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Negative-Binomial and quasi-poisson regressions between COVID-19, mobility and environment in São Paulo, Brazil.
Ibarra-Espinosa, Sergio; Dias de Freitas, Edmilson; Ropkins, Karl; Dominici, Francesca; Rehbein, Amanda.
  • Ibarra-Espinosa S; Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, Brazil. Electronic address: zergioibarra@gmail.com.
  • Dias de Freitas E; Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, Brazil.
  • Ropkins K; Institute for Transport Studies, University of Leeds, UK.
  • Dominici F; Harvard Data Science Initiative, Harvard University, Boston, MA, 02138, USA.
  • Rehbein A; Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, Brazil.
Environ Res ; 204(Pt D): 112369, 2022 03.
Article in English | MEDLINE | ID: covidwho-1574591
ABSTRACT
Brazil, the country most impacted by the coronavirus disease 2019 (COVID-19) on the southern hemisphere, use intensive care admissions per day, mobility and other indices to monitor quarantines and prevent the transmissions of SARS-CoV-2. In this study we quantified the associations between residential mobility index (RMI), air pollution, meteorology, and daily cases and deaths of COVID-19 in São Paulo, Brazil. We applied a semiparametric generalized additive model (GAM) to estimate 1) the association between RMI and COVID-19, accounting for ambient particulate matter (PM2.5), ozone (O3), relative humidity, temperature and delayed exposure between 4 and 21 days, and 2) the association between COVID-19 and exposure to for ambient particulate matter (PM2.5), ozone (O3), accounting for relative humidity, temperature and mobility. We found that an RMI of 45.28% results in 1212 cases (95% CI 1189 to 1235) and 44 deaths (95% CI 40 to 47). Increasing the isolation from 45.28% to 50% would avoid 438 cases and 21 deaths. Also, we found that an increment of 10 µg⋅m-³ of PM2.5 results in a risk of 1.140 (95% CI 1.021 to 1.274) for cases and 1.086 (95% CI 1.008 to 1.170) for deaths, while O3 produces a relative risk of 1.075 (95% CI 1.006 to 1.150) for cases and 1.063 (95% CI 1.006 to 1.124) for deaths, respectively. We compared our results with observations and literature review, finding well agreement. Policymakers can use such mobility indices as tools to control social distance activities. Spatial distancing is an important factor to control COVID-19, however, measuring face-mask usage would enhance the understanding the pandemic dynamic. Small increments of air pollution result in an increased number of COVID-19 cases and deaths.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Air Pollutants / Air Pollution / COVID-19 Type of study: Observational study / Prognostic study / Reviews Limits: Humans Country/Region as subject: South America / Brazil Language: English Journal: Environ Res Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Air Pollutants / Air Pollution / COVID-19 Type of study: Observational study / Prognostic study / Reviews Limits: Humans Country/Region as subject: South America / Brazil Language: English Journal: Environ Res Year: 2022 Document Type: Article