Hematology and Clinical Chemistry Reference Ranges for Laboratory-Bred Natal Multimammate Mice (Mastomys natalensis)

Laboratory-controlled physiological data for the multimammate rat (Mastomys natalensis) are scarce, despite this species being a known reservoir and vector for zoonotic viruses, including the highly pathogenic Lassa virus, as well as other arenaviruses and many species of bacteria. For this reason, M. natalensis is an important rodent for the study of host-virus interactions within laboratory settings. Herein, we provide basic blood parameters for age- and sex-distributed animals in regards to blood counts, cell phenotypes and serum chemistry of a specific-pathogen-monitored M.natalensis breeding colony, to facilitate scientific insight into this important and widespread rodent species.Peer Reviewe

Population Size and Migration of Anopheles gambiae in the Bancoumana Region of Mali and Their Significance for Efficient Vector Control

We present results of two intensive mark-release-recapture surveys conducted during the wet and dry seasons of 2008 in the villages of Fourda and Kenieroba, Mali. The former is a small fishing village by the Niger River with a moderate to high densities of Anopheles gambiae Giles s.s. (Diptera: Culicidae) throughout the year, while the latter is a large agricultural community 2 km inland that experiences strong seasonal fluctuation in An. gambiae densities. We estimate the population size of female An. gambiae in Fourda to be in less than 3,000 during the dry season. We found evidence of large population size and migration from Fourda in Kenieroba during the wet season, but very low numbers and no sign of migrants during the dry season. We suggest that malaria vector control measures aimed at adult mosquitoes might be made more efficient in this region and other seasonal riparian habitats by targeting disruption of mosquito populations by the river during the dry season. This would decrease the size of an already small population, and would be likely to delay the explosive growth in vector numbers in the larger inland villages as rainfall increases

Detection of Lassa Virus, Mali

To determine whether Lassa virus was circulating in southern Mali, we tested samples from small mammals from 3 villages, including Soromba, where in 2009 a British citizen probably contracted a lethal Lassa virus infection. We report the isolation and genetic characterization of Lassa virus from an area previously unknown for Lassa fever

Spatial distribution of the chromosomal forms of anopheles gambiae in Mali

<p>Abstract</p> <p>Background</p> <p>Maps of the distribution of malaria vectors are useful tools for stratification of malaria risk and for selective vector control strategies. Although the distribution of members of the <it>Anopheles gambiae </it>complex is well documented in Africa, a continuous map of the spatial distribution of the chromosomal forms of <it>An. gambiae s.s. </it>is not yet available at country level to support control efforts.</p> <p>Methods</p> <p>Bayesian geostatistical methods were used to produce continuous maps of the spatial distribution of the chromosomal forms of <it>An. gambiae s.s</it>. (Mopti, Bamako, Savanna and their hybrids/recombinants) based on their relative frequencies in relation to climatic and environmental factors in Mali.</p> <p>Results</p> <p>The maps clearly show that each chromosomal form favours a particular defined eco-climatic zone. The Mopti form prefers the dryer northern Savanna and Sahel and the flooded/irrigated areas of the inner delta of the Niger River. The Savanna form favours the Sudan savanna areas, particularly the South and South-Eastern parts of the country (Kayes and Sikasso regions). The Bamako form has a strong preference for specific environmental conditions and it is confined to the Sudan savanna areas around urban Bamako and the Western part of Sikasso region. The hybrids/recombinants favour the Western part of the country (Kayes region) bordering the Republic of Guinea Conakry.</p> <p>Conclusion</p> <p>The maps provide valuable information for selective vector control in Mali (insecticide resistance management) and may serve as a decision support tool for the basis for future malaria control strategies including genetically manipulated mosquitoes.</p

A comprehensive analysis of drug resistance molecular markers and Plasmodium falciparum genetic diversity in two malaria endemic sites in Mali.

BACKGROUND: Drug resistance is one of the greatest challenges of malaria control programme in Mali. Recent advances in next-generation sequencing (NGS) technologies provide new and effective ways of tracking drug-resistant malaria parasites in Africa. The diversity and the prevalence of Plasmodium falciparum drug-resistance molecular markers were assessed in Dangassa and Nioro-du-Sahel in Mali, two sites with distinct malaria transmission patterns. Dangassa has an intense seasonal malaria transmission, whereas Nioro-du-Sahel has an unstable and short seasonal malaria transmission. METHODS: Up to 270 dried blood spot samples (214 in Dangassa and 56 in Nioro-du-Sahel) were collected from P. falciparum positive patients in 2016. Samples were analysed on the Agena MassARRAY® iPLEX platform. Specific codons were targeted in Pfcrt, Pfmdr1, Pfdhfr, and Pfdhps, Pfarps10, Pfferredoxin, Pfexonuclease and Pfmdr2 genes. The Sanger's 101-SNPs-barcode method was used to assess the genetic diversity of P. falciparum and to determine the parasite species. RESULTS: The Pfcrt_76T chloroquine-resistance genotype was found at a rate of 64.4% in Dangassa and 45.2% in Nioro-du-Sahel (p = 0.025). The Pfdhfr_51I-59R-108N pyrimethamine-resistance genotype was 14.1% and 19.6%, respectively in Dangassa and Nioro-du-Sahel. Mutations in the Pfdhps_S436-A437-K540-A581-613A sulfadoxine-resistance gene was significantly more prevalent in Dangassa as compared to Nioro-du-Sahel (p = 0.035). Up to 17.8% of the isolates from Dangassa vs 7% from Nioro-du-Sahel harboured at least two codon substitutions in this haplotype. The amodiaquine-resistance Pfmdr1_N86Y mutation was identified in only three samples (two in Dangassa and one in Nioro-du-Sahel). The lumefantrine-reduced susceptibility Pfmdr1_Y184F mutation was found in 39.9% and 48.2% of samples in Dangassa and Nioro-du-Sahel, respectively. One piperaquine-resistance Exo_E415G mutation was found in Dangassa, while no artemisinin resistance genetic-background were identified. A high P. falciparum diversity was observed, but no clear genetic aggregation was found at either study sites. Higher multiplicity of infection was observed in Dangassa with both COIL (p = 0.04) and Real McCOIL (p = 0.02) methods relative to Nioro-du-Sahel. CONCLUSIONS: This study reveals high prevalence of chloroquine and pyrimethamine-resistance markers as well as high codon substitution rate in the sulfadoxine-resistance gene. High genetic diversity of P. falciparum was observed. These observations suggest that the use of artemisinins is relevant in both Dangassa and Nioro-du-Sahel

Seasonal Climate Effects Anemotaxis in Newly Emerged Adult Anopheles gambiae Giles in Mali, West Africa

The direction and magnitude of movement by the malaria vector Anopheles gambiae Giles has been of great interest to medical entomologists for over 70 years. This direction of movement is likely to be affected by many factors, from environmental conditions and stage of life history of the mosquito to the existence of attractants in the vicinity. We report here the direction of movement of newly emerged An. gambiae in nature, around the village of Donéguébougou, Mali. We assessed the direction of movement for individual mosquitoes by placing them in a novel enclosure with exit traps oriented in the direction of the cardinal and intermediate points of the compass. We consistently found predominantly Southward directions of movement during 2009 and 2010, with an additional Eastward component during the dry season and a Westward one during the wet season. Our data indicate that wind has an important effect on the direction of movement, but that this effect varied by season: Average directions of movement were downwind during the dry season and upwind during the wet season. A switch in anemotactic response suggests that the direction of movement of An. gambiae relative to the wind immediately after emergence under varying conditions of humidity should be further investigated under controlled conditions

Spatial distribution of malaria transmission in relationship to "Anopheles gambiae" complex members in Sudan savanna and irrigated rice cultivation areas of Mali

Malaria remains a major public health problem that is exacerbated by poor implementation of control measures, and by the spread of drug-resistant parasites and insecticide resistant vectors. Preventive measures, including those targeted at vectors, are one of the four basic elements of the global malaria control strategy. The control methods to use should be selective and specific to the control area. The success of the approach of selective and targeted interventions requires a good stratification of control areas, which should be based on mapping of malaria risk and vector species distribution. The goal of this thesis was to enhance our understanding of the relationship between the distribution of members of Anopheles gambiae complex and climatic and environmental conditions, to describe their spatial and temporal distribution, to quantify their unique contribution to malaria transmission, and to produce attributed malaria risk maps of Mali. We used Bayesian geostatistical modeling, implemented via Markov chain Monte Carlo simulation (MCMC), which can quantify the relationship between environmental factors and the species distribution by taking into account the spatial dependence present in the data in a flexible way that allows simultaneous estimation of all model parameters. In addition, Bayesian kriging enables model-based prediction together with the prediction error, a feature which is not possible in the classical kriging. The analyses described in chapters 2 and 3 identified environmental factors related to the distribution of a) the two major species (An. arabiensis and An. gambiae s.s.) which compose the An. gambiae complex and b) the chromosomal (Bamako, Mopti, Savanna Hybrids) forms of An. gambiae s.s., and produced maps of the geographical distribution of the species and chromosomal forms. Estimation of the contribution of species and chromosomal forms to malaria transmission in Mali is described in Chapter 4; the spatio-temporal distribution of An. gambiae complex densities and its chromosomal (Mopti, Bamako, Savanna, Hybrids) forms in a Sudan savanna village is examined in Chapter 5; the investigation of malaria vector ecology during the dry season and its implication for vector control is described in Chapter 6, and Chapter 7 presents the spatial pattern of malaria transmission in the rice cultivation area of the Office du Niger. The maps produced in chapters 2 & 3 showed higher frequencies of An. arabiensis in the drier Savanna areas and An. gambiae s.s. in the flooded/irrigated areas of the inner delta of Niger river, the southern Savanna, along rivers and in the Sahel. The Mopti form was found in the same ecological area as An. arabiensis. In addition, it occupied the flooded/irrigated areas of the inner delta of Niger River. The Savanna form prefers the Sudan Savanna areas and the Bamako form was confined around Bamako city and in part of Sikasso region (South of Mali). Analyses in Chapter 4 indicated that high malaria risk was associated with insecticide resistance gene (kdr) carriers (Bamako/Savanna chromosomal) and Hybrids compared to the non-carriers An. arabiensis and the Mopti chromosomal form, although the association was not significant. The attributed risk maps of the different species and subspecies indicated that in the middle West and South East part of the country malaria transmission risk is mainly due to An. arabiensis, in the irrigated/flooded areas malaria risk is attributed to the Mopti form, in the southern part to the Savanna/Bamako forms and in the southern areas of the region of Kayes to the hybrids. Thus these results suggest that insecticide control measures must be strengthened in the Sahelian (epidemic prone area) and irrigated/flooded areas where An. arabiensis and the Mopti chromosomal form, which have no or lower frequency of insecticide resistance gene, prevail. Any vector control by means of insecticides in the Southern part of the country, where the S molecular form (Savanna and Bamako) predominates, must be accompanied by a close insecticide resistance monitoring system. The analyses carried out in Chapter 5 and 6 on the spatial distribution of the sibling species of An. gambiae complex in a savanna village showed that the distribution of mosquito densities was concentric with higher densities clustering at the periphery of the village at the beginning of the rainy season and during the dry season. This distribution was patchy during the middle and the end of the rainy season. The chromosomal forms were sympatric throughout the seasons. There was a spatial clustering in their relative frequency distribution changing over time in the village. The Mopti chromosomal form was the most abundant at the beginning and middle of the rainy season and the Bamako form at the end of the rainy season. Larval habitats monitoring showed that in the main village of Bancoumana nearly all larval habitats were human-made, rain-dependent and dried out 10-12 weeks after the end of the rainy season. At the same time, numerous natural puddles highly productive for anopheline larvae even during the dry season were located in the fishermen’s hamlets. These were adjacent to the receding Niger River bed and 5 km away from the main village. Larval habitats in Bancoumana were re-colonized shortly after rainfall suggesting that mosquitoes emerging from the riverbed are an important source for the rain-fed water bodies of Bancoumana. This observation indicates that control interventions targeting the Mopti form should be implemented at the beginning and middle of the rainy season, while those targeting the Bamako form should be done at the end of the rainy season. In addition, appropriate vector control implemented in the fishermen’s hamlet during the dry season and at the periphery of the main village at the beginning of the rainy season may be feasible, sustainable at low cost and may ameliorate malaria transmission in this area. In chapter 7, the analyses of malaria transmission parameters in the rice cultivation area of the Office du Niger indicated a strong spatial correlation in mosquito densities, which is related to the rice cultivation environment. However, the spatial correlation observed in the parous rate (PR) and human blood index (HBI) was weak suggesting that these parameters are more closely related to local conditions such as population behavior and economic status, and/or the presence of animals rather than similar environment over large areas. Since both the PR and HBI measure the vector-human contact rate, and hence the potential for malaria transmission intensity, attention must be paid to the local variations when implementing control strategies in rice cultivation areas. This work makes a substantial contribution to the mapping of the spatial distribution of malaria vector species and subspecies which was previously limited by the lack of field data and appropriate statistical analyses. It also provides valuable information for conventional vector control as well as future implementation for genetically manipulated mosquitoes control method

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\ud 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

“Marche” site, North-West edge of Donéguébougou.

<p>Upper panel, dry season (April 2009); lower panel, wet season (August 2009). Note that the experimental enclosure pictured in the upper panel is not completely ready for the replicate: we always verified that the exit traps were at the same height before the start of the replicate.</p