Impact of Climate on Confirmed Cases of COVID-19 in Lahore: A Predictive Model: COVID-19: A Predictive Model - Manzoor, Farkhanda; Sharif, Saima (Proceedings of the Pakistan Academy of Sciences: B. Life and Environmental Sciences, 2021)
World over, the weather conditions are usually categorized as predictors of respiratory viral infections. This study uses a stepwise linear regression model to explore the effects of climate factors or weather factors such as temperature, humidity, wind speed on the spread of COVID-19 in Lahore city (Pakistan). The study was conducted in Lahore College for Women University, Lahore, and the data regarding the cases of COVID-19 in the Lahore district was obtained from the Primary and Secondary Health Care Department Punjab, from 18th March 2020 to 25th August 2020 while the weather statistics were obtained from Environmental Protection Department, Lahore. A predictive model by regression was designed in which day-to-day humidity, wind speed, average temperature, and their impact on confirmed cases of COVID-19 in Lahore were analyzed. The independent variables in the model were average temperature (C), humidity (%), wind (km/h) and the dependent variable was the number of daily established cases of COVID in Lahore. The result of the analysis shows the effectiveness of the proposed model and the impact of climate parameters on the assessment model. The study illustrates that the above model can be used to predict the future spread of COVID-19 based on the above-mentioned climate factors. As such, it proves as a useful modality to predict new cases for the government and other health agencies.