UC San Diego

Abstract: Background: We investigated the effect of HIV on COVID-19 outcomes with attention to selection bias due to differential testing and to comorbidity burden. Methods: Retrospective cohort analysis using four hierarchical outcomes: positive SARS-CoV-2 test, COVID-19 hospitalization, intensive care unit (ICU) admission, and hospital mortality. The effect of HIV status was assessed using traditional covariate-adjusted, inverse probability weighted (IPW) analysis based on covariate distributions for testing bias (testing IPWs), HIV infection status (HIV IPWs), and combined models. Among PWH, we evaluated whether CD4 count and HIV plasma viral load (pVL) discriminated between those who did or did not develop study outcomes using receiver operating characteristic analysis. Results: Between March and November 2020, 63,319 people were receiving primary care services at UCSD, of whom 4,017 were people living with HIV (PWH). PWH had 2.1 times the odds of a positive SARS-CoV-2 test compared to those without HIV after weighting for potential testing bias, comorbidity burden, and HIV-IPW (95% CI 1.6-2.8). Relative to persons without HIV, PWH did not have an increased rate of COVID-19 hospitalization after controlling for comorbidities and testing bias [adjusted incidence rate ratio (aIRR): 0.5, 95% CI: 0.1 – 1.4]. PWH had neither a different rate of ICU admission (aIRR:1.08, 95% CI; 0.31 – 3.80) nor in-hospital death (aIRR:0.92, 95% CI; 0.08 – 10.94) in any examined model. Neither CD4 count nor pVL predicted any of the hierarchical outcomes among PWH. Conclusions: PWH have a higher risk of COVID-19 diagnosis but similar outcomes compared to those without HIV. Summary point: After considering the effects of potential bias due to differential testing, comorbidities, and other patient characteristics, people with HIV had an increased rate of SARS-CoV-2 positivity and similar rates of hospitalization, ICU admission, and death.