  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.

Applications;Machine Learning