Sangkham Sarawut, Islam Md Aminul, Sarndhong Kritsada, Vongruang Patipat, Hasan Mohammad Nayeem, Tiwari Ananda, Bhattacharya Prosun
Department of Environmental Health, School of Public Health, University of Phayao, Phayao, 56000, Thailand.
COVID-19 Diagnostic Lab, Department of Microbiology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
Case Stud Chem Environ Eng. 2023 Jun 22:100410. doi: 10.1016/j.cscee.2023.100410.
The ongoing global pandemic caused by the SARS-CoV-2 virus, known as COVID-19, has disrupted public health, businesses, and economies worldwide due to its widespread transmission. While previous research has suggested a possible link between environmental factors and increased COVID-19 cases, the evidence regarding this connection remains inconclusive. The purpose of this research is to determine whether or not there is a connection between the presence of fine particulate matter (PM) and meteorological conditions and COVID-19 infection rates in Bangkok, Thailand. The study employs a statistical method called Generalized Additive Model (GAM) to find a positive and non-linear association between RH, AH, and R and the number of verified COVID-19 cases. The impacts of the seasons (especially summer) and rainfall on the trajectory of COVID-19 cases were also highlighted, with an adjusted R-square of 0.852 and a deviance explained of 85.60%, both of which were statistically significant ( < 0.05). The study results assist in preventing the future seasonal spread of COVID-19, and public health authorities may use these findings to make informed decisions and assess their policies.
由严重急性呼吸综合征冠状病毒2（SARS-CoV-2）引发的全球大流行（即2019冠状病毒病），因其广泛传播而扰乱了全球的公共卫生、商业和经济。虽然此前的研究表明环境因素与2019冠状病毒病病例增加之间可能存在联系，但有关这种关联的证据仍无定论。本研究的目的是确定泰国曼谷细颗粒物（PM）的存在、气象条件与2019冠状病毒病感染率之间是否存在关联。该研究采用一种名为广义相加模型（GAM）的统计方法，以发现相对湿度（RH）、绝对湿度（AH）和降雨量（R）与确诊的2019冠状病毒病病例数之间存在正相关和非线性关联。研究还强调了季节（尤其是夏季）和降雨对2019冠状病毒病病例轨迹的影响，调整后的决定系数R平方为0.852，偏差解释率为85.60%，两者均具有统计学意义（P＜0.05）。研究结果有助于预防2019冠状病毒病未来的季节性传播，公共卫生当局可利用这些发现做出明智决策并评估其政策。
