Allocating COVID-19 vaccines based on health and socioeconomics could reduce mortality
Efforts to reduce COVID-19 mortality rates in the US have focused on prioritizing vaccination initially for those at a higher risk of severe outcomes. The effectiveness of population-level health and socioeconomic indicators to determine risk of COVID-19 mortality is understudied. To test the hypothesis that health and socioeconomic indicators can accurately model risk of COVID-19 mortality, the researchers extracted county-level estimates of 14 indicators associated with COVID-19 mortality from public data sources. They then modeled the proportion of county-level COVID-19 mortality explained by identified health and socioeconomic indicators, and assessed the estimated effect of each predictor.
The authors found evidence for a spatial relationship between COVID-19 mortality and 9 health and socioeconomic indicators. The prevalence of chronic kidney disease and the proportion of the population resident in nursing homes had the largest individual effect on COVID-19 mortality. Although the research suggests a correlation between health and socioeconomic indicators and COVID-19 mortality, the study was limited by lags in reporting COVID-19 cases and deaths, and therefore these may have been underestimated.
According to the authors, "Our findings here show that differential risks of severe outcomes from COVID-19 across populations can be in part estimated from the structures and contexts in which the outbreak occurs, for example, a population's quality of health, its access to healthcare and the disparities therein. While vaccine supply continues to be limited for most, and especially low- and middle-income, countries, these population level indicators may help inform optimal allocation.".
INFORMATION:
Research Article
Peer-reviewed; Observational study; Humans
In your coverage please use this URL to provide access to the freely available paper:
http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003693
Funding: This work is funded in part by a grant from the National Science Foundation (DMS-2027369) and a gift from the Morris-Singer Foundation to JS. The funders had no role in study design, analysis or decision to publish.
Competing Interests: The authors of this manuscript report the following competing interests: JS and Columbia University disclose ownership of SK Analytics and JS discloses personal fees from BNI (Business Network International). SK consulted for SK Analytics.
Citation: Kandula S, Shaman J (2021) Investigating associations between COVID-19 mortality and population-level health and socioeconomic indicators in the United States: A modeling study. PLoS Med 18(7): e1003693. https://doi.org/10.1371/journal.pmed.1003693
