Hasan Mohammad Nayeem, Islam Md Aminul, Sangkham Sarawut, Werkneh Adhena Ayaliew, Hossen Foysal, Haque Md Atiqul, Alam Mohammad Morshad, Rahman Md Arifur, Mukharjee Sanjoy Kumar, Chowdhury Tahmid Anam, Sosa-Hernández Juan Eduardo, Jakariya Md, Ahmed Firoz, Bhattacharya Prosun, Sarkodie Samuel Asumadu
Department of Statistics, Shahjalal University of Science & Technology, Sylhet, Bangladesh.
Joint Rohingya Response Program, Food for the Hungry, Cox's Bazar, Bangladesh.
Groundw Sustain Dev. 2023 May;21:100932. doi: 10.1016/j.gsd.2023.100932. Epub 2023 Mar 2.
The ongoing COVID-19 contagious disease caused by SARS-CoV-2 has disrupted global public health, businesses, and economies due to widespread infection, with 676.41 million confirmed cases and 6.77 million deaths in 231 countries as of February 07, 2023. To control the rapid spread of SARS-CoV-2, it is crucial to determine the potential determinants such as meteorological factors and their roles. This study examines how COVID-19 cases and deaths changed over time while assessing meteorological characteristics that could impact these disparities from the onset of the pandemic. We used data spanning two years across all eight administrative divisions, this is the first of its kind--showing a connection between meteorological conditions, vaccination, and COVID-19 incidences in Bangladesh. We further employed several techniques including Simple Exponential Smoothing (SES), Auto-Regressive Integrated Moving Average (ARIMA), Auto-Regressive Integrated Moving Average with explanatory variables (ARIMAX), and Automatic forecasting time-series model (Prophet). We further analyzed the effects of COVID-19 vaccination on daily cases and deaths. Data on COVID-19 cases collected include eight administrative divisions of Bangladesh spanning March 8, 2020, to January 31, 2023, from available online servers. The meteorological data include rainfall (mm), relative humidity (%), average temperature (°C), surface pressure (kPa), dew point (°C), and maximum wind speed (m/s). The observed wind speed and surface pressure show a significant negative impact on COVID-19 cases (-0.89, 95% confidence interval (CI): 1.62 to -0.21) and (-1.31, 95%CI: 2.32 to -0.29), respectively. Similarly, the observed wind speed and surface pressure show a significant negative impact on COVID-19 deaths (-0.87, 95% CI: 1.54 to -0.21) and (-3.11, 95%CI: 4.44 to -1.25), respectively. The impact of meteorological factors is almost similar when vaccination information is included in the model. However, the impact of vaccination in both cases and deaths model is significantly negative (for cases: 1.19, 95%CI: 2.35 to -0.38 and for deaths: 1.55, 95%CI: 2.88 to -0.43). Accordingly, vaccination effectively reduces the number of new COVID-19 cases and fatalities in Bangladesh. Thus, these results could assist future researchers and policymakers in the assessment of pandemics, by making thorough efforts that account for COVID-19 vaccinations and meteorological conditions.
由严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引起的持续的2019冠状病毒病已扰乱全球公共卫生、商业和经济,原因是感染广泛传播,截至2023年2月7日,231个国家有6.7641亿确诊病例和677万死亡病例。为控制SARS-CoV-2的快速传播,确定诸如气象因素等潜在决定因素及其作用至关重要。本研究考察了2019冠状病毒病病例和死亡人数随时间的变化情况,同时评估了自大流行开始以来可能影响这些差异的气象特征。我们使用了跨越两年的所有八个行政区的数据,这是同类研究中的首例——显示了孟加拉国气象条件、疫苗接种与2019冠状病毒病发病率之间的联系。我们还采用了多种技术,包括简单指数平滑法(SES)、自回归积分移动平均法(ARIMA)、带解释变量的自回归积分移动平均法(ARIMAX)和自动预测时间序列模型(Prophet)。我们进一步分析了2019冠状病毒病疫苗接种对每日病例和死亡人数的影响。收集的2019冠状病毒病病例数据包括孟加拉国八个行政区从2020年3月8日至2023年1月31日的数据,来自可用的在线服务器。气象数据包括降雨量(毫米)、相对湿度(%)、平均温度(摄氏度)、地面气压(千帕)、露点(摄氏度)和最大风速(米/秒)。观测到的风速和地面气压分别对2019冠状病毒病病例(-0.89,95%置信区间(CI):1.62至-0.21)和(-1.31,95%CI:2.32至-0.29)显示出显著的负面影响。同样,观测到的风速和地面气压分别对2019冠状病毒病死亡人数(-0.87,95%CI:1.54至-0.21)和(-3.11,95%CI:4.44至-1.25)显示出显著的负面影响。当模型中纳入疫苗接种信息时,气象因素的影响几乎相似。然而,疫苗接种在病例和死亡人数模型中的影响均为显著负面(病例:1.19,95%CI:2.35至-0.38;死亡人数:1.55,95%CI:2.88至-0.43)。因此,疫苗接种有效地减少了孟加拉国新增2019冠状病毒病病例和死亡人数。因此,这些结果可为未来研究人员和政策制定者评估大流行提供帮助,通过全面考虑2019冠状病毒病疫苗接种和气象条件来做出深入努力。