Population impact of malaria control interventions in the health district of Kati, Mali.

Background: WHO and its partners have adopted alternative control interventions since the failure to eradicate malaria worldwide in the 1960s and 1970s. The aim of these interventions has been to redesign the control interventions to make them more effective and more efficient. The purpose of this study is to assess the population impact of control interventions implemented at the community health area level.

Spatio-Temporal Variability of Malaria Incidence in the Health District of Kati, Mali, 2015-2019.

Introduction: Despite the implementation of control strategies at the national scale, the malaria burden remains high in Mali, with more than 2.8 million cases reported in 2019. In this context, a new approach is needed, which accounts for the spatio-temporal variability of malaria transmission at the local scale.

Sub-national tailoring of seasonal malaria chemoprevention in Mali based on malaria surveillance and rainfall data.

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.

Stratification at the health district level for targeting malaria control interventions in Mali.

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.

Spatio-temporal analysis and prediction of malaria cases using remote sensing meteorological data in Diébougou health district, Burkina Faso, 2016-2017.

Malaria control and prevention programs are more efficient and cost-effective when they target hotspots or select the best periods of year to implement interventions. This study aimed to identify the spatial distribution of malaria hotspots at the village level in Diébougou health district, Burkina Faso, and to model the temporal dynamics of malaria cases as a function of meteorological conditions and of the distance between villages and health centres (HCs). Case data for 27 villages were collected in 13 HCs.