An Investigation into the Relationship Between Malarious Countries and COVID-19 Cases

Studies have shown that a negative correlation may exist between the number of COVID-19 cases and the incidence of malaria. This relationship is important, as it can provide valuable insight into potential treatments of the virus. To further investigate the correlation, 66 other factors (such as country demographic, GDP per capita, Health Index etc.) were examined. Open source data-sets were collected online from institutions such as the John Hopkins Coronavirus Resource Center and analyzed using various Python libraries. By calculating various correlation coefficients, it was determined that the number of tests conducted, air traffic and other several other factors correlated with COVID-19 cases, and may be responsible for the lower number of COVID-19 cases instead. To further strengthen the results, a machine learning model was constructed to evaluate the most relevant factors contributing to the transmission of COVID-19. Here, malaria was not deemed as an important feature. Instead, factors such as climate and country wealth were most important. A mixture of statistics and machine learning helped show that various factors unrelated to malaria may be responsible for the lower occurrence of COVID-19 in malarious countries, and while this is not enough to prove causation, it makes it likely that the correlation between COVID-19 and the Plasmodium parasite is spurious.

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