Leveraging Big Data Science to Focus the HIV Response in Countries with Generalized HIV Epidemics

The overarching goal of the proposed aims has been to leverage novel methods with large and underutilized data sets to evaluate the potential impact of increasingly specific HIV responses across generalized epidemic settings in Sub-Saharan Africa (SSA) in reducing overall HIV incidence. This application was highly responsive to multiple areas of interest in the recent Notice of Special Interest (NOSI): Harnessing Big Data to Halt HIV (NOT-AI-21- 054). Moreover, the aims aligned with current realities of the HIV pandemic. While overall incidence has steadily declined over the last 15 years, over 1.5 million people newly acquired HIV in 2020 including one million people across SSA. The risk for HIV is not evenly distributed anywhere in the world. And while specific key populations are recognized to be at increased risk of HIV in many higher income settings, a general population construct is often used to represent HIV epidemics across SSA. This construct typically negates proximal determinants of HIV acquisition and transmission and ultimately has limited the effectiveness of the HIV response domestically in the US and around the world.
We proposed an ambitious set of aims to leverage available HIV-related data for key populations as well as auxiliary data including from social media, search patterns, spatial data, socioeconomic and migration data. We are assembling multiple data sources and integrating these data to build a comprehensive data warehouse to estimate key population-specific indicators including HIV incidence and prevalence, population size, engagement in the HIV treatment cascade, and structural determinants. These estimates, augmented by small area estimation methods where data are sparse, will inform dynamic transmission models to estimate differential risks of onward HIV transmission among key populations and to better address the needs of key populations compared with general-population approaches. Finally, we are leveraging very large and underutilized existing program data for HIV testing, prevention, and treatment programs. This was done in partnership with implementing partners. Cameroon, Kenya, Senegal, and South Africa are used as exemplar countries with sufficient data, willing governments, and representation of common HIV epidemic typologies in their respective regions of SSA. The following aims are near completion and will proceed without any foreign subawards.

Grant Number: 5R01AI170249-04
NIH Institute/Center: NIH
Principal Investigator: Stefan Baral