We are particularly interested in what percentage
of COVID-19 cases are clustered in highly dense populations and lower-incomes—compared to
less dense areas and higher-income groups. This initial data set will give us a glimpse into the
total percentages while we dive deeper into understanding how symptoms vary in different
socioeconomic groups.
Question we are curious about:
● Knowing that population density and poverty positively correlate with COVID-19
cases, what are steps that society or the government can take to prevent these
disparities?
● If population density does not aggravate the conception of COVID-19, how does the
early intervention of crisis flatten the curve?
● How accurate can reporting be in lower-income communities if they have less
access to medical care and are less likely to be tested for the novel Coronavirus?
● Does income and population density correlate to symptoms felt by COVID-19
positive patients, either symptomatic or asymptomatic?