Abstract
Aiming at the Covid-19 pandemic problem, to find out whether the climate factors could affect the development of pandemic, this paper mainly uses mathematical modeling and machine learning to analyze the correlation between climate factors and COVID-19 cases. Firstly, Weather conditions are classified by seasons, and cases differ in regions, then correlation results of different features are conduct to see what are the most important features that affect the pandemic, according to the correlation result, KNN model is used for predicting the future COVID-19 cases including potential danger zones. In order to test the effectiveness of the methods utilized in this paper, real climate data and covid-19 cases data of different regions in USA are deployed, the results show that, the temperature plays an important role in the pandemic, and the KNN method could predict the future development of Covid-19 with R square reached 0.25, which verifies the effectiveness of the machine learning method.
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