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Environ Sci Pollut Res Int . Are meteorological factors enhancing COVID-19 transmission in Bangladesh? Novel findings from a compound Poisson genera

tetano

Editor, Senior Moderator
Environ Sci Pollut Res Int


. 2020 Oct 28.
doi: 10.1007/s11356-020-11273-2. Online ahead of print.
Are meteorological factors enhancing COVID-19 transmission in Bangladesh? Novel findings from a compound Poisson generalized linear modeling approach


Abu Reza Md Towfiqul Islam[SUP] 1 [/SUP], Md Hasanuzzaman[SUP] 2 [/SUP], Mashura Shammi[SUP] 3 [/SUP], Roquia Salam[SUP] 2 [/SUP], Md Bodrud-Doza[SUP] 4 [/SUP], Md Mostafizur Rahman[SUP] 5 [/SUP], Md Abdul Mannan[SUP] 6 [/SUP], Saleemul Huq[SUP] 7 [/SUP]



Affiliations

Abstract

Novel coronavirus (SARS-CoV-2) causing COVID-19 disease has arisen to be a pandemic. Since there is a close association between other viral infection cases by epidemics and environmental factors, this study intends to unveil meteorological effects on the outbreak of COVID-19 across eight divisions of Bangladesh from March to April 2020. A compound Poisson generalized linear modeling (CPGLM), along with a Monte-Carlo method and random forest (RF) model, was employed to explore how meteorological factors affecting the COVID-19 transmission in Bangladesh. Results showed that subtropical climate (mean temperature about 26.6 ?C, mean relative humidity (MRH) 64%, and rainfall approximately 3 mm) enhanced COVD-19 onset. The CPGLM model revealed that every 1 mm increase in rainfall elevated by 30.99% (95% CI 77.18%, - 15.20%) COVID-19 cases, while an increase of 1 ?C of diurnal temperature (TDN) declined the confirmed cases by - 14.2% (95% CI 9.73%, - 38.13%) on the lag 1 and lag 2, respectively. In addition, NRH and MRH had the highest increase (17.98% (95% CI 22.5%, 13.42%) and 19.92% (95% CI: 25.71%, 14.13%)) of COVID-19 cased in lag 4. The results of the RF model indicated that TDN and AH (absolute humidity) influence the COVID-19 cases most. In the Dhaka division, MRH is the most vital meteorological factor that affects COVID-19 deaths. This study indicates the humidity and rainfall are crucial factors affecting the COVID-19 case, which is contrary to many previous studies in other countries. These outcomes can have policy formulation for the suppression of the COVID-19 outbreak in Bangladesh.

Keywords: Bangladesh; COVID-19; Compound Poisson generalized linear modeling (CPGLM); Meteorological factors; Random forest (RF); Time-series analysis.
 
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