Analysis of Gender Differences in COVID-19

Abstract

The Covid-19 pandemic epidemiological data should be provided by age and sex segments, according to the global health community, but this specification which is degraded by age and sex hardly reported. There is high importance in such information’s but also, they are essential for the population to make properly informed decisions regarding their personal illness risk, as well as for governments to construct public policy. Our paper aims to investigate the relationship and influence of the experimental design between the gender-specific Covid-19 infections and losses. To create short-term projections of the Covid-19 outbreak over time period, we set the following hypothesis: “As the spread of Covid-19 increased, the number of infected women also increases”. We have used R Studio as an integrated development environment for R to verify the accuracy of the hypothesis. The layout of the publication analyzes related ideas regarding the variations and effects of Covid-19 infections based on sex and gender. In order to estimate the evaluation of represented experimental design we used a dataset to demonstrate that women experience higher infection rates than male population. Determined through the calculation of essential statistical values we drawn conclusion that the male population had a higher death rate than the female population