Demystifying a possible relationship between COVID-19, air quality and meteorological factors: Evidence from Kuala Lumpur, Malaysia
Air pollution is the culprit to yearly millions of deaths worldwide, deteriorating human health. What is not yet clear is the impact of environmental factors on susceptibility to getting infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The study aimed to determine associations between air quality, meteorological factors, and COVID-19 cases in Kuala Lumpur, Malaysia. Air pollutants and meteorological data in 2018–2020 were obtained from the Department of Environment Malaysia, while daily new COVID-19 cases in 2020 were obtained from the Ministry of Health Malaysia. Data collected were statistically analyzed using the Statistical Package for Social Sciences (SPSS). There were significant differences between PM10, PM2.5, SO2, NO2, CO, O3, and solar radiation in 2019 and 2020 since movement control order (MCO) was implemented on 18 March 2020. Spearman’s correlation test showed that COVID-19 cases were positively correlated with PM10 (r = 0.131, p < 0.001), PM2.5 (r = 0.151, p < 0.001), SO2 (r = 0.091, p = 0.003), NO2 (r = 0.228, p < 0.001), CO (r = 0.269, p = 0.001), and relative humidity (RH) (r = 0.106, p = 0.001), whereas ambient temperature (AT) was negatively correlated with COVID-19 cases (r = –0.118, p < 0.001). Further, multiple linear regression suggested that NO2 and AT (R2 = 0.071, p < 0.001, f2 = 0.08) were the most significant air pollutant and meteorological factors with weak contribution that influenced the incidence of COVID-19 cases in Kuala Lumpur. In general, better air quality, lower RH, higher AT, along with the targeted approach implemented thus far, have proven to curb the spread of this virus infection in Malaysia. This study supports future research in studies documented to understand the potential of transmission, survival, and infection of SARS-CoV-2. © The Author(s).
Air quality; Linear regression; Meteorology; Nitrogen oxides; Viruses; Correlation tests; Environmental factors; Meteorological data; Meteorological factors; Movement control; Multiple linear regressions; Severe acute respiratory syndrome coronavirus; Statistical packages; Diseases; air quality; atmospheric pollution; environmental factor; health impact; mortality; public health; severe acute respiratory syndrome; viral disease; virus; Kuala Lumpur [West Malaysia]; Malaysia; West Malaysia; SARS coronavirus