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Primary Submission Category: Methodological approaches to studying public health
Building a Data Science Community of Practice to Strengthen Social Determinants of Health Data in Sub-Saharan Africa
Authors: Jessica Gjonaj, Felix Emeka Anyiam, Ngeresa Antony Osango, Richard Mugo, Peace Aber, Jasmit Shah, Rajesh Vedanthan, Joseph Hogan, Ann Mwang, Rumi Chunara,
Presenting Author: Jessica Gjonaj*
Background: Social determinants of health (SDOH) function across economic, social, and economic domains, accounting for up to 50% of variation in health outcomes.1 Despite their influence, integrating SDOH in health analytic models remains a challenge particularly in Sub-Sahran Africa (SSA) where it can be difficult to robustly collect context-specific data due to variations in data types, fragmentation, or inconsistent reporting. Increasing efforts to identify and integrate SDOH data, particularly in this region, is crucial in advancing public health research.2
Methods: Leveraging the NYU-Moi Data Science for Social Determinants Training Program and NIH DS-I Africa Network, a Data Science for Social Determinants Community of Practice (DSSD CoP) was formed to systematically address gaps in the identification and measurement of SDOH data in SSA. The CoP has identified two initial activities. The first is a scoping review to systematically map the types of data used to operationalize SDOH in SSA research and identify trends and gaps in measurement and reporting. The second is a data indexing group working towards creating a structured, searchable repository of SSA SDOH data sources derived from existing studies and surveys.
Results: The recent publication of the scoping review protocol highlight the novelty of this effort which is currently in the first phase of abstract screening.3 In parallel, the SDOH index has already identified 26 datasets that capture key SDOH data across Kenya (18), Uganda (2), Rwanda (1), Ghana (1), Sierra Leone (1), South Africa (1), Ethiopia (1), and Nigeria (1). The group aims to expand dissemination of this index form to gather more information on the current state of SDOH data in the region.
Conclusion: The CoP is a scalable initiative for advancing collaborative infrastructure and data science capacity to enhance the impact of SDOH research in public health. We already have early indication from CoP efforts that the focus on SSA allows for unique exploration of how social determinants interact with health outcomes in a specific context, which is crucial for accounting for SDOH data alongside health burdens across the region.