Crimean–Congo hemorrhagic fever is a tick-borne disease caused by the arbovirus Crimean–Congo hemorrhagic fever virus (CCHFV, family Bunyaviridae, genus Nairovirus). CCHFV can cause a severe hemorrhagic fever with high-case fatality rates in humans. CCHFV has a wide geographic range and has been described in around 30 countries in the Middle East, Asia, Europe, and Africa including Mali and neighboring countries. To date, little is known about the prevalence rates of CCHFV in Mali. Here, using banked bovine serum samples from across the country, we describe the results of a seroepidemiological study for CCHFV aimed at identifying regions of circulation in Mali. In total, 1,074 serum samples were tested by a modified in-house CCHFV-IgG-enzyme-linked immunosorbent assay (ELISA) with confirmatory testing by commercial ELISA and immunofluorescence assay. Overall, 66% of samples tested were positive for CCHFV-specific IgG antibodies. Regional seroprevalence rates ranged from 15% to 95% and seemed to correlate with cattle density. Our results demonstrate that CCHFV prevalence is high in many regions in Mali and suggest that CCHFV surveillance should be established.

Fleas are obligate blood-feeding ectoparasites and vectors of several bacterial zoonotic pathogens as well as trypanosomes that parasitize rodents and other small mammals. During investigations of tick- and rodent-borne diseases in Mali, West Africa, we included fleas and rodent-borne trypanosomes, both of which are poorly known in this country, but are attracting greater public health interest. Small mammals were captured in 20 Malian villages from December 2007 to October 2011. Fleas were collected and identified to species, and thin blood smears were prepared, stained and examined microscopically for trypanosomes. We captured 744 small mammals, 68 (9.1 %) of which yielded fleas. Two species of fleas, Xenopsylla cheopis and Xenopsylla nubica, were collected from six species of rodents and one species of shrew. Multimammate rats, Mastomys natalensis, were hosts for 58.5 % of all fleas collected. Xenopsylla cheopis was found in the moister southern savannah while X. nubica was mostly restricted to the drier Sahel. Trypanosomes were found in 3 % of 724 blood smears, although 91 % of parasitemic animals originated from two villages where black rats (Rattus rattus) and M. natalensis were the primary hosts and X. cheopis the dominant flea. The trypanosomes were morphologically consistent with the Trypanosoma (Herpetosoma) lewisi group, flea-borne hemoflagellates that parasitize domestic rats. Xenopsylla cheopis and trypanosomes parasitize peridomestic rats that commingle with people in southern Mali. Given the increasing awareness of flea-borne trypanosomes as possible human pathogens, we hope our findings will stimulate future investigators to examine the potential public health significance of flea-borne trypanosomosis in West Africa.

Background: The long-lasting insecticidal nets (LLINs) and indoor residual spraying of insecticide (IRS) are major malaria vector control strategies in Mali. The success of control strategies depends on a better understanding of the status of malaria vectors with respect to the insecticides used. In this study we evaluate the level of resistance of Anopheles gambiae (sensu lato) to bendiocarb and the molecular mechanism that underlies it. Methods: Larvae of An. gambiae (s.l.) were collected from breeding habitats encountered in the three study sites and bioassayed with bendiocarb. The ace-1 target site substitution G119S was genotyped using a TaqMan assay. Results: The three species of the An. gambiae complex in Mali, i.e. An. arabiensis, An. coluzzii and An. gambiae (s.s.) were found in sympatry in the three surveyed localities with different frequencies. We observed a resistance and suspicious resistance of the three species to bendiocarb with a mortality rate ranging from 37% to 86%. The allelic frequency of the G119S mutation was higher in An. gambiae (s.s.) compared to the other two species; 42.86%, 25.61% and 16.67% respectively in Dangassa, Koula, and Karadié. The allelic frequency of G119S in An. coluzzii ranged from 4.5% to 8.33% and from 1.43% to 21.15% for An. arabiensis. After exposure to bendiocarb, the G119S mutation was found only in survivors. The survival of Anopheles gambiae (s.l) populations from the three surveyed localities was associated with the presence of the mutation. Conclusions: The study highlights the implication of G119S mutation in bendiocarb resistance in An. gambiae (s.s.), An. arabiensis and An. coluzzii populations from the three surveyed localities.

Malaria transmission largely depends on environmental, climatic, and hydrological conditions. In Mali, malaria epidemiological patterns are nested within three ecological zones. This study aimed at assessing the relationship between those conditions and the incidence of malaria in Dangassa and Koila, Mali. Malaria data was collected through passive case detection at community health facilities of each study site from June 2015 to January 2017. Climate and environmental data were obtained over the same time period from the Goddard Earth Sciences (Giovanni) platform and hydrological data from Mali hydraulic services. A generalized additive model was used to determine the lagged time between each principal component analysis derived component and the incidence of malaria cases, and also used to analyze the relationship between malaria and the lagged components in a multivariate approach. Malaria transmission patterns were bimodal at both sites, but peak and lull periods were longer lasting for Koila study site. Temperatures were associated with malaria incidence in both sites. In Dangassa, the wind speed (p = 0.005) and river heights (p = 0.010) contributed to increasing malaria incidence, in contrast to Koila, where it was humidity (p < 0.001) and vegetation (p = 0.004). The relationships between environmental factors and malaria incidence differed between the two settings, implying different malaria dynamics and adjustments in the conception and plan of interventions.

: Seasonal malaria chemoprevention (SMC) was adopted in Mali in 2012 for preventing malaria in children younger than 5 years. Although this strategy has been highly effective in reducing childhood malaria, an uptick in malaria occurrence has occurred in children 5 to 15 years of age. This study aimed to investigate the feasibility of providing SMC to older children. A cohort of 350 children age 5 to 14 years were monitored during the 2019 transmission season in Dangassa, Mali. The intervention group received five monthly rounds of sulfadoxine–pyrimethamine plus amodiaquine, whereas the control group consisted of untreated children. Community acceptance for extending SMC was assessed during the final round. Logistic regression models were applied to compare the risk of Plasmodium falciparum malaria infection, anemia, and fever between the intervention and control groups. Kaplan-Meier survival analyses were used to compare the time to P. falciparum parasitemia infection between the groups. The community acceptance rate was 96.5% (139 of 144). Significant declines were observed in the prevalence of P. falciparum parasitemia (adjusted odds ratio, 0.22; 95% CI, 0.11–0.42) and anemia (adjusted odds ratio, 0.15; 95% CI, 0.07–0.28) in the intervention group compared with the control group. The cumulative incidence of P. falciparum infections was significantly greater (75.4%, 104 of 138) in the control group compared with the intervention group (40.7%, 61 of 143, P = 0.001). This study reveals that expanding SMC to older children is likely feasible, has high community acceptance, and is in reducing uncomplicated malaria and anemia in older children.

Mali aims to reach the pre-elimination stage of malaria by the next decade. This study used functional regression models to predict the incidence of malaria as a function of past meteorological patterns to better prevent and to act proactively against impending malaria outbreaks. All data were collected over a five-year period (2012–2017) from 1400 persons who sought treatment at Dangassa’s community health center. Rainfall, temperature, humidity, and wind speed variables were collected. Functional Generalized Spectral Additive Model (FGSAM), Functional Generalized Linear Model (FGLM), and Functional Generalized Kernel Additive Model (FGKAM) were used to predict malaria incidence as a function of the pattern of meteorological indicators over a continuum of the 18 weeks preceding the week of interest. Their respective outcomes were compared in terms of predictive abilities. The results showed that (1) the highest malaria incidence rate occurred in the village 10 to 12 weeks after we observed a pattern of air humidity levels >65%, combined with two or more consecutive rain episodes and a mean wind speed <1.8 m/s; (2) among the three models, the FGLM obtained the best results in terms of prediction; and (3) FGSAM was shown to be a good compromise between FGLM and FGKAM in terms of flexibility and simplicity. The models showed that some meteorological conditions may provide a basis for detection of future outbreaks of malaria. The models developed in this paper are useful for implementing preventive strategies using past meteorological and past malaria incidence.