Social Determinants of Health
Individual lifestyles and societal influence happen to play a vital role in the spread rate of COVID-19.
This research identifies those specific social determinants of health that have the largest effect on the spread of COVID-19, including income, commute time, traffic volume, and associations.
Employers can use this data, in combination with the above risk models, to customize return-to-work policies for different regional socio-economic needs.
Click on the map to see an interactive version that shows the SDOH score and rank for each county.
Research shows that low-income, high population density, and longer commute factors contribute toward a higher spread rate for the disease.
Census data, the main source for population health data, along with COVID-19 case data was transformed and synthesized to create a matrix for each county. After multiple rounds of testing—continuously adjusting in each iteration—we successfully established a relationship between COVID-19 incidence and social determinants of health. From there, we created a set-up that is optimized for COVID-19 and fits all the SDOH variables with the spread of COVID-19.
A few variables were found to explain the spread of infection with a high degree of confidence. These select variables were quantified and combined to generate a score. The scores were then applied in a ranking of each county. It was concluded that counties that have a high rank and are considered to have poorer social determinants of health are experiencing a higher rate of COVID-19 cases.