Department of Mechanical Engineering, School of Engineering, Cochin University of Science and Technology, Kerala, 682022, India.
Diabetes Metab Syndr. 2020 Nov-Dec;14(6):1735-1742. doi: 10.1016/j.dsx.2020.09.002. Epub 2020 Sep 3.
Meteorological parameters play a major role in the transmission of infectious diseases such as COVID-19. In this study, we aim to analyze the correlation between meteorological parameters and COVID-19 pandemic in the financial capital of India, Mumbai.
In this research, we collected data from April 27 till July 25, 2020 (90 days). A Spearman rank correlation test along with two-tailed p test and an Artificial Neural Network (ANN) technique have been used to predict the associations of COVID-19 with meteorological parameters.
A significant correlation of COVID-19 was found with temperature (T), dew point (DP), relative humidity (RH, RH, RH) and surface pressure (P, P, P). The parameters which showed significant correlation were then taken for the modeling and prediction of COVID-19 infections using Artificial Neural Network technique.
It was found that the relative humidity and pressure parameters had the most influencing effect out of all other significant parameters (obtained from Spearman's method) on the active number of COVID-19 cases. The finding in this study might be useful for the public, local authorities, and the Ministry of Health, Govt. of India to combat COVID-19.
气象参数在传染病(如 COVID-19)的传播中起着重要作用。本研究旨在分析印度金融之都孟买的气象参数与 COVID-19 大流行之间的相关性。
在这项研究中,我们收集了 2020 年 4 月 27 日至 7 月 25 日(90 天)的数据。使用 Spearman 秩相关检验以及双尾 p 值检验和人工神经网络(ANN)技术来预测 COVID-19 与气象参数的关联。
COVID-19 与温度(T)、露点(DP)、相对湿度(RH、RH、RH)和地面气压(P、P、P)显著相关。然后,使用人工神经网络技术对具有显著相关性的参数进行建模和预测 COVID-19 感染。
研究发现,相对湿度和压力参数对 COVID-19 活跃病例数的影响最大,而其他显著参数(Spearman 方法获得)的影响相对较小。本研究的结果可能对公众、地方当局和印度政府卫生部抗击 COVID-19 具有一定的参考价值。