Correlation between Air and Urban Travelling with New Confirmed Cases of COVID-19 A Case Study
This provides insights for public health policymakers in managing pandemic spread through travel restrictions, but it is incremental as it applies existing regression methods to new data.
The study tackled the problem of understanding how inter-state and air travel correlate with new COVID-19 cases in Iran, achieving an 81% accuracy in showing a positive correlation between travel and infection rates.
COVID-19 which has spread in Iran from February 19, 2020, has infected 202,584 people and killed 9,507 people until June 20, 2020. The immediate suggested solution to prevent the spread of this virus was to avoid traveling around. In this study, the correlation between traveling between cities with new confirmed cases of COVID-19 in Iran is demonstrated. The data, used in the study, consisted of the daily inter-state traffic, air traffic data, and daily new COVID-19 confirmed cases. The data is used to train a regression model and voting was used to show the highest correlation between travels made between cities and new cases of COVID-19. Although the available data was very coarse and there was no detail of inner-city commute, an accuracy of 81% was achieved showing a positive correlation between the number of inter-state travels and the new cases of COVID-19. Consequently, the result suggests that one of the best ways to avoid the spread of the virus is limiting or eliminating traveling around.