Harnessing big heterogeneous data to evaluate the potential impact of HIV responses among key populations in Sub Saharan Africa: The Boloka Data Repository Initiative (Preprint)

BACKGROUND Key Populations (KPs), including gay men and other men who have sex with men, female sex workers, transgender persons, people who use drugs, and incarcerated persons, have a higher risk of human immunodeficiency virus (HIV) acquisition and transmission than the general population. Currently, there is no centralized data repository where KP HIV surveillance and programming data is gathered and stored in South Africa. Data on KPs are being collected on a smaller scale by numerous stakeholders and managed in silos; hence, there exists an opportunity to harness these variety of data sources for evaluating the potential impact of HIV responses among KPs in South Africa. OBJECTIVE To leverage and harness Big Heterogeneous Data on HIV among KPs and rigorously harmonize as well as analyze it to inform a targeted HIV response for greater impact in Sub-Saharan Africa (SSA). METHODS The Boloka data repository initiative has five main stages. There will be engagement of a wide range of stakeholders throughout South Africa to develop meaningful partnerships to both facilitate acquisition of data and to generate ideas around a base structure for the Boloka data repository (stage 1). Through these engagements, different data types including programmatic, and research data will be collated (stage 2). The data will be filtered and screened to enable high quality analyses (stage 3). The collated data will be stored in the Boloka data repository (stage 4). The established Boloka data repository will be made accessible for stakeholders and authorized users (stage 5). RESULTS The stakeholder analysis process is underway and the Excel project tracking tool listing potential stakeholders, their contact details, and their level of engagement with data (e.g., district, provincial, and national) is in place. A series of engagements have been carried out with the respective organizations; the engagements are at different stages. The research team has identified and begun meeting with numerous data stakeholders and developed meaningful research-practice partnerships to facilitate collaboration and data sharing; several collaborative agreements are underway CONCLUSIONS A truly “complete” data infrastructure that systematically and rigorously integrates empiric, contextual, observational, and programmatic data for KPs will not only improve our understanding of local epidemics but will also improve HIV interventions and policies. Further, it will inform future research directions, and become an incredible institutional mechanism for epidemiological and public health training.