Background: The first-line diagnosis of malaria in Mali is based on the use of rapid diagnostic tests (RDT) that detect the Histidin Rich Protein 2 (HRP2) antigen specific to Plasmodium falciparum. Our study, based on a real-time polymerase chain reaction (qPCR) gold standard, aimed to describe the distribution of the Plasmodium species in each administrative region of Mali and to assess the performance of RDTs. Methods: We randomly selected 150 malaria-negative and up to 30 malaria-positive RDTs in 41 sites distributed in 9 regions of Mali. DNA extracted from the RDT nitrocellulose strip was assayed with a pan-Plasmodium qPCR. Positive samples were then analyzed with P. falciparum-, P. malariae-, P. vivax-, or P. ovale-specific qPCRs. Results: Of the 1496 RDTs, 258 (18.6%) were positive for Plasmodium spp., of which 96.9% were P. falciparum. The P. vivax prevalence reached 21.1% in the north. RDT displayed acceptable diagnostic indices; the lower CI95% bounds of Youden indices were all ≥0.50, except in the north (Youden index 0.66 (95% CI [0.44–0.82]) and 0.63 (95% CI [0.33–0.83]. Conclusions: Overall, RDT diagnostic indices are adequate for the biological diagnosis of malaria in Mali. We recommend the use of RDTs detecting P. vivax-specific antigens in the north.

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. This study aimed to describe the spatio-temporal variability of malaria incidence and the associated meteorological and environmental factors in the health district of Kati, Mali. Methods: Daily malaria cases were collected from the consultation records of the 35 health areas of Kati’s health district, for the period 2015–2019. Data on rainfall, relative humidity, temperature, wind speed, the normalized difference vegetation index, air pressure, and land use–land cover were extracted from open-access remote sensing sources, while data on the Niger River’s height and flow were obtained from the National Department of Hydraulics. To reduce the dimension and account for collinearity, strongly correlated meteorological and environmental variables were combined into synthetic indicators (SI), using a principal component analysis. A generalized additive model was built to determine the lag and the relationship between the main SIs and malaria incidence. The transmission periods were determined using a change-point analysis. High-risk clusters (hotspots) were detected using the SatScan method and were ranked according to risk level, using a classification and regression tree analysis. Results: The peak of the malaria incidence generally occurred in October. Peak incidence decreased from 60 cases per 1000 person–weeks in 2015, to 27 cases per 1000 person–weeks in 2019. The relationship between the first SI (river flow and height, relative humidity, and rainfall) and malaria incidence was positive and almost linear. A non-linear relationship was found between the second SI (air pressure and temperature) and malaria incidence. Two transmission periods were determined per year: a low transmission period from January to July—corresponding to a persisting transmission during the dry season—and a high transmission period from July to December. The spatial distribution of malaria hotspots varied according to the transmission period. Discussion: Our study confirmed the important variability of malaria incidence and found malaria transmission to be associated with several meteorological and environmental factors in the Kati district. The persistence of malaria during the dry season and the spatio-temporal variability of malaria hotspots reinforce the need for innovative and targeted strategies.

Background: First-line biological diagnosis of malaria in Mali is based on the use of rapid diagnostic tests (RDT), which detect in the blood the Histidin Rich Protein 2 antigen, specific to Plasmodium falciparum. Our study, based on a real-time polymerase chain reaction (qPCR) gold-standard diagnosis, aims to evaluate the performance of RDTs used in Mali and to describe the distribution of Plasmodium species in each administrative regions of Mali; Methods: We collected RDT cassettes in 47 sites of the nine regions of Mali. We randomly selected 150 malaria-negative and up to 30 malaria-positive RDTs from each regions. DNA was extracted from the RDTs’ nitrocellulose strip and then assayed with a pan-Plasmodium qPCR. Positive samples were then analyzed with qPCRs specific for P. falciparum, P. malariae, P. vivax, and P. ovale; Results: Of the 1,389 tested by qPCR RDTs, 258 (18.6%) were positive for Plasmodium spp. P.falciparum was the most predominant (97.3%). However, the prevalence of P.vivax reach 21.1% in the Ménaka region in the north; Conclusion: Overall, RDT diagnostic indices are adequate for the biological diagnosis of malaria in Mali. Our finding support the adjustment of RDTs to the local epidemiology.