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Abstract Background In the context of high malaria burden yet limited resources, Guinea’s national malaria programme 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. Methods Guinea’s malaria programme triggered the SNT exercise with a list of decisions that could be informed with local data. The programme 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 modelling to predict the impact of different intervention mix scenarios. The SNT analysis was performed at the district level, excluding the urban area of Conakry. Results Malaria incidence, malaria prevalence, and all-cause under-5 mortality were used for the epidemiological stratification of Guinea. Additional indicators relevant for decision-making including seasonality patterns, insecticide resistance, historical 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. Conclusions SNT allowed Guinea’s national malaria programme 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 programme to identify the optimal mix of interventions for each district and to successfully mobilize resources to support their plans.

Abstract Background Malaria risk maps are crucial for controlling and eliminating malaria by identifying areas of varying transmission risk. In the Greater Mekong Subregion, these maps guide interventions and resource allocation. This article focuses on analysing changes in malaria transmission and developing fine-scale risk maps using five years of routine surveillance data in Laos (2017–2021). The study employed data from 1160 geolocated health facilities in Laos, along with high-resolution environmental data. Methods A Bayesian geostatistical framework incorporating population data and treatment-seeking propensity was developed. The models incorporated static and dynamic factors and accounted for spatial heterogeneity. Results Results showed a significant decline in malaria cases in Laos over the five-year period and a shift in transmission patterns. While the north became malaria-free, the south experienced ongoing transmission with sporadic outbreaks. Conclusion The risk maps provided insights into changing transmission patterns and supported risk stratification. These risk maps are valuable tools for malaria control in Laos, aiding resource allocation, identifying intervention gaps, and raising public awareness. The study enhances understanding of malaria transmission dynamics and facilitates evidence-based decision-making for targeted interventions in high-risk areas.

Insecticide treated nets (ITNs) are an important part of malaria control in Africa and WHO targets aim for 80% coverage. This study estimates the spatio-temporal access and use of ITNs in Africa from 2000-2020, and shows that both metrics have improved over time but access remains below WHO targets.