Subnational tailoring of malaria interventions to prioritize the malaria response in Guinea

Abstract

AbstractBackgroundIn the context of high malaria burden yet limited resources, Guinea’s national malaria program adopted an innovative subnational tailoring (SNT) approach, including engagement of stakeholders, data review, and data analytics, to update their malaria operational plan for 2024-2026 and identify the most appropriate interventions for each district considering the resources available.MethodsGuinea’s malaria program triggered the SNT exercise with a list of decisions that could be informed with local data. The program established an SNT team, which determined intervention targeting criteria; identified, assembled, and reviewed relevant data sources; stratified malaria risk and its determinants to inform geographical targeting for each intervention; and used mathematical modeling to predict the impact of different intervention mix scenarios. The SNT analysis was performed at the district level, excluding the urban area of Conakry.ResultsMalaria incidence, malaria prevalence, and all-cause under-5 mortality were used for the epidemiological stratification of Guinea. Additional indicators relevant for decisions-making including seasonality patterns, insecticide resistance or malaria interventions and vaccine coverage were also stratified. Stratified layers were used to inform the targeting criteria for each intervention to identify districts to prioritize for indoor residual spray, dual-action insecticide-treated nets, seasonal malaria chemoprevention (SMC) including number of cycles for each eligible district, malaria vaccine, and perennial malaria chemoprevention. Results of the SNT analysis were used to mobilize funding from the Global Fund for scale-up of dual-action nets and expansion of SMC.ConclusionsSNT allowed Guinea’s national malaria program to adapt their intervention strategy at the health district level, an unprecedented approach in the country. The use of local data to inform eligibility and prioritization allowed the program to identify the optimal mix of interventions for each district and to successfully mobilize resources to support their plans.