Targeting COVID-19 Health Disparities With Data Analytics

The COVID-19 pandemic has brought to light existing health disparities, especially among Black, Latinx, and other underrepresented populations. Using data analytics, Indiana’s Marion County Public Health Department created strategies to address disparities in COVID-19 testing and improve health equality.

COVID-19 is spread easily between individuals. As the Centers for Disease Control and Prevention (CDC) tracks the spread of COVID-19, they also evaluate how likely people are to be exposed to the illness through community transmission.

To evaluate the level of community transmission, the CDC examines the total new cases reported over the last seven days per 100,000 residents and the percentage of positive COVID-19 tests reported in the county of the past seven days.

Marion County health leaders used a dashboard created by Regenstrief Institute, Indiana Health Information Exchange (IHIE), and other members of the Indiana Pandemic Information Collaborative (IPIC) to identify communities with the highest disease burden.

Using this data, health officials set up test sites in areas that were easily accessible to the community population to assist in mitigating the spread of the virus.

“Given the novel and dynamic nature of the pandemic, we based resource allocation decisions on assessments of multiple COVID-19 disease statistics and trends rather than predefined criteria. This allowed us to reach those most affected,” Marion County Public Health Department director Virginia Caine, MD, said in a press release.

“We worked with community partners to identify and address challenges related to COVID testing to increase access.”

According to data analysis, the rate of new cases decreased in the targeted populations after the testing locations and associated informational campaigns were established.

“Populations at highest risk of disease should receive extra resources from local health departments,” said Brian Dixon, PhD, MPA, Regenstrief Institute and Indiana University Richard M. Fairbanks School of Public Health director of public health informatics.

“Using surveillance data helps identify which populations are being marginalized and guides health leaders in targeting those groups. Monitoring inequitable disease distribution is one way that local health departments can counter outcomes of systemic racism.”

Caine added, “This intervention would not have been possible without community partnerships. These relationships need to be established and built upon for interventions such as this to be successful.”

The results of Marion County’s program are featured in the scientific report, “Supporting Health Equity Through Data-Driven Decision-Making: A Local Health Department Response to COVID-19,” published in a special issue of the American Journal of Public Health.