Kaur Satinder, Bherwani Hemant, Gulia Sunil, Vijay Ritesh, Kumar Rakesh
CSIR-National Environmental Engineering Research Institute, Mumbai, Maharashtra 400018 India.
CSIR-National Environmental Engineering Research Institute, Nagpur, Maharashtra 440020 India.
Environ Dev Sustain. 2021;23(5):6681-6697. doi: 10.1007/s10668-020-00884-x. Epub 2020 Jul 18.
COVID-19 is a highly infectious disease caused by SARS-CoV-2, first identified in China and spread globally, resulting into pandemic. Transmission of virus takes place either directly through close contact with infected individual (symptomatic/asymptomatic) or indirectly by touching contaminated surfaces. Virus survives on the surfaces from few hours to days. It enters the human body through nose, eyes or mouth. Other sources of contamination are faeces, blood, food, water, semen etc. Parameters such as temperature/relative humidity also play an important role in transmission. As the disease is evolving, so are the number of cases. Proper planning and restriction are helping in influencing the trajectory of the transmission. Various measures are undertaken to prevent infection such as maintaining hygiene, using facemasks, isolation/quarantine, social/physical distancing, in extreme cases lockdown (restricted movement except essential services) in hot spot areas or throughout the country. Countries that introduced various mitigation measures had experienced control in transmission of COVID-19. Python programming is conducted for change point analysis (CPA) using Bayesian probability approach for understanding the impact of restrictions and mitigation methods in terms of either increase or stagnation in number of COVID-19 cases for eight countries. From analysis it is concluded that countries which acted late in bringing in the social distancing measures are suffering in terms of high number of cases with USA, leading among eight countries analysed. The CPA week in comparison with date of lockdown and first reported case strongly correlates (Pearson's = - 0.86 to - 0.97) to cases, cases per unit area and cases per unit population, indicating earlier the mitigation strategy, lesser the number of cases. The overall paper will help the decision makers in understanding the possible steps for mitigation, more so in developing countries where the fight against COVID-19 seems to have just begun.
新冠肺炎是一种由严重急性呼吸综合征冠状病毒2（SARS-CoV-2）引起的高传染性疾病，最早在中国被发现并在全球传播，从而导致了大流行。病毒的传播要么是通过与受感染个体（有症状/无症状）密切接触直接发生，要么是通过接触受污染的表面间接发生。病毒在表面可存活数小时至数天。它通过鼻子、眼睛或嘴巴进入人体。其他污染来源包括粪便、血液、食物、水、精液等。温度/相对湿度等参数在传播中也起着重要作用。随着疾病的演变，病例数量也在变化。适当的规划和限制有助于影响传播轨迹。人们采取了各种措施来预防感染，如保持卫生、使用口罩、隔离/检疫、社交/物理距离，在极端情况下，在热点地区或全国范围内实施封锁（除基本服务外限制行动）。采取了各种缓解措施的国家在新冠肺炎传播控制方面取得了成效。使用贝叶斯概率方法进行Python编程以进行变点分析（CPA），以了解限制措施和缓解方法对八个国家新冠肺炎病例数量增加或停滞的影响。从分析中得出结论，在实施社交距离措施方面行动较晚的国家，如美国，在八个分析国家中病例数最多，正为此所苦。与封锁日期和首例报告病例相比，CPA周与病例数、单位面积病例数和单位人口病例数密切相关（皮尔逊相关系数为-0.86至-0.97），这表明缓解策略实施得越早，病例数就越少。整篇论文将有助于决策者了解可能的缓解措施，对于抗击新冠肺炎的斗争似乎才刚刚开始的发展中国家来说更是如此。
