Awasthi Amit, Sharma Aditi, Kaur Prabhjot, Gugamsetty Balakrishnaiah, Kumar Akshay
Department of Physics, University of Petroleum and Energy Studies, Dehradun, UK 248007 India.
Department of Petroleum Engineering and Earth Sciences, University of Petroleum and Energy Studies, Dehradun, UK India.
Environ Dev Sustain. 2021;23(6):8147-8160. doi: 10.1007/s10668-020-01000-9. Epub 2020 Sep 25.
The novel coronavirus disease is known as COVID-19, which is declared as a pandemic by the World Health Organization during March 2020. In this study, the COVID-19 connection with various weather parameters like temperature, wind speed, and relative humidity is investigated and the future scenario of COVID-19 is predicted based on the Gaussian model (GM). This study is conducted in Delhi, the capital city of India, during the lowest mobility rate due to strict lockdown nationwide for about two months from March 15 to May 17, 2020. Spearman correlation is applied to obtain the interconnection of COVID-19 cases with weather parameters. Based on statistical analysis, this has been observed that the temperature parameter shows a significant positive trend during the period of study. The number of confirmed cases of COVID-19 is fitted with respect to the number of days by using the Gaussian curve and it is estimated on the basis of the model that maximum cases will go up to 123,886 in number. The maximum number of cases will be observed during the range of 166 ± 36 days. It is also estimated by using the width of the fitted GM that it will take minimum of 10 months for the complete recovery from COVID-19. Additionally, the linear regression technique is used to find the trend of COVID-19 cases with temperature and it is estimated that with an increase in temperature by 1 °C, 30 new COVID-19 cases on daily basis will be expected to observe. This study is believed to be a preliminary study and to better understand the concrete relationship of coronavirus, at least one complete cycle is essential to investigate. The laboratory-based study is essential to be done to support the present field-based study. Henceforth, based on preliminary studies, significant inputs are put forth to the research community and government to formulate thoughtful strategies like medical facilities such as ventilators, beds, testing centers, quarantine centers, etc., to curb the effects of COVID-19.
新型冠状病毒病被称为COVID-19，2020年3月世界卫生组织宣布其为大流行病。在本研究中，调查了COVID-19与诸如温度、风速和相对湿度等各种天气参数的关联，并基于高斯模型（GM）预测了COVID-19的未来情况。本研究于2020年3月15日至5月17日在印度首都德里进行，当时由于全国范围内严格封锁约两个月，人员流动率处于最低水平。应用斯皮尔曼相关性来获取COVID-19病例与天气参数之间的相互联系。基于统计分析，观察到在研究期间温度参数呈现出显著的正趋势。通过使用高斯曲线将COVID-19确诊病例数与天数进行拟合，并根据该模型估计，病例数最多将增至123,886例。病例数最多将在166±36天的范围内出现。通过拟合的GM宽度还估计，从COVID-19完全康复至少需要10个月。此外，使用线性回归技术来找出COVID-19病例数随温度的变化趋势，估计温度每升高1°C，预计每天将新增30例COVID-19病例。本研究被认为是一项初步研究，为了更好地理解冠状病毒的具体关系，至少进行一个完整周期的调查是必不可少的。必须开展基于实验室的研究以支持当前基于实地的研究。此后，基于初步研究，向研究界和政府提出了重要意见，以制定周全的策略，如配备呼吸机、床位、检测中心、隔离中心等医疗设施，以遏制COVID-19的影响。
