Project: Health Infrastructure Effects on Pandemic: How COVID-19 cases are affected by poverty (Collaboration with Wellspan)
Student Researchers: Danielle Andrews, Rachel Copley, and Hala Nusair
Introduction & Background
“Pennsylvania has been challenged by its Department of Health infrastructure, which does not include County Health departments in every region. As a result, it is believed that efforts related to case investigation, contact tracing, and other disease management strategies have not been as effective in mitigating the impact of COVID-19. In order to test this theory, GIS is a perfect tool to accurately represent the trends in the spread of COVID-19. In the project, York county’s COVID cases were compared to counties that have a Health Department COVID cases. Confirmed case data poverty data was included to determine if poverty affects the spread of the virus.”
Problem/Issue Statement
“Some counties in Pennsylvania, including York County, currently have no public health infrastructure and were not prepared to respond quickly to a global pandemic. This issue could be the reason why, in some counties, COVID-19 spreads more quickly.”
Hypothesis
“There will be more COVID-19 cases in areas where there is little to no health facilities/resources. Counties with a health department will also have less cases than a county with no health department. Areas with high poverty rates will have more COVID cases than areas with little to no poverty.”
Method
“Data was gathered from the federal Census Bureau, county Covid dashboards, and county GIS data portals for York County, Erie County, and Carroll County. For each county, the base county boundary layer was added as a feature class into ArcMap. Then the zip code boundary lines were added on top of the county boundary layer. To add the COVID-19 data, spreadsheets were created in excel using values taken from each states’ COVID-19 dashboard and converted into a table in ArcMap. Once in ArcMap, the COVID-19 table was then joined with the zip code data frame. This made it possible for the number of cases to be represented on the map. Poverty data was also collected and added to the map. Race data were also collected and added to a separate map. The race data was joined to the block group of its representative county.”
Conclusions
“As the country responds to COVID-19, the role of public health infrastructure in ensuring the delivery of equitable health care in rural communities has not been fully appreciated. The impact of such crises is exacerbated in rural racial/ethnic minority communities. Various elements contribute to the problems identified in rural areas, including a declining population, economic stagnation, shortages of physicians, and other health care providers. As well as a disproportionate number of older, poor, and underinsured residents. This project is a representation of the challenges faced by communities in addressing COVID-19 and other issues associated with it, people living in urban areas are at increased risk of COVID-19 because they are less likely to be employed and more likely to have low incomes than people living in other areas.
In the future, it would be beneficial to look into how COVID-19 case numbers are affected by the total population and how COVID-19 deaths and hospitalizations are affected by age groups.”