Big Data Analytics Dashboard Shows Greatest Risk Factors for COVID-19

June 23, 2020 - Parkland Center for Clinical Innovation (PCCI) has developed a big data analytics dashboard to accurately identify communities at high risk for COVID-19 infection.

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The PCCI COVID-19 Vulnerability Index incorporates socioeconomic, clinical, mobility, and demographic risk factors. The index showed that social deprivation is a leading factor in determining an individuals’ risk for COVID-19 and is the primary reason for racial and ethnic disparities in COVID-19 risk – more so than age, race, or comorbidity rates.

The Vulnerability Index determines communities at risk by examining comorbidity rates, including chronic illnesses like hypertension, cancer, diabetes, and heart disease; areas with large density of populations over the age of 65; increased social deprivation such as lack of access to food, medicine, employment, and transportation.

The index also evaluates communities’ levels of mobility by modeling the rate at which individuals are able to observe stay-at-home and social distancing measures. Historical racial and ethnic disparities are also seen with COVID-19, with African American and Hispanic neighborhoods at greatest risk.

PCCI relied on data from Parkland Health & Hospital System, Dallas County Health and Human Services Department, and other resources.

“These kinds of precise data insights will help us understand communities and populations at greatest risk to COVID-19 and how to prioritize and tailor community interventions in order to proactively manage current and future outbreaks or other community-wide interventions,” said Steve Miff, PhD, President and CEO of PCCI.

The index will allow leaders to target interventions in a way that is most effective for particular areas.

“From a community health perspective, these latest PCCI analytics continue to support our ongoing efforts to proactively identify hot-spots, rapidly deploy targeted testing that is accessible locally, inform and educate the community using culturally-sensitive approaches, and align other critical resources to support individuals and their families during these difficult times,” said Philip Huang, MD, Director of Dallas County Health and Human Services.

The PCCI Vulnerability Index is multi-dimensional and incorporates stable, foundational elements such as demographics, prevalence of comorbidities, and social and economic resources. The index dynamically monitors and models the population’s ability to observe stay-at-home orders and near real-time COVID-19 incident rate.

“We are using analytics such as the PCCI Vulnerability Index to identify and prioritize our testing strategy, deployment of resources, and to facilitate transparency and collaboration across both public and private organizations that are crucial in these efforts,” said Kelvin Baggett, MD, City of Dallas COVID-19 Health and Healthcare Access Czar.

As communities work to manage risk and mitigate ongoing risks with COVID-19, PCCI’s Vulnerability Index will serve as an essential tool. In particular, the dashboard can help leaders target and tailor neighborhood responses, such as pandemic response readiness incorporating focused partnerships with local organizations based on neighborhood-specific risk profiles.

Additionally, the dashboard will help leaders leverage partnerships for rapid deployment of testing, isolation, or educational resources when rising risks occur, as well as tailor interventions to address elements of social deprivation that lead to higher risk of COVID-19.

The dashboard will also facilitate the implementation of culturally sensitive or culturally informed interventions targeting African American and Hispanic neighborhoods.

The findings from the PCCI Vulnerability Index align with those of a recent study from the MIT Sloan School of Management. The team found that COVID-19 death rates in the US are correlated with patients’ age, race, socioeconomic status, and other social determinants of health data.

“Some of these correlations are baffling and deserve further study, but regardless, our findings can help guide policymakers through this challenging time,” said Bora Ozaltun, a Graduate Research Assistant in the Center for Energy and Environmental Policy Research (CEEPR) lab.

“It’s clear that there are important and statistically significant difference in death rates across states. We need to investigate what’s driving those differences and see if we can understand how we might do things differently.”