Analysis of Gender Differences in COVID-19
Date Issued
2022
Author(s)
Mitreska, Izabela
Simonoski, Oliver
Salkoski, Rasim
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.
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.
Subjects
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