Examining the correlation between the weather conditions and COVID-19 pandemic in India: A mathematical evidence

Abstract

In this article, for the analysis of Covid-19 progression in India, we present new insights to formulate a data-driven epidemic model and approximation algorithm using the real data on infection, recovery and death cases with respect to weather in the view of mathematical variables.

Stochastic analysis of the relationship between atmospheric variables and coronavirus disease (COVID‐19) in a hot, arid climate

“…Studies conducted in 2020 investigated the correlation between the weather or climate variables (e.g., temperature, humidity, wind speed, visibility, rain, and solar radiation) and the number of COVID‐19 cases. Several of these studies have concentrated on different cities and countries around the world, for example, the United States and Europe (Bukhari & Jameel, 2020 ; Gharoie Ahangar et al, 2020 ), Africa (Adekunle et al, 2020 ), Russia (Lasisi and Eluwole, 2021 ), Wuhan, China (Ma et al, 2020 ), 122 cities in China (Xie & Zhu, 2020 ), India (Awasthi et al, 2020 ; Borah et al, 2020 ; Gupta, Pradhan, et al, 2020 ), Jakarta, Indonesia (Tosepu et al, 2020 ), Pakistan (Aslam et al, 2020 ), Brazil (Aule et al, 2020 ; Pequeno et al, 2020 ), Iran (Ahmadi et al, 2020 ). Preliminary studies that found no relationship between COVID‐19 transmission and atmospheric variables (e.g., temperature) were performed by Xie and Zhu ( 2020 ), Gupta, Raghuwanshi, et al ( 2020 ), and Yao et al ( 2020 ).…”

Mathematical analysis and simulation of a stochastic COVID-19 Lévy jump model with isolation strategy

“…For instance, the risk estimation, the infection evolution and the prediction of COVD-19 infection is studied [25] , [26] , [27] , [28] ; the authors concludes that for ensuring a quick ending of the epidemic, the interventions strategy and self-protection measures should always be maintained. The meteorological role and policy measures on COVD-19 spread were studied in [29] , [30] ; it was concluded that the policy strategy has reduced the infection and the meteorological role can be considered as an important factor in controlling COVID-19. The effect of quarantine on coronavirus was discussed in [31] ; the results confirm the importance of reducing contact between the infected and other individuals.…”

Analysis of Atangana–Baleanu fractional-order SEAIR epidemic model with optimal control

“…An epidemic stochastic mathematical model with integer order is used to predict the spread of coronavirus in [ 8 ]. A mathematical model is used to study correlation between the weather conditions and the COVID-19 pandemic in India by Borah et al [ 9 ].…”