Malaria is the leading cause of morbidity and mortality in Mali. Between 2017 and 2020, the number of cases increased in the country, with 2,884,827 confirmed cases and 1454 reported deaths in 2020. We performed a malaria risk stratification at the health district level in Mali with a view to proposing targeted control interventions. Data on confirmed malaria cases were obtained from the District Health Information Software 2, data on malaria prevalence and mortality in children aged 6–59 months from the 2018 Demographic and Health Survey, entomological data from Malian research institutions working on malaria in the sentinel sites of the National Malaria Control Program (NMCP), and environmental data from the National Aeronautics and Space Administration. A stratification of malaria risk was performed. Targeted malaria control interventions were selected based on spatial heterogeneity of malaria incidence, malaria prevalence in children, vector resistance distribution, health facility usage, child mortality, and seasonality of transmission. These interventions were discussed with the NMCP and the different funding partners. In 2017–2019, median incidence across the 75 health districts was 129.34 cases per 1000 person-years (standard deviation = 86.48). Risk stratification identified 12 health districts in very low transmission areas, 19 in low transmission areas, 20 in moderate transmission areas, and 24 in high transmission areas. Low health facility usage and increased vector resistance were observed in high transmission areas. Eight intervention combinations were selected for implementation. Our work provides an updated risk stratification using advanced statistical methods to inform the targeting of malaria control interventions in Mali. This stratification can serve as a template for continuous malaria risk stratifications in Mali and other countries.

Background In malaria endemic countries, seasonal malaria chemoprevention (SMC) interventions are performed during the high malaria transmission in accordance with epidemiological surveillance data. In this study we propose a predictive approach for tailoring the timing and number of cycles of SMC in all health districts of Mali based on sub-national epidemiological surveillance and rainfall data. Our primary objective was to select the best of two approaches for predicting the onset of the high transmission season at the operational scale. Our secondary objective was to evaluate the number of malaria cases, hospitalisations and deaths in children under 5 years of age that would be prevented annually and the additional cost that would be incurred using the best approach. Methods For each of the 75 health districts of Mali over the study period (2014–2019), we determined (1) the onset of the rainy season period based on weekly rainfall data; (ii) the onset and duration of the high transmission season using change point analysis of weekly incidence data; and (iii) the lag between the onset of the rainy season and the onset of the high transmission. Two approaches for predicting the onset of the high transmission season in 2019 were evaluated. Results In the study period (2014–2019), the onset of the rainy season ranged from week (W) 17 (W17; April) to W34 (August). The onset of the high transmission season ranged from W25 (June) to W40 (September). The lag between these two events ranged from 5 to 12 weeks. The duration of the high transmission season ranged from 3 to 6 months. The best of the two approaches predicted the onset of the high transmission season in 2019 to be in June in two districts, in July in 46 districts, in August in 21 districts and in September in six districts. Using our proposed approach would prevent 43,819 cases, 1943 hospitalisations and 70 deaths in children under 5 years of age annually for a minimal additional cost. Our analysis shows that the number of cycles of SMC should be changed in 36 health districts. Conclusion Adapting the timing of SMC interventions using our proposed approach could improve the prevention of malaria cases and decrease hospitalisations and deaths. Future studies should be conducted to validate this approach. Graphical Abstract

Background In malaria endemic countries, control interventions are performed during the high malaria transmission season using epidemiological surveillance data. One such intervention, seasonal chemoprevention (SMC), consists of the monthly administration of antimalarial drugs to children under 5 years. This study proposes an anticipating approach for adapting the timing of SMC interventions in Mali and the number of rounds. Our primary objective was to select the best approach for anticipating the onset of the high transmission season in the different health districts of Mali based on epidemiological surveillance and rainfall data. Our secondary objective was to evaluate the number of malaria cases, hospitalisations, and deaths in children under 5 years that could be prevented in Mali using the selected approach and the additional cost associated.Method Confirmed malaria cases and weekly rainfall data were collected for the 75 health districts of Mali for the 2014-2019 period. The onset of the rainy season, the onset of the high transmission season, the lag between these two events and the duration of the high transmission season were determined for each health district. Two approaches for anticipating the onset of the high transmission season in 2019 were evaluated. Results In 2014-2019, the onset of the rainy season ranged from W17 April to W34 August and that of the high transmission season from W25 June to W40 September. The lag between these two events ranged from 5 to 12 weeks. The duration of the high transmission season ranged from 3 to 6 months. The best approach anticipated the onset of the high transmission season 2019 in June in 2 districts, July in 46 districts, August in 21 districts and September in 6 districts. Using this approach over the 2014-2019 period would have led to changing the timing of SMC interventions in 36 health districts and would have prevented 43,819 cases, 1,943 hospitalisations and 70 deaths in children under 5 years. The additional cost of using our proposed approach is less than 5% of the current approach. Conclusion Adapting the timing of SMC interventions using our proposed approach would improve the prevention of malaria cases, hospitalisations, and deaths for a reasonable additional cost.

ABSTRACT. The Mali National Malaria Control Program (NMCP) recently established a phased set of goals for eliminating malaria in Mali by 2030. Over the past decade, the scale-up of NMCP-led malaria control interventions has led to considerable progress, as evidenced by multiple malariometric indicators. The West Africa International Center of Excellence in Malaria Research (WA-ICEMR) is a multidisciplinary research program that works closely with the NMCP and its partners to address critical research needs for malaria control. This coordinated effort includes assessing the effectiveness of control interventions based on key malaria research topics, including immune status, parasite genetic diversity, insecticide and drug resistance, diagnostic accuracy, malaria vector populations and biting behaviors, and vectorial capacity. Several signature accomplishments of the WA-ICEMR include identifying changing malaria age demographic profiles, testing innovative approaches to improve control strategies, and providing regular reporting on drug and insecticide resistance status. The NMCP and WA-ICEMR partnership between the WA-ICEMR and the NMCP offers a comprehensive research platform that informs the design and implementation of malaria prevention and control research programs. These efforts build local expertise and capacity for the next generation of malaria researchers and guide local policy, which is crucial in sustaining efforts toward eliminating malaria in West Africa.

Introduction: Malaria has been the main cause of morbidity and mortality in Mali, with an increase from 2017 to 2020 (2,884,837 confirmed cases and 1,454 deaths). On the recommendation of the World Health Organization (WHO) and for efficient use of resources, Mali has begun a process of malaria stratification. Method: Malaria, entomological and environmental data were collected through the local health information system, the Demographic and Health Survey 2018, research institutions and MALI-METEO services. The WHO stratification based on malaria incidence was used to present a stratified malaria risk map. Environmental factors associated with malaria were identified using a general additive non-linear regression model. The classification and regression tree method was used to improve the stratification. Interventions were proposed according to the incidence stratification and the different environmental, entomological, access to care maps. Results: From 2017 to 2019, the median incidence across the 75 health districts was 129. cases per 1,000 person-year (IQR=86.48). Stratification resulted in 12 health districts of very low, 19 low, 20 moderates and 24 in high transmission areas. Considering the environmental risk associated to malaria incidence, 6 environmental classes were selected. Four different strategies were proposed, from improving 2 surveillance and response to epidemic in the very low and low zones, to access to care improvement in the moderate and high zone. Conclusion: This stratification in Mali will allow targeting malaria control strategies.