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Leveraging Injection Networks to Prevent HIV and Other Blood Borne Infections Among People Who Inject Drugs in Kenya:
Matthew J Akiyama1, Hannah N Manley1, Lindsey R Riback1
1Albert Einstein College of Medicine.
Insights
This study uses network analysis and mathematical modeling to identify key individuals in HIV and Hepatitis C transmission networks among people who inject drugs in Kenya. Findings will inform targeted interventions to reduce blood-borne infections in resource-limited settings.
Area of Science:
- Epidemiology
- Public Health
- Network Science
Background:
- Blood-borne infections (BBIs), including HIV and Hepatitis C (HCV), pose significant global health challenges, particularly among people who inject drugs (PWID).
- Global health organizations aim to eliminate viral hepatitis and HIV by 2030, necessitating novel strategies for marginalized populations in resource-limited settings.
- Limited harm reduction services in some regions highlight the need for targeted prevention approaches for PWID.
Purpose of the Study:
- To identify transmission networks of BBIs among PWID in Kenya.
- To inform the development of targeted prevention and elimination strategies for BBIs in resource-limited settings.
- To investigate the impact of network characteristics on BBI transmission and intervention effectiveness.
Main Methods:
- Respondent-Driven Sampling (RDS) to recruit PWID from needle and syringe programs.
- Biobehavioral surveys, social network analysis, and point-of-care testing for HIV, HCV, and Hepatitis B (HBV).
- Integration of network data, egocentric analysis, and viral phylogenetics with mathematical modeling to assess transmission dynamics and intervention impacts.
Main Results:
- Identification of highly central individuals within PWID social networks who may significantly contribute to BBI transmission.
- Characterization of transmission pathways and network structures relevant to HIV, HCV, and HBV.
- Mathematical modeling to simulate the effects of targeted interventions based on network properties.
Conclusions:
- Network and molecular epidemiologic data are crucial for designing effective, targeted BBI elimination strategies among PWID.
- This study provides a framework for optimizing interventions in resource-limited settings.
- The findings will aid policymakers and researchers in maximizing the impact of prevention and treatment efforts and monitoring progress toward BBI elimination goals.
Background:
HIV and Hepatitis C (HCV) are blood borne infections (BBIs) that remain a significant cause of global morbidity and mortality among people who inject drugs (PWID). UNAIDS and WHO have set goals for the elimination of viral hepatitis and HIV as major public health threats by 2030. To achieve these targets, innovative strategies are required among marginalized populations such as PWID, especially in resource-limited countries where coverage of harm reduction services is often limited. The goal of this study is to inform targeted strategies to prevent transmission of BBIs among PWID.
Methods:
We will use respondent driven sampling (RDS) to recruit PWID from needle and syringe programs in Kenya. Participants will complete biobehavioral and social network surveys and receive point-of-care HCV, HIV, and hepatitis B (HBV) testing. Participants will return for at least one follow-up visit to complete additional surveys and testing. We will use network data from RDS, egocentric, and viral phylogenetics to identify how highly central PWID contribute to transmission networks and use mathematical modelling to investigate the impact of targeted interventions based on network characteristics.
Discussion:
This study will provide important information for policymakers and researchers designing strategies for BBI elimination. Network- and molecular epidemiologic-informed tools to guide targeted strategies may be critical to maximizing the impact of treatment and prevention efforts in resource-limited settings. This approach may provide a durable template for future studies, including prospective assessments of targeted prevention and elimination strategies among PWID, and assist with monitoring elimination progress in resource-limited settings.
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