The Use of Decision Trees for Analysis of the Potential Determinants for the Incidence of Deaths and Cases of Coronavirus (Covid-19) in Different Countries

Joanna Wyrobek
European Research Studies Journal, Volume XXIII, Special Issue 3, 556-566, 2020
DOI: 10.35808/ersj/1945


Purpose: The objective of this paper is to identify the key economic factors determining the intensity of COVID virus infections and deaths in various countries. Design/Methodology/Approach: The publication uses the methods of k-means clustering, k-nearest neighbors algorithm, DBSCan algorithm to divide countries into different groups in terms of the level of disease and death from COVID. The decision tree analysis provided potential determinants for the severity of the pandemic in different regions of the world. We analyzed 211 countries. As potential determinants, we examined the following factors: average temperature, average precipitation, GDP per capita, population density (in 2018), hospital beds per 1.000 citizens, doctors per 1.000 citizens, share of people aged 65 years or above, pollution (based on the PM2.5 indicator from The World Bank), total tests per 1.000 citizens and health expenditure as a percentage of GDP. Findings: Our analysis revealed that the COVID pandemic intensity in analyzed countries depends on the number of doctors, population density, average temperature, total tests per 1.000 citizens, and GDP per capita by using data from the World Bank. Practical Implications: Research suggests that the efficient healthcare system supports immunological response of population to the COVID virus. Another critical factor is the density of population. These two factors proved to play a critical role in determining the level of the COVID cases in deaths in various countries. Nevertheless, countries with the lowest GDP per capita had very low levels of COVID cases, which suggests that either they do not recognize COVID patients correctly or they will experience the pandemic with time delay. Originality/value: Economic factors proved to be good predictors of the COVID virus development in the analyzed countries, however, contrary to expectations, countries with low GDP per capita so far suffered the least from the COVID virus pandemic.

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