Probabilistic Assessment of the Interaction between Weather, COVID-19 and Exchange rate of Mumbai City in India using Archimedean Copulas

Abstract Coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented health crisis across the world. When there is no specific solution available to tackle the pandemic, there is an urgency to know the pertinent factors like weather and its interaction with the number of daily cases and impact on the economy. The purpose of this investigation is to determine the probabilistic assessment of mean temperature and relative humidity on the number of COVID-19 infected cases and its effect on the Indian Rupees (INR) exchange rate against US dollar for the city of Mumbai. The bivariate Archimedean copulas were applied to assess the conditional probability of the number of cases given mean daily temperature and relative humidity and also the conditional probability of INR exchange rate given the number of daily new cases. Though the number of cases and mean temperature are positively correlated, but the maximum probability of occurrence is just about 20% for Tmean < = 30ºC, 35ºC in the interval of 101–200 cases. The pattern of the likelihood of occurrence of the number of COVID-19 cases to the mean relative humidity is similar to that of the mean daily temperature except for RHmean < = 45% when the probability is almost negligible while moving from one interval to another of the number of cases. The maximum probability of occurrence is about 20% for RHmean < = 75% in the interval of 101–200 cases. Our results also reveal that the probability of occurrence of the Indian rupee depreciating to INR 76–77 range remained high, irrespective of the number of cases. A note of caution is that these conditional probability figures are not the absolute probable of occurrence, rather a percentage change of the conditional probability while moving from lower end to higher end values for a given interval.