The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning

摘要

Expert groups have coalesced around a roadmap to address thecurrent COVID-19 pandemic centered on social distancing, monitoring case counts and health care capacity, and, eventually,moving to pharmaceutical interventions. However, responsibilityfor navigating the pandemic response falls largely on state andlocal officials. To make equitable decisions on allocating resources, caring for vulnerable subpopulations, and implementinglocal- and state-level interventions, access to current pandemicdata and key vulnerabilities at the community level are essential(National Academies of Sciences, Engineering, and Medicine2020). Although numerous predictive models and interactivemonitoring applications have been developed using pandemicrelated data sets (Wynants et al. 2020), their capacity to aid indynamic, community-level decision-making is limited. We developed the interactive COVID-19 Pandemic Vulnerability Index(PVI) Dashboard (https://covid19pvi.niehs.nih.gov/) to addressthis need by presenting a visual synthesis of dynamic informationat the county level to monitor disease trajectories, communicatelocal vulnerabilities, forecast key outcomes, and guide informedresponses (Figure 1).