HIV Infection Prevalence Significantly Intersects With COVID-19 Infection At the Area Level: A US County-Level Analysis

J Acquir Immune Defic Syndr. 2021 Oct 1;88(2):125-131. doi: 10.1097/QAI.0000000000002758.

Abstract

Background: Limited empirical evidence exists about the extent to which the current HIV epidemic intersects with COVID-19 infections at the area/geographic level. Moreover, little is known about how demographic, social, economic, behavioral, and clinical determinants are jointly associated with these infectious diseases.

Setting: Contiguous US counties (N = 3108).

Methods: We conducted a cross-sectional analysis and investigated the joint association between new HIV infection prevalence in 2018 and COVID-19 infections (January 22, 2020 and October 7, 2020) and explore the contribution of factors such as income inequality, binge drinking, and socioeconomic deprivation. We used Bayesian multivariate spatial models to estimate the cross-disease correlations between these diseases and identified hotspots, which we defined as a county with a posterior probability greater than 80% of being in the top decile of that disease.

Results: New HIV infection prevalence and COVID-19 infection moderately and significantly intersect [spatial correlation = 0.37, 95% credible interval (CrI) = 0.36-0.37]. Seventy-five counties, mostly in the south, were at elevated burden for HIV and COVID-19 infections. Higher income inequality was positively associated with both COVID-19 (relative risk 1.05, 95% CrI = 1.03-1.07) and HIV infection (relative risk = 1.12, 95% CrI = 1.09-1.15).

Conclusions: We found that there is a considerable intersection between the current distribution of HIV burden with COVID-19 infections at the area level. We identified areas that federal funding and vaccination campaigns should prioritize for prevention and care efforts.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Bayes Theorem
  • COVID-19 / epidemiology*
  • COVID-19 / virology
  • Cross-Sectional Studies
  • HIV Infections / epidemiology*
  • HIV Infections / virology
  • Humans
  • Income
  • Middle Aged
  • Prevalence
  • Socioeconomic Factors
  • United States / epidemiology