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Assessing the Relationship between COVID-19, Air Quality, and Meteorological Variables: A Case Study of Dhaka City in Bangladesh

Md Sariful Islam, Mizanur Rahman, Tanmoy Roy Tusher, Shimul Roy, Mohammad Arfar Razi

2021Aerosol and Air Quality Research23 citationsDOIOpen Access PDF

Abstract

The novel coronavirus disease 2019 (COVID-19) has become a serious health concern worldwide for almost a year. This study investigated the effects of selected air pollutants and meteorological variables on daily COVID-19 cases in Dhaka city, Bangladesh. Air pollutants and meteorological data for Dhaka city were collected from 8 April to 16 June 2020 from multiple sources. This study implied spearman’s correlation to see the correlation between daily COVID-19 cases and different air pollutants and meteorological variables. Besides, multiple linear regression and the Generalized Additive Model (GAM) were used to investigate the association between COVID-19 cases and other variables used in this study. Due to lockdown measures, significant differences between PM2.5, SO2, NO2, CO, and O3 in 2019 and 2020 were observed in Dhaka city. We used lag-0, lag-7, lag-14, and lag-21 days on daily COVID-19 cases to look at the lag effect of different air pollutants and meteorology. The LRM results showed that the daily COVID-19 cases are significantly correlated with relative humidity (lag-0 days) and pressure (lag-14 days) (p < 0.05). Additionally, the GAM model results showed a significant nonlinear association among daily COVID-19 cases and meteorology and air quality variables on different lag days. Therefore, our results suggest that an effective public health intervention measures should be implemented to slowdown the spreading of COVID-19.

Topics & Concepts

LagCoronavirus disease 2019 (COVID-19)Distributed lagAir quality indexGeneralized additive modelAir pollutantsEnvironmental scienceEnvironmental healthLag timeRelative humidityMeteorologyRegression analysisLinear regressionAir pollutionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Time lagPublic healthGeographyStatisticsMedicineMathematicsDiseaseInfectious disease (medical specialty)BiologyEcologyComputer networkPathologyNursingBiological systemComputer scienceCOVID-19 impact on air qualityCOVID-19 epidemiological studiesCOVID-19 Pandemic Impacts
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