[Susceptibility status of Anopheles gambiae sensu lato to insecticides commonly used for malaria control in Mali]. / Susceptibilité d'Anopheles gambiae sensu lato aux insecticides communément utilisés dans la lutte antivectorielle au Mali.

The objective of this work was to monitor the susceptibility of malaria vectors to insecticides in nine sentinel sites of the National Malaria Control Program in Mali. The study was performed during the rainy seasons of 2010 and 2011. WHO bioassays were conducted using F0 and/or F1 from wild collected females. The insecticides used were lambda-cyhalothrin 0.05%, DDT 4%, permethrin 0.75%, deltamethrin 0.05%, bendiocarb 0.1% and fenitrothion 1.0%. Results showed suspicion of resistance to pyrethroids and organochlorine in An. gambiae s.l. at almost all the sites except Yanfolila where the vector was susceptible to lambda-cyhalothrin (98.0%) [CI 95%, 98-99.8] and to DDT (100%). An. gambiae s.l. was susceptible to bendiocarb in five of the sites (Gao, Bougouni, Djenné, Yanfolila, Tombouctou) while there was a suspicion of resistance at the other sites (Kati, Niono, Bandiagara, Kita). Fenitrothion remains efficient except in the rice area of Niono, where there was a suspicion of resistance with a mortality rate of 92% [IC 95% 88.3-94.8]. Thus, it could be used as an alternative insecticide for IRS in Mali. These results show resistance to pyrethroids, the main insecticide family used in public health (and to some extent in agriculture). This could compromise the malaria vector control efforts in Mali where pyrethroids are used for both in bed nets and in IRS.

[Vectorial transmission of malaria in a village along the Niger River and its fishing hamlet (Kéniéroba and Fourda, Mali)]. / Transmission vectorielle du paludisme dans un village du bord du fleuve Niger et son hameau de pêche (Kéniéroba et Fourda, Mali).

A better understanding of malaria transmission dynamics is an essential element in the development of any targeted vector control strategy. The objective of this study was to better understand malaria transmission dynamics along the Niger River in Sudan savanna zone of Mali. Trough cross-sectional surveys, Anopheline larvae were collected by WHO standard dipping technique, and vector adults by Human Landing and pyrethrum spray catches methods. The vector population was composed of An. gambiae s.l. (> 99%) and An. funestus (< 1%). An. gambiae s.l. was composed of 96% and 98% of An. gambiae s.s. respectively in Kéniéroba and Fourda. An. gambiae s.s. was in majority composed of its molecular form M in both locations. The density of An. gambiae s.l was higher in the dry season in the immediate vicinity of the river (fishing hamlet Fourda) compared to farther inland Kéniéroba. The average infection rate of An. gambiae s.l. was 3.63% and 4.06% in Kéniéroba and Fourda respectively. The average entomological inoculation rate (EIR) during the study period was almost similar in Kéniéroba (0.70 infective bites/person/month) and Fourda (0.69 infective bites/person/month). The means EIRs over each of the rainy season 2006 and 2007 were always higher than the one of the dry season 2007 in both localities, with much smaller amplitude in Fourda than in Kéniéroba. However, the level of the transmission was 2.31 (0.37/0.16) times higher in Fourda than in Kéniéroba during the dry season.We conclude that in Sudan savanna zone of Mali, malaria transmission along the river is continuous throughout the year, but it is more intense in the immediate vicinity of the river during the dry season than during the rainy season in opposition to more distant localities to the river and vector control should not be focused only on the rainy in such setting.

Lassa fever in West Africa: evidence for an expanded region of endemicity.

Lassa virus (LASV) is endemic in Sierra Leone, Guinea and Liberia (known as the Mano River region) and Nigeria and Lassa fever cases from these countries are being reported annually. Recent investigations have found evidence for an expanded endemicity zone between the two known Lassa endemic regions indicating that LASV is more widely distributed throughout the Tropical Wooded Savanna ecozone in West Africa.

[Seasonal variability of intestinal helminths and Schistosoma haematobium in a rural area of the Sahel in Mali]. / Variations saisonnières de l'infestation par les helminthes intestinaux et Schistosoma haematobium en zone rurale sahélienne au Mali

OBJECTIVE: The objective of this study was to determine the prevalence of intestinal helminths and Schistosoma haematobium before and after the rainy season in Pongonon, Mali. METHODS: Volunteers aged one year and above were included. The Kato-Katz method was used to detect eggs and cysts in stool samples, and Wattman filtration to detect S. haematobium eggs in urine samples. Two cross-sectional surveys were conducted in July and November 2007. RESULTS: In July (beginning of the rainy season), 304 volunteers were included; 278 were seen again in November (at the end of the rainy season). We found more intestinal helminths at the end of the rainy season (8.3%) compared to the beginning of the season (2.9%) (P = 0.01). There was no infection with S. haematobium in July but 7.6% in November (P < 0.001). The prevalence of intestinal helminths in children and adults was similar (P > 0.05), but the prevalence of infection with S. haematobium was higher in children aged 6 to 16 years (17/153) than in adults (2/74) (P = 0.02). CONCLUSION: Infections with helminth and S. Haematobium were both more prevalent at the end of the rainy season. Adults were infected as well as children and may constitute potential reservoirs of parasites. Effective control of these parasitic infections requires mass drug administration programs that take place during the seasons of high parasite egg excretion and that also include adult populations in some areas.

Seasonality of childhood infectious diseases in Niono, Mali.

Common childhood diseases vary seasonally in Mali, much of the Sahel, and other parts of the world, yet patterns for multiple diseases have rarely been simultaneously described for extended periods at single locations. In this retrospective longitudinal (1996-2004) investigation, we studied the seasonality of malaria, acute respiratory infection and diarrhoea time-series in the district of Niono, Sahelian Mali. We extracted and analysed seasonal patterns from each time-series with the Multiplicative Holt-Winters and Wavelet Transform methods. Subsequently, we considered hypothetical scenarios where successful prevention and intervention measures reduced disease seasonality by 25 or 50% to assess the impact of health programmes on annual childhood morbidity. The results showed that all three disease time-series displayed remarkable seasonal stability. Malaria, acute respiratory infection and diarrhoea peaked in December, March (and September) and August, respectively. Finally, the annual childhood morbidity stemming from each disease diminished 7-26% in the considered hypothetical scenarios. We concluded that seasonality may assist with guiding the development of integrated seasonal disease calendars for programmatic child health promotion activities.

The spatial distribution of Anopheles gambiae sensu stricto and An. arabiensis (Diptera: Culicidae) in Mali.

Variations in the biology and ecology and the high level of genetic polymorphism of malaria vectors in Africa highlight the value of mapping their spatial distribution to enhance successful implementation of integrated vector management. The objective of this study was to collate data on the relative frequencies of Anopheles gambiae s.s. and An. arabiensis mosquitoes in Mali, to assess their association with climate and environmental covariates, and to produce maps of their spatial distribution. Bayesian geostatistical logistic regression models were fitted to identify environmental determinants of the relative frequencies of An. gambiae s.s. and An. arabiensis species and to produce smooth maps of their geographical distribution. The frequency of An. arabiensis was positively associated with the normalized difference vegetation index, the soil water storage index, the maximum temperature and the distance to water bodies. It was negatively associated with the minimum temperature and rainfall. The predicted map suggests that, in West Africa, An. arabiensis is concentrated in the drier savannah areas, while An. gambiae s.s. prefers the southern savannah and land along the rivers, particularly the inner delta of Niger. Because the insecticide knockdown resistance (kdr) gene is reported only in An. gambiae s.s. in Mali, the maps provide valuable information for vector control. They may also be useful for planning future implementation of malaria control by genetically manipulated mosquitoes.

Malaria mapping using transmission models: application to survey data from Mali.

Geographic mapping of the distribution of malaria is complicated by the limitations of the available data. The most widely available data are from prevalence surveys, but these surveys are generally carried out at arbitrary locations and include nonstandardized and overlapping age groups. To achieve comparability between different surveys, the authors propose the use of transmission models, particularly the Garki model, to convert heterogeneous age prevalence data to a common scale of estimated entomological inoculation rates, vectorial capacity, or force of infection. They apply this approach to the analysis of survey data from Mali, collected in 1965-1998, extracted from the Mapping Malaria Risk in Africa database. They use Bayesian geostatistical models to produce smooth maps of estimates of the entomological inoculation rates obtained from the Garki model, allowing for the effect of environmental covariates. Again using the Garki model, they convert kriged entomological inoculation rates values to age-specific malaria prevalence. The approach makes more efficient use of the available data than do previous malaria mapping methods, and it produces highly plausible maps of malaria distribution.

Bayesian modelling of geostatistical malaria risk data.

Bayesian geostatistical models applied to malaria risk data quantify the environment-disease relations, identify significant environmental predictors of malaria transmission and provide model-based predictions of malaria risk together with their precision. These models are often based on the stationarity assumption which implies that spatial correlation is a function of distance between locations and independent of location. We relax this assumption and analyse malaria survey data in Mali using a Bayesian non-stationary model. Model fit and predictions are based on Markov chain Monte Carlo simulation methods. Model validation compares the predictive ability of the non-stationary model with the stationary analogue. Results indicate that the stationarity assumption is important because it influences the significance of environmental factors and the corresponding malaria risk maps.

Patterns of irrigated rice growth and malaria vector breeding in Mali using multi-temporal ERS-2 synthetic aperture radar.

We explored the use of the European Remote Sensing Satellite 2 Synthetic Aperture Radar (ERS-2 SAR) to trace the development of rice plants in an irrigated area near Niono, Mali and relate that to the density of anopheline mosquitoes, especially An. gambiae. This is important because such mosquitoes are the major vectors of malaria in sub-Saharan Africa, and their development is often coupled to the cycle of rice development. We collected larval samples, mapped rice fields using GPS and recorded rice growth stages simultaneously with eight ERS-2 SAR acquisitions. We were able to discriminate among rice growth stages using ERS-2 SAR backscatter data, especially among the early stages of rice growth, which produce the largest numbers of larvae. We could also distinguish between basins that produced high and low numbers of anophelines within the stage of peak production. After the peak, larval numbers dropped as rice plants grew taller and thicker, reducing the amount of light reaching the water surface. ERS-2 SAR backscatter increased concomitantly. Our data support the belief that ERS-2 SAR data may be helpful for mapping the spatial patterns of rice growth, distinguishing different agricultural practices, and monitoring the abundance of vectors in nearby villages.

Mapping rice field anopheline breeding habitats in Mali, West Africa, using Landsat ETM+ sensor data.

The aim of this study was to determine whether remotely sensed data could be used to identify rice-related malaria vector breeding habitats in an irrigated rice growing area near Niono, Mali. Early stages of rice growth show peak larval production, but Landsat sensor data are often obstructed by clouds during the early part of the cropping cycle (rainy season). In this study, we examined whether a classification based on two Landsat Enhanced Thematic Mapper (ETM)+ scenes acquired in the middle of the season and at harvesting times could be used to map different land uses and rice planted at different times (cohorts), and to infer which rice growth stages were present earlier in the season. We performed a maximum likelihood supervised classification and evaluated the robustness of the classifications with the transformed divergence separability index, the kappa coefficient and confusion matrices. Rice was distinguished from other land uses with 98% accuracy and rice cohorts were discriminated with 84% accuracy (three classes) or 94% (two classes). Our study showed that optical remote sensing can reliably identify potential malaria mosquito breeding habitats from space. In the future, these 'crop landscape maps' could be used to investigate the relationship between cultivation practices and malaria transmission.

An empirical malaria distribution map for West Africa.

The objective of this study was to produce a malaria distribution map that would constitute a useful tool for development and health planners in West Africa. The recently created continental database of malaria survey results (MARA/ARMA 1998) provides the opportunity for producing empirical models and maps of malaria distribution at a regional and eventually at a continental level. This paper reports on the mapping of malaria distribution for sub-Saharan West Africa based on these data. The strategy was to undertake a spatial statistical analysis of malaria parasite prevalence in relation to those potential bio-physical environmental factors involved in the distribution of malaria transmission intensity which are readily available at any map location. The resulting model was then used to predict parasite prevalence for the whole of West Africa. We also produced estimates of the proportion of population of each country in the region exposed to various categories of risk to show the impact that malaria is having on individual countries. The data represent a very large sample of children in West Africa. It constitutes a first attempt to produce a malaria risk map of the West African region, based entirely on malariometric data. We anticipate that it will provide useful additional guidance to control programme managers, and that it can be refined once sufficient additional data become available.