Ambient air pollution and risk of SARS-CoV-2 infection and of COVID-19 disease in a cohort study in Catalonia (COVICAT Cohort)

Kogevinas, Manolis; Vinyals, Gemma Castaño; Karachaliou, Marianna; Espinosa, Ana; Cid, Rafael de; Aymerich, Judith García; Gordo, Cristina; Moncunill, Gemma; Dobaño, Carlota; Tonne, Cathryn

doi:10.1289/isee.2021.o-to-177

Cited by 3 publications

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“…This setting includes not only the immediate educational environment (the classroom) but also the geographical location of the education centre on the globe, which influences the climatology and its temporary pandemic effect. Long-term exposure to air pollution was associated in [23] with stronger antibody response among infected individuals, probably reflecting higher viral exposure and disease severity. However, probably the most critical aspect is the conditioning of the classrooms to maintain clean indoor environments.…”

Section: Proposed Model For Calculating Cumulative Riskmentioning

confidence: 98%

Model and Validation Study for Optimizing Students’ Positions in Classrooms to Limit the Spread of Infectious Diseases Such as COVID

Molina-Jordá

2022

Education Sciences

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Classrooms at any educational institution have become high-risk sites for contagion during past and present pandemic periods caused by the SARS-CoV-2 (COVID-19) viral siege, given the prolonged time educators and students spend in joint activity. Among the several strategies employed by educational institutions to minimize the outbreak of contagion are regulating classroom capacity and studying the optimal spatial arrangement of students. The architectural features of each classroom, which include corridors, ventilation components, total volume, and maximum capacity, among other factors, have a direct impact on the risk of human contagion. This work is a proposal to optimize the spatial arrangement of students to minimize the risk of contagion, considering not only the distance between them, but also the different architectural features in the classrooms. The analyses conducted in the different scenarios conclude with a comparison of risk in terms of the arrangement of students that various educators would have used at different education levels in their classrooms based solely on intuitive criteria. The results indicate that in some situations, the locations chosen by educators can double the risk of infection compared to optimal arrangements.

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Section: Proposed Model For Calculating Cumulative Riskmentioning

confidence: 98%

Model and Validation Study for Optimizing Students’ Positions in Classrooms to Limit the Spread of Infectious Diseases Such as COVID

Molina-Jordá

2022

Education Sciences

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“…The COVID‐19 endpoints varied among studies and included number of cases, number of deaths, case‐hospitalization rate, case‐fatality rate, percent of severe infection, basic reproduction number, intensive care unit (ICU) admissions, and epidemic escalation. In addition, emerging cohort studies suggest long‐term exposure to air pollution prior to the pandemic is associated with a higher risk of severe COVID‐19 in those infected with SARS‐CoV‐2 (Bozack et al, 2021; Kogevinas et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Association between air pollution and COVID‐19 disease severity via Bayesian multinomial logistic regression with partially missing outcomes

et al. 2022

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Recent ecological analyses suggest air pollution exposure may increase susceptibility to and severity of coronavirus disease 2019 (COVID‐19). Individual‐level studies are needed to clarify the relationship between air pollution exposure and COVID‐19 outcomes. We conduct an individual‐level analysis of long‐term exposure to air pollution and weather on peak COVID‐19 severity. We develop a Bayesian multinomial logistic regression model with a multiple imputation approach to impute partially missing health outcomes. Our approach is based on the stick‐breaking representation of the multinomial distribution, which offers computational advantages, but presents challenges in interpreting regression coefficients. We propose a novel inferential approach to address these challenges. In a simulation study, we demonstrate our method's ability to impute missing outcome data and improve estimation of regression coefficients compared to a complete case analysis. In our analysis of 55,273 COVID‐19 cases in Denver, Colorado, increased annual exposure to fine particulate matter in the year prior to the pandemic was associated with increased risk of severe COVID‐19 outcomes. We also found COVID‐19 disease severity to be associated with interactions between exposures. Our individual‐level analysis fills a gap in the literature and helps to elucidate the association between long‐term exposure to air pollution and COVID‐19 outcomes.

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“…Entre todos os poluentes conhecidos com efeitos negativos na saúde respiratória, os que mais têm sido relacionados à mortalidade por COVID-19 são os materiais particulados (Fine Particulate Matter);TUNG et al, 2021;YAO et al, 2020) e os poluentes atmosféricos contendo nitrogênio e ozônio(AKAN, 2022; CONTICINI et al, n.d.;KOGEVINAS et al, 2021; MARQUÈS et al, 2021). Em estudos, realizados em diferentes locais do mundo, pesquisadores investigaram a exposição a longo prazo à poluição do ar e à gravidade do COVID-19, foi o casode Chen et al, (2022) na Califórnia, EUA, onde descobriram um aumento na exposição média de PM2,5 em 1 ano associado ao aumento do risco de morte relacionadas a COVID-19.…”

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Poluição Do Ar E Covid-19: Análise Da Mortalidade Na Região Norte Do Brasil

Silva,

Dias,

Barbosa

et al. 2024

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A poluição do ar é problemática presente em muitos contextos socioespaciais afetando milhões de pessoas anualmente no mundo. A intensa urbanização e os riscos socioambientais estão atrelados a mortalidade por doenças cardiorrespiratórias agravadas por contextos atípicos, como o da pandemia da Covid-19. Por meio de dados de mortalidade do Ministério da Saúde e poluentes atmosféricos buscou-se identificar a relação entre a exposição à poluição do ar e os óbitos por Covid -19 na região Norte do Brasil. Utilizamos um modelo estatístico misto binomial negativo com inflação de zero (ZINB) para os óbitos por Covid-19 em nível de município como desfecho, e para a média de longo prazo, poluentes atmosféricos (PM2,5, NO2 e O3). Foram incluídos variáveis-controles - climáticas, demográficas e oferta de equipamentos e profissionais de saúde. Os resultados evidenciam associação positiva entre as mortes por Covid-19 e material particulado (PM2,5) com incremento de cerca de 1,15 µg/m³ no modelo principal, assim como, para os modelos bipoluentes (O3 e NO2) e (PM2,5 e O3). A análise geral confirma o incremento de poluentes atmosféricos no agravamento e consequente mortalidade por Covid-19 para todos os municípios da Região Norte. Contexto atrelado também a baixa escolaridade, a baixa renda, a baixa oferta de leitos e profissionais de saúde, indicando a seletividade espacial existente, principalmente, para populações vulnerabilizadas.

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Ambient air pollution and risk of SARS-CoV-2 infection and of COVID-19 disease in a cohort study in Catalonia (COVICAT Cohort)

Cited by 3 publications

References 0 publications

Model and Validation Study for Optimizing Students’ Positions in Classrooms to Limit the Spread of Infectious Diseases Such as COVID

Model and Validation Study for Optimizing Students’ Positions in Classrooms to Limit the Spread of Infectious Diseases Such as COVID

Association between air pollution and COVID‐19 disease severity via Bayesian multinomial logistic regression with partially missing outcomes

Poluição Do Ar E Covid-19: Análise Da Mortalidade Na Região Norte Do Brasil

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