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                <text>Coronavirus</text>
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                <text>Dominio científico: Coronavirus</text>
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              <text>Societal and economic factors associated with COVID-19 indicate that developing countries could suffer the most</text>
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              <text>Alessandro Maria Selvitella, Kathleen Lois Foster</text>
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              <text>Most of the research related to the COVID-19 pandemic deals with the biological and epidemiological factors which have driven the spread of the coronavirus around the globe. In this paper, we analyse how societal and economic variates relate to the number of cases and deaths across countries, via machine learning methods. Our findings recommend focusing our attention on  developing  countries  where  the  healthcare  system might suffer the most.</text>
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              <text>2020</text>
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              <text>covid-19, LASSO, variable selection, socioeconomic determinants, explainability</text>
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              <text>Epidemiology and Health</text>
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              <text>Korean Society of Epidemiology</text>
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              <text>Social sciences (General)</text>
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