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COVID-19 and climatic factors: A global analysis.
Islam, Nazrul; Bukhari, Qasim; Jameel, Yusuf; Shabnam, Sharmin; Erzurumluoglu, A Mesut; Siddique, Muhammad A; Massaro, Joseph M; D'Agostino, Ralph B.
  • Islam N; Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK; MRC Epidemiology Unit, University of Cambridge, Cambridge, UK. Electronic address: nazrul.islam@ndph.ox.ac.uk.
  • Bukhari Q; McGovern Institute for Brain Research, Massachusetts Institute of Technology (MIT), Cambridge, USA.
  • Jameel Y; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology (MIT), Cambridge, USA.
  • Shabnam S; Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA, USA.
  • Erzurumluoglu AM; MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
  • Siddique MA; Department of Electrical Engineering, National University of Computer and Emerging Sciences (NUCES), Lahore, Pakistan.
  • Massaro JM; Department of Biostatistics, Boston University School of Public Health, Boston, USA.
  • D'Agostino RB; Department of Mathematics and Statistics, Boston University, Boston, USA.
Environ Res ; 193: 110355, 2021 Feb.
Artículo en Inglés | MEDLINE | ID: covidwho-893763
ABSTRACT

BACKGROUND:

It is unknown if COVID-19 will exhibit seasonal pattern as other diseases e.g., seasonal influenza. Similarly, some environmental factors (e.g., temperature, humidity) have been shown to be associated with transmission of SARS-CoV and MERS-CoV, but global data on their association with COVID-19 are scarce.

OBJECTIVE:

To examine the association between climatic factors and COVID-19.

METHODS:

We used multilevel mixed-effects (two-level random-intercepts) negative binomial regression models to examine the association between 7- and 14-day-lagged temperature, humidity (relative and absolute), wind speed and UV index and COVID-19 cases, adjusting for Gross Domestic Products, Global Health Security Index, cloud cover (%), precipitation (mm), sea-level air-pressure (mb), and daytime length. The effects estimates are reported as adjusted rate ratio (aRR) and their corresponding 95% confidence interval (CI).

RESULTS:

Data from 206 countries/regions (until April 20, 2020) with ≥100 reported cases showed no association between COVID-19 cases and 7-day-lagged temperature, relative humidity, UV index, and wind speed, after adjusting for potential confounders, but a positive association with 14-day-lagged temperature and a negative association with 14-day-lagged wind speed. Compared to an absolute humidity of <5 g/m3, an absolute humidity of 5-10 g/m3 was associated with a 23% (95% CI 6-42%) higher rate of COVID-19 cases, while absolute humidity >10 g/m3 did not have a significant effect. These findings were robust in the 14-day-lagged analysis.

CONCLUSION:

Our results of higher COVID-19 cases (through April 20) at absolute humidity of 5-10 g/m3 may be suggestive of a 'sweet point' for viral transmission, however only controlled laboratory experiments can decisively prove it.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Estudio experimental / Ensayo controlado aleatorizado Límite: Humanos Idioma: Inglés Revista: Environ Res Año: 2021 Tipo del documento: Artículo

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Estudio experimental / Ensayo controlado aleatorizado Límite: Humanos Idioma: Inglés Revista: Environ Res Año: 2021 Tipo del documento: Artículo