Abstract
The global COVID-19 pandemic has imposed unprecedented pressure on health systems and has interrupted
public health efforts for other major health conditions, including HIV. HIV service interruptions in the forms
of redeployment of staff, reallocation of resources, lack of equipment and medicine (e.g., shortages of HIV/STI
testing kits, strained drug supply chain), and reduced access to care (e.g., travel restrictions, lock downs) may
have a profound and long-term impact on HIV treatment cascade outcomes, especially given the evolving
nature of the pandemic. There are several gaps in the existing literature in addressing HIV service
interruptions and their consequences. These gaps include a lack of using large-scale, real-world, multi-type
data with theoretical guidance; the focus on single or limited HIV treatment cascade outcomes; and limited
efforts to identify factors that can mitigate the negative impacts of such interruptions to inform potential
interventions and capacity building at state or local levels. In response to NOT-AI-21-057, we propose to
comprehensively investigate HIV service interruptions during the COVID-19 pandemic following a
socioecological model, assess their impacts on various outcomes of the HIV prevention and treatment cascade,
and identify resilience resources for buffering impacts of interruptions on HIV treatment cascade outcomes.
Specifically, we will assess HIV service interruptions in South Carolina (SC) since 2020 using operational
report data of Ryan White HIV clinics, in-depth interview data with clinic leaders and providers, and HIV
service utilization data based on both electronic health records (EHR) and publicly available cellphone-based
HIV clinics visitation data. We will further explore how HIV service interruptions affects HIV prevention and
treatment cascade outcomes at appropriate geospatial units based on the integration of multi-type datasets
(e.g., EHR, geospatial data) from multiple sources. Finally, we will identify institutional-, community-, and
structural-level factors (e.g., resilience resources) that may mitigate the adverse impacts of HIV service
interruptions based on the triangulation of quantitative (EHR data, online survey data) and qualitative (in-
depth interviews, focus group discussion) data regarding health infrastructure, social capital, and
organizational preparedness. Our proposed research can lead to a better understanding of complicated HIV
service interruptions in SC and resilience factors that can mitigate the negative effects of such interruptions on
various HIV treatment cascade outcomes. The multi-level resilience resources identified through data
triangulation will assist SC health departments and communities in developing strategic plans in response to
this evolving pandemic and other future public health emergencies (e.g., monkeypox, disasters caused by
climate change). The research findings can also inform public health policymaking and the practices of other
Deep South states with similar sociocultural contexts and experiences of HIV service interruptions during the
pandemic.