Impact of Temperature, Humidity and Precipitation on the COVID-19 Cases: A Study Across all Provinces in Pakistan

Meteorological variables play a significant role in transmitting viruses like influenza and the coronavirus pandemic (COVID-19). Previous studies have identified the relationship between changes in meteorological variables, humidity, rainfall and temperature, and the infection rate of COVID-19 at the national level in Pakistan. However, the current study applied the logistic regression analysis technique to work out such a relationship at a more detailed scale, i.e., sub-national levels in addition to the national level in Pakistan, using long-term analysis of two years of COVID-19 data. For the sub-national level, the logistic regression analysis technique was applied with the infection rate as the predictive variable. The results have shown an increase in the infection rate of COVID-19 with an increase in the humidity level. Contrary to this, an increase in the temperature has slowed down the spread of COVID-19 cases at both national and sub-national levels. Temperature minimum was proven to be statistically significant (p<0.001) for both provinces, Punjab and Sindh. While only AJK witnessed statistically significant p-values for Humidity. At the national level, both Temperature maximum and Humidity have shown such values, i.e., p<0.001. We believe that this is the first study conducted in Pakistan which has explored the direct and indirect relationship between variables like temperature (min. and max.), humidity, and rainfall as the predictive parameters for the infection rate of COVID-19 cases at the detailed level. The pattern observed in this study can help observe the future spreading of COVID-19 cases subject to the climatic parameters in Pakistan at both the national and sub-national levels.