Why Local Data Matters
In many countries, health policy is shaped by data collected elsewhere. Models from high-income contexts often fail to reflect the realities of rural Burundi. Our research team works from a different starting point: effective programs require accurate local data. We run field studies and epidemiological surveillance directly in the communities we serve, so our programs respond to what is actually happening — not what we assume.
Our methodology combines community interviews with quantitative clinical data. This helps us understand not just what diseases are prevalent, but why certain populations remain vulnerable even where national health programs exist.
Relative Impact of Interventions (2021-2024 Cohort)
Reduction in severe cases following targeted community health worker (CHW) deployment.
Malaria Interventions in Rural Contexts
Malaria is the leading cause of death in Burundi for children under five and pregnant women. Our longitudinal study tested combining long-lasting insecticide-treated nets (LLINs) with ongoing community-based education, documented against the WHO Africa baseline.
Distributing nets is necessary but not sufficient. Paired with bi-weekly CHW home visits, we saw a sustained 42% reduction in severe pediatric malaria — families need both the nets and the education to use them consistently.
Maternal Health and Community Networks
Maternal mortality in East Africa cannot be solved by physician availability alone. Our research focuses on task-shifting — training non-physician workers to perform specific maternal health interventions safely. Building on Lancet Global Health frameworks, we piloted equipping community midwives with mobile ultrasound and obstetric triage protocols. Early complication detection at village level — followed by referral to Ubuntu Medical Center — significantly improves birth outcomes.
Healthcare Financing and Equity
Clinical programs fail if patients cannot afford to use them. Our health economists are studying financial barriers to care, focusing on the mutuelles de santé community insurance model. Preliminary data shows community-managed pools reduce out-of-pocket spending and protect households from financial shocks — evidence we are publishing for NGOs and governments building universal coverage in similar settings.
Access Our Datasets
Future Health is committed to open science. Anonymized epidemiological datasets and methodological appendices for our published studies are available for academic and institutional researchers upon formal request.
