COVID-19 Analysis
Coronavirus disease 2019, or COVID-19, is an illness that affects the respiratory system of individuals. It is believed that the virus emerged from an animal source, but it now spreads by human contact. Severe complications from COVID-19 include pneumonia, multi-organ failure and death. The spread of this virus is now prevalent over the world and its outbreak has been declared a pandemic by the World Health Organization (WHO).
Four models were created using supervised machine learning to analyze the relationship between the number of confirmed cases and the number of deaths/recovered cases for all countries, as well as the relationship between deaths and gender. Using linear regression and calculating the R-squared score, the relationship between these values was determined.
Comparison of Deaths by Gender for Countries:
1. China 2. France 3. Germany 4. Iran 5. Italy and 6. Spain
Machine Learning Models
• The first model calculates the relationship between the number of confirmed cases and number of deaths for 176 countries. The R-squared score for this first model is 0.653.
• The second model calculates the relationship between the number of confirmed cases and number of recovered cases for the same 176 countries. The R-squared score for the second model is 0.372. This can be due to the lack of testing to confirm that poeple have recovered. Therefore, the number of confirmed cases increases daily, but the number of recovered cases does not.
• The third model determines the relationship between female deaths and total deaths for countries China, France, Germany, Iran, Italy and Spain, as these are the countries with the highest numbers. The R-squared score for this model is 0.977.
• The fourth model determines the relationship between male deaths and total deaths for the same five countries. The R-squared score for the fourth model is 0.996, showing that coronavirus deaths are more prevalent among the male population.