A time-varying vulnerability index for COVID-19 in New Mexico, USA using generalized propensity scores

• Published in: Health Policy OPEN 2021-12, Vol.2, p.100052-100052, Article 100052
• Main Authors: Gorris, Morgan E., Shelley, Courtney D., Del Valle, Sara Y., Manore, Carrie A.
• Format: Article
• Language: English
• Subjects: BASIC BIOLOGICAL SCIENCES; Coronavirus; Decision support techniques; Index; MATHEMATICS AND COMPUTING; New Mexico; Propensity score; Vulnerable populations
• ISSN: 2590-2296; 2590-2296
• DOI: 10.1016/j.hpopen.2021.100052

[Display omitted] •New Mexico has a unique population vulnerable to negative COVID-19 outcomes.•We used propensity scores to assess vulnerability while accounting for social demographics.•The county vulnerabilities are variable in the first eight weeks, then stabilize.•Average household size was an important determinant of time-varying vulnerability.•Health officials may use this vulnerability index as a decision support tool. The coronavirus disease (COVID-19) pandemic has highlighted systemic inequities in the United States and resulted in a larger burden of negative social outcomes for marginalized communities. New Mexico, a state in the southwestern US, has a unique population with a large racial minority population and a high rate of poverty that may make communities more vulnerable to negative social outcomes from COVID-19. To identify which communities may be at the highest relative risk, we created a county-level vulnerability index. After the first COVID-19 case was reported in New Mexico on March 11, 2020, we fit a generalized propensity score model that incorporates sociodemographic factors to predict county-level viral exposure and thus, the generic risk to negative social outcomes such as unemployment or mental health impacts. We used four static sociodemographic covariates important for the state of New Mexico—population, poverty, household size, and minority population—and weekly cumulative case counts to iteratively run our model each week and normalize the exposure score to create a time-varying vulnerability index. We found the relative vulnerability between counties varied in the first eight weeks from the initial COVID-19 case before stabilizing. This framework for creating a location-specific vulnerability index in response to an ongoing disaster may be used as a quick, deployable metric to inform health policy decisions such as allocating state resources to the county level.