Dalal Arpita, Pandey Piyush
Department of Ecology and Environmental Science, Assam University, Silchar, 788011 India.
Department of Microbiology, Assam University, Silchar, 788011 India.
Environ Sustain (Singap). 2021;4(3):551-558. doi: 10.1007/s42398-021-00176-8. Epub 2021 May 17.
Weather variables are one of the crucial factors affecting respiratory infectious diseases; however, the effect of weather variables on the coronavirus disease 2019 (COVID-19) is still inconclusive and varies in different regions. The present study investigated the effects of weather variables (maximum temperature, MT; relative humidity, RH; wind speed, WS; precipitation, PR; and dew point, DP) on daily infection and death cases in three lockdown phases in Asia as of November 1, 2020. Generalized additive lag model was used to analyze the risk associated with weather variables, with confounders like median age of the national population, population density, country and lockdown phases. Our findings revealed that during lockdown phases all five weather variables show association with daily confirmed, and death cases. On the other hand, PR (pre-lockdown phase) and DP (lockdown phase) showed positive association with both daily confirmed and death cases. Throughout the three lockdown phases MT, RH and PR showed strong positive associations with daily confimed/death cases. A lag period of 0-4-days possess higher risk of infection and death due to the varied ratios of different weather variables. The relative risk indicated that the infection and mortality risk was higher in India as compared to the rest of the countries. Here, unique combination of weather variables together with higher population density makes this region as one of the hotspots for COVID-19. This shows that the COVID-19 pandemic may be suppressed or enhanced with combination of different weather conditions together with factors like population density and median age of the country, which shall be useful for better implementation of health policies and further preparedness in Asia.
The online version contains supplementary material available at 10.1007/s42398-021-00176-8.
气象变量是影响呼吸道传染病的关键因素之一;然而,气象变量对2019冠状病毒病(COVID-19)的影响仍无定论,且在不同地区有所不同。本研究调查了截至2020年11月1日气象变量(最高温度、相对湿度、风速、降水量和露点)对亚洲三个封锁阶段每日感染和死亡病例的影响。使用广义相加滞后模型分析与气象变量相关的风险,并考虑国家人口中位数年龄、人口密度、国家和封锁阶段等混杂因素。我们的研究结果显示,在封锁阶段,所有五个气象变量均与每日确诊病例和死亡病例相关。另一方面,降水量(封锁前阶段)和露点(封锁阶段)与每日确诊病例和死亡病例均呈正相关。在整个三个封锁阶段,最高温度、相对湿度和降水量与每日确诊/死亡病例呈强正相关。由于不同气象变量的比例不同,0至4天的滞后期具有更高的感染和死亡风险。相对风险表明,与其他国家相比,印度的感染和死亡风险更高。在这里,气象变量的独特组合以及较高的人口密度使该地区成为COVID-19的热点地区之一。这表明,COVID-19大流行可能会因不同天气条件与人口密度和国家中位数年龄等因素的组合而受到抑制或加剧,这将有助于在亚洲更好地实施卫生政策和进一步做好准备。
在线版本包含可在10.1007/s42398-021-00176-8获取的补充材料。