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Our task is to examine the relationship between the SARS-CoV-2 arrival and the number of confirmed COVID-19 cases in the first wave (period from March 4 to May 22, 2020 (unofficial data)), and socio-economic variables at the powiat (county) level (NUTS-4) using simple statistical techniques such as data visualization, correlation analysis, spatial clustering and multiple linear regression. We showed that immigration and the logarithm of general mobility is the best predictor of SARS-CoV-2 arrival times, while emigration, industrialization and air quality explain the most of the size of the epidemic in poviats. On the other hand, infection dynamics is driven to a lesser extent by previously postulated variables such as population size and density, income or the size of the elderly population. Our analyses could support Polish authorities in preparation for the second wave of infections and optimal management of resources as we have provided a proposition of optimal distribution of human resources between poviats.
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?:doi
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10.1101/2020.10.14.20090985
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document_parses/pdf_json/ae27cfdd3c9af7faba38c4cfc6016638e4867545.json
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An attempt to optimize human resources allocation based on spatial diversity of COVID-19 cases in Poland
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