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Association between meteorological factors and COVID-19 transmission in low- and middle-income countries: A time-stratified case-crossover study.
Wang, Yu; Lyu, Yiran; Tong, Shilu; Ding, Cheng; Wei, Lan; Zhai, Mengying; Xu, Kaiqiang; Hao, Ruiting; Wang, Xiaochen; Li, Na; Luo, Yueyun; Li, Yonghong; Wang, Jiao.
Afiliación
  • Wang Y; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
  • Lyu Y; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
  • Tong S; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China; Shanghai Children's Medical Center, Shanghai Jiao Tong University, Shanghai, 200025, China; School of Public Health, I
  • Ding C; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
  • Wei L; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
  • Zhai M; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
  • Xu K; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China; School of Public Health, Hebei University, Hebei, 071000, China.
  • Hao R; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
  • Wang X; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
  • Li N; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
  • Luo Y; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
  • Li Y; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
  • Wang J; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China. Electronic address: wangjiao@nieh.chinacdc.cn.
Environ Res ; 231(Pt 1): 116088, 2023 Aug 15.
Article en En | MEDLINE | ID: mdl-37169140
ABSTRACT

BACKGROUND:

Evidence is limited regarding the association between meteorological factors and COVID-19 transmission in low- and middle-income countries (LMICs).

OBJECTIVE:

To investigate the independent and interactive effects of temperature, relative humidity (RH), and ultraviolet (UV) radiation on the spread of COVID-19 in LMICs.

METHODS:

We collected daily data on COVID-19 confirmed cases, meteorological factors and non-pharmaceutical interventions (NPIs) in 2143 city- and district-level sites from 6 LMICs during 2020. We applied a time-stratified case-crossover design with distributed lag nonlinear model to evaluate the independent and interactive effects of meteorological factors on COVID-19 transmission after controlling NPIs. We generated an overall estimate through pooling site-specific relative risks (RR) using a multivariate meta-regression model.

RESULTS:

There was a positive, non-linear, association between temperature and COVID-19 confirmed cases in all study sites, while RH and UV showed negative non-linear associations. RR of the 90th percentile temperature (28.1 °C) was 1.14 [95% confidence interval (CI) 1.02, 1.28] compared with the 50th percentile temperature (24.4 °C). RR of the10th percentile UV was 1.41 (95% CI 1.29, 1.54). High temperature and high RH were associated with increased risks in temperate climate but decreased risks in tropical climate, while UV exhibited a consistent, negative association across climate zones. Temperature, RH, and UV interacted to affect COVID-19 transmission. Temperature and RH also showed higher risks in low NPIs sites.

CONCLUSION:

Temperature, RH, and UV appeared to independently and interactively affect the transmission of COVID-19 in LMICs but such associations varied with climate zones. Our results suggest that more attention should be paid to meteorological variation when the transmission of COVID-19 is still rampant in LMICs.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: Environ Res Año: 2023 Tipo del documento: Article País de afiliación: China
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: Environ Res Año: 2023 Tipo del documento: Article País de afiliación: China