobamba EC-060155, Ecuador
Carlos Gabriel Pérez Castillo: Independent Researcher, Riobamba EC-060155, Ecuador
Juan Federico Villacis Uvidia: Faculty of Accounting and Auditing, Technical University of Ambato, Ambato EC-180207, Ecuador
Paula Abdo-Peralta: Faculty of Natural Resources, Escuela Superior Politecnica de Chimborazo, Panamericana Sur, km 1 ½, Riobamba EC-060155, Ecuador
Catherine Frey: Independent Researcher, Riobamba EC-060155, Ecuador
Guicela Margoth Ati-Cutiupala: Faculty of Natural Resources, Escuela Superior Politecnica de Chimborazo, Panamericana Sur, km 1 ½, Riobamba EC-060155, Ecuador
Juan Ureña-Moreno: Independent Researcher, Riobamba EC-060155, Ecuador
Theofilos Toulkeridis: School of Geology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

IJERPH, 2024, vol. 21, issue 10, 1-24

Abstract: The relationship between COVID-19 infections and environmental contaminants provides insight into how environmental factors can influence the spread of infectious diseases. By integrating epidemiological and environmental variables into a mathematical framework, the interaction between virus spread and the environment can be determined. The aim of this study was to evaluate the impact of atmospheric contaminants on the increase in COVID-19 infections in the city of Quito through the application of statistical tests. The data on infections and deaths allowed to identify the periods of greatest contagion and their relationship with the contaminants O 3 , SO 2 , CO, PM 2.5 , and PM 10 . A validated database was used, and statistical analysis was applied through five models based on simple linear regression. The models showed a significant relationship between SO 2 and the increase in infections. In addition, a moderate correlation was shown with PM 2.5 , O 3 , and CO, and a low relationship was shown for PM 10 . These findings highlight the importance of having policies that guarantee air quality as a key factor in maintaining people’s health and preventing the proliferation of viral and infectious diseases.

Keywords: infectious diseases; COVID-19; atmospheric contaminants; statistical tests; linear regression (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2024
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