An estimated 43% of the variability in US fatalities from the novel coronavirus (COVID-19) is linked with county-level socioeconomic indicators and health vulnerabilities.
The strongest association is seen in the proportions of people living with chronic kidney disease and living in nursing homes.
The study by researchers at Columbia University’s Mailman School of Public Health suggests that allocating vaccines based on these factors could help minimise severe outcomes, particularly deaths. Results are published in the open-access journal PLOS Medicine.
“It is well known that COVID-19 deaths are concentrated in communities with underlying health and socioeconomic vulnerabilities,” said Sasikiran Kandula, MS, the study’s first author and senior staff associate in the Department of Environmental Health Sciences at Columbia Mailman School of Public Health.
Kandula noted that the study estimates an increase in risk from some of the key health and socioeconomic characteristics in the US.
Dr Jeffrey Shaman, the paper’s senior author and Professor of Environmental Health Sciences at Columbia’s Mailman School of Public Health, said, “This information can guide the distribution of vaccines, particularly in parts of the world where vaccine supply is limited, in order to get them to communities where they are needed most.”
Currently, COVID-19 vaccination strategies in the US are informed by individual characteristics, such as age and occupation. The effectiveness of population-level health and socioeconomic indicators to determine risk of dying from the virus is understudied.
To test their hypothesis that health and socioeconomic indicators can accurately model risk of COVID-19 mortality, Shaman and Kandula extracted county-level estimates of 14 indicators associated with COVID-19 mortality from public data sources.
They then modelled the proportion of county-level COVID-19 mortality explained by identified health and socioeconomic indicators, and assessed the estimated effect of each predictor.
They found that 43% of variability in US COVID-19 mortality can be traced to nine county-level socioeconomic indicators and health vulnerabilities, after adjusting for associations in deaths rates between adjacent counties.
Among health indicators, mortality is estimated to increase by: 43 per 1,000 residents for every 1% increase in the prevalence of chronic kidney disease; and by 10 for chronic heart disease; seven for diabetes; four for COPD; four for high cholesterol; three for high blood pressure; and three for obesity prevalence respectively.
Among socioeconomic indicators, mortality is estimated to increase by 39 deaths per 1,000 for every 1% increase among those living in nursing homes, and by three and two for each 1% increase in the percentage of the population who are elderly (65+ years) and uninsured aged between 18 and 64-year-olds, respectively. The mortality rate is estimated to decrease by two for every $1,000 increase in per capita income.
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.
