The COVID-19 vaccine efficacy among people living with and without HIV: a real-world data approach

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Project Summary/Abstract Effective and durable COVID-19 vaccines hold the potential to dramatically alter the COVID-19 pandemic. Remarkable achievement of COVID-19 vaccine development was observed in large, randomized-controlled trials, where several vaccines were found to be safe and efficacious in preventing symptomatic COVID-19. Despite the high level of vaccine efficacy, a small percentage of fully vaccinated persons (i.e., received all recommended doses of an FDA-authorized COVID-19 vaccine) will develop symptomatic or asymptomatic infections of SARS-CoV-2, which is referred to as COVID-19 vaccine breakthrough infections (hereafter as “breakthrough infections”). Immunocompromised individuals, such as people living with HIV (PLWH), appear to be at an elevated risk of COVID-related illness, hospitalization, and death. Thus, ensuring the effectiveness of COVID-19 vaccine in PLWH is pressing. However, the efficacy of COVID-19 vaccine among PLWH remains unclear because PLWH were not representatively included in the vaccine efficacy trials and did not account for a large proportion in the existing efforts to investigate vaccine efficacy among immunocompromised population in the real-world. Understanding COVID-19 vaccine efficacy in real-world settings is critical to helping disease monitoring and inform future booster vaccine distribution. With NIH support (R01AI127203) since 2017, we have been utilizing a Big Data approach to examine the treatment gaps among 12,203 PLWH who were diagnosed with HIV during 2005-2020 (‘HIV Cohort’) in South Carolina (SC). Also supported by NIH (R01AI127203-04S1), our team have established a South Carolina COVID-19 cohort (S3C) since 06/2020 by integrating patients’ electronic health records (EHR) with one-year pre-COVID healthcare utilization data. In this exploratory study, we will retrieve the patient-level immunization records from the South Carolina Statewide Immunization Online Network (SIMON) and merge this database with ‘HIV Cohort’ database to identify vaccinated PLWH and a comparison group of non-PLWH via propensity score matching. The S3C cohort data, which includes healthcare encounters and COVID-19 diagnosis information, will be merged with HIV Cohort and SIMON datasets to define the breakthrough infections. With the integration of multiple data sources and advanced data analytics, the current exploratory study first aims to characterize and compare the breakthrough infections (e.g., prevalence and disease severity) between PLWH and non-PLWH and then examine whether HIV markers and HIV treatment play a role in COVID-19 vaccine efficacy within the PLWH population while adjusting for key confounders (e.g., prior COVID-19 diagnosis, comorbid conditions, local COVID-19 incidence). The proposed research is innovative and significant because understanding the COVID- 19 vaccine efficacy among PLWH and non-PLWH is essential to support informed vaccination decision-making in clinical practice. Characterizing PLWH at higher risk of breakthrough infections (low CD4 counts, unsuppressed viral load) may help to develop guidance to augment their protection against risk of COVID-19.