Air Pollution and Temperature in the Prediction of Covid-19

Abstract

Air pollution is the major problem all around the world, it can harm our air track and cause irritation, shortness of breath, coughing, wheezing and put our life risk at lung cancer, heart attack, and respiratory diseases. Temperature also associates with the lung problems which induces the changes in the characteristics of covid-19. Covid-19 is an ongoing pandemic spreads across the world which affects 50 million and causes 1 million deaths. It is caused by the strain of severe acute respiratory syndrome (SARS). Air pollutants can contribute in the affecting, recovery and mortality rate of covid-19.Collecting data’s of air pollutant’s like CO, NO, PM_2.5, PM₁₀, AQI and corona virus affected, recovery and death cases from various resources.We are using the Jupiter lab platform in anaconda software. Two types of predictions are made by each of the models, such as the number of deaths, and the number of recovery cases. The outcomes delivered by the analysis shows it a promising instrument to utilize these strategies for the current situation of the Corona virus pandemic. The results conclude that the Random Forest Regression performs fine among all the used models followed by Linear Regression and LASSO which performs well in forecasting the death rate as well as recovery.