About the instructor:
ALOWE David Kossi holds a master’s degree in epidemiology, biostatistics, and health research. He has been a member of the Epidemiological Surveillance and Research Unit at Togo’s National Malaria Control Program (PNLP) since 2025. As part of the stratification process, he actively contributes to the subnational adaptation (SNT) of malaria control interventions in Togo with support from AHADI.
His primary responsibilities include managing and analyzing databases, as well as presenting methodological approaches and analysis results to the national SNT team. Passionate about using data to inform public health decisions, he applies his expertise to improve the planning and effectiveness of malaria control interventions in Togo.
Event Summary
David Kossi Alowe presented an overview of Togo's 2025 Subnational Tailoring (SNT) exercise, a WHO-recommended approach to optimizing malaria control efforts. The presentation highlighted how the country's National Malaria Control Program (PNLP) moved away from uniform, one-size-fits-all interventions toward precise, district-level targeting — enabling more rational use of limited resources by adapting prevention and treatment strategies to the epidemiological realities of each health district.
The analytical framework drew on multiple data sources, including epidemiological, entomological, and environmental indicators, to stratify Togo's 39 health districts by incidence levels and key determining factors such as access to care and seasonal rainfall patterns. This stratification informed the development of differentiated intervention packages for each district, ranging from next-generation mosquito net distribution to seasonal chemoprevention.
The presentation concluded that the 2025 SNT exercise represented meaningful progress for Togo, with notable improvements in data quality and stronger strategic alignment with the 2026–2029 National Strategic Plan. While the modeling of decision-making scenarios was highlighted as a particular success, challenges remained — including fragmented data sources and the need to build local analytical capacity. The long-term sustainability of the SNT approach was framed as dependent on embedding a culture of high-quality data collection and fully committing to spatially precise, locally tailored strategies.
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