In December of 2019 COVID-19 appeared in China, which quickly spread across whole world and completely paralyzed public life and traffic, even in Slovenia. In this thesis, we analyze correlation between epidemic, government measures, population mobility and traffic. We found out it affected air traffic and public traffic the most as they were restricted by measures. High correlations, especially with measures, were also with car traffic. Wilcoxon signed-rank test confirmed fall in numbers of cars detected. Measures moved the start of motorcycling season, but no other significant effect was seen. The lowest correlation calculated was with freight transport, which still supplied the economy even during the epidemic. Correlation between population mobility and measures was high again in most categories. Movement was higher only in residential buildings. As opposed to Google data, Apple data showed similar correlations of population mobility with measures and number of infections respectively. As with others, big influence of epidemic on driving and walking was noticeable. While comparing navigation requests data with road traffic we came to conclusion that navigation is used the most by car and motorcycle drivers and least by drivers of freight trucks. Analysis source code is available in public repository just like presentation of results in a form of web page.
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