The leishmaniases are vector-borne diseases that have a broad global distribution throughout much of the Americas, Africa, and Asia. Despite representing a significant public health burden, our understanding of the global distribution of the leishmaniases remains vague, reliant upon expert opinion and limited to poor spatial resolution. A global assessment of the consensus of evidence for leishmaniasis was performed at a sub-national level by aggregating information from a variety of sources. A database of records of cutaneous and visceral leishmaniasis occurrence was compiled from published literature, online reports, strain archives, and GenBank accessions. These, with a suite of biologically relevant environmental covariates, were used in a boosted regression tree modelling framework to generate global environmental risk maps for the leishmaniases. These high-resolution evidence-based maps can help direct future surveillance activities, identify areas to target for disease control and inform future burden estimation efforts.

/pdf/global-distribution-maps-of-the-leishmaniases-438vfc4cru.pdf

Global distribution maps of the leishmaniases

OBJECTIVE: To predict the spatial distributions of Schistosoma haematobium and S. mansoni infections to assist planning the implementation of mass distribution of praziquantel as part of an on-going national control programme in Tanzania. METHODS: Bayesian geostatistical models were developed using parasitological data from 143 schools. RESULTS: In the S. haematobium models, although land surface temperature and rainfall were significant predictors of prevalence, they became non-significant when spatial correlation was taken into account. In the S. mansoni models, distance to water bodies and annual minimum temperature were significant predictors, even when adjusting for spatial correlation. Spatial correlation occurred over greater distances for S. haematobium than for S. mansoni. Uncertainties in predictions were examined to identify areas requiring further data collection before programme implementation. CONCLUSION: Bayesian geostatistical analysis is a powerful and statistically robust tool for identifying high prevalence areas in a heterogeneous and imperfectly known environment.

http://www.thiswormyworld.org/sites/www.thiswormyworld.org/files/Schisto_Control_Tanzania_0.pdf

Bayesian spatial analysis and disease mapping: tools to enhance planning and implementation of a schistosomiasis control programme in Tanzania

Spatio-temporal modelling of the distributions of the leishmaniases and their sandfly vectors is reviewed in relation to climate change. Many leishmaniases are rural zoonoses, and so there is a foundation of descriptive ecology and qualitative risk assessment. Dogs are widespread reservoir hosts of veterinary importance. Recent statistical modelling has not always produced novel general conclusions, exemplifying the difficulty of applying models outside the original geographical region. Case studies are given for transmission cycles involving both cutaneous and visceral leishmaniasis in the Old World and the Americas. An important challenge is to integrate statistical spatial models based mainly on climate with more explanatory biological models. Ecological niche models pose difficulties because of the number of assumptions. A positive association has been reported between the El Nino cycle and the annual incidence of visceral leishmaniasis in Brazil, but more basic research is needed before tackling other climate-change scenarios, including leishmaniasis emergence in northern Europe.

https://web.oie.int/boutique/extrait/11ready399412.pdf

Leishmaniasis emergence and climate change.

Worldwide risk factors in leishmaniasis

The risk of transmission of West Nile virus (WNV) to humans is associated with the density of infected vector mosquitoes in a given area. Current technology for estimating vector distribution and abundance is primarily based on Centers for Disease Control and Prevention (CDC) light trap collections, which provide only point data. In order to estimate mosquito abundance in areas not sampled by traps, we developed logistic regression models for five mosquito species implicated as the most likely vectors of WNV in Connecticut. Using data from 32 traps in Fairfield County from 2001 to 2003, the models were developed to predict high and low abundance for every 30 x 30 m pixel in the County. They were then tested with an independent dataset from 16 traps in adjacent New Haven County. Environmental predictors of abundance were extracted from remotely sensed data. The best predictive models included non-forested areas for Culex pipiens, surface water and distance to estuaries for Cx. salinarius, surface water and grasslands/agriculture for Aedes vexans and seasonal difference in the normalized difference vegetation index and distance to palustrine habitats for Culiseta melanura. No significant predictors were found for Cx. restuans. The sensitivity of the models ranged from 75% to 87.5% and the specificity from 75% to 93.8%. In New Haven County, the models correctly classified 81.3% of the traps for Cx. pipiens, 75.0% for Cx. salinarius, 62.5% for Ae. vexans, and 75.0% for Cs. melanura. Continuous surface maps of habitat suitability were generated for each species for both counties, which could contribute to future surveillance and intervention activities.

Modeling the Spatial Distribution of Mosquito Vectors for West Nile Virus in Connecticut, USA

Visceral leishmaniasis (VL) is a vector-borne disease highly influenced by environmental factors. A model was developed for mapping the distribution and incidence of VL in Gedaref State, eastern Sudan, in relation to different environmental factors. Geographical information systems (GIS) were used to extract and map regression results for environmental variables of 190 villages in Gedaref State, including rainfall, vegetation status, soil type, altitude, distance from river, topography, wetness indexes, and average rainfall estimates. VL incidence in each village was calculated from hospital records. By use of logistic and linear multivariate regression analyses, models were developed to determine which environmental factors explain variability in VL presence and incidence. We found that average rainfall and the altitude were the best predictors of VL incidence. The resulting models were mapped by GIS software predicting both VL presence or absence and incidence at any locality in Gedaref State. The results are discussed in relation to VL control.

Risk mapping of visceral leishmaniasis: The role of local variation in rainfall and altitude on the presence and incidence of Kala-Azar in eastern Sudan

Background 
Phlebotomus orientalis is a vector of Leishmania donovani, the causative agent of life threatening visceral leishmaniasis spread in Eastern Africa. During blood-feeding, sand fly females salivate into the skin of the host. Sand fly saliva contains a large variety of proteins, some of which elicit specific antibody responses in the bitten hosts. To evaluate the exposure to sand fly bites in human populations from disease endemic areas, we tested the antibody reactions of volunteers' sera against recombinant P. orientalis salivary antigens.


Methodology/Principal findings 
Recombinant proteins derived from sequence data on P. orientalis secreted salivary proteins, were produced using either bacterial (five proteins) or mammalian (four proteins) expression systems and tested as antigens applicable for detection of anti-P. orientalis IgG in human sera. Using these recombinant proteins, human sera from Sudan and Ethiopia, countries endemic for visceral leishmaniasis, were screened by ELISA and immunoblotting to identify the potential markers of exposure to P. orientalis bites. Two recombinant proteins; mAG5 and mYEL1, were identified as the most promising antigens showing high correlation coefficients as well as good specificity in comparison to the whole sand fly salivary gland homogenate. Combination of both proteins led to a further increase of correlation coefficients as well as both positive and negative predictive values of P. orientalis exposure.


Conclusions/Significance 
This is the first report of screening human sera for anti-P. orientalis antibodies using recombinant salivary proteins. The recombinant salivary proteins mYEL1 and mAG5 proved to be valid antigens for screening human sera from both Sudan and Ethiopia for exposure to P. orientalis bites. The utilization of equal amounts of these two proteins significantly increased the capability to detect anti-P. orientalis antibody responses.

/pdf/human-antibody-reaction-against-recombinant-salivary-3498qecduu.pdf

Human antibody reaction against recombinant salivary proteins of Phlebotomus orientalis in Eastern Africa.

Background
Simulium damnosum sensu lato (s.l.) blackflies transmit Onchocerca volvulus, a filarial nematode that causes human onchocerciasis. Human landing catches (HLCs) is currently the sole method used to estimate blackfly biting rates but is labour-intensive and questionable on ethical grounds. A potential alternative is to measure host antibodies to vector saliva deposited during bloodfeeding. In this study, immunoassays to quantify human antibody responses to S. damnosum s.l. saliva were developed, and the salivary proteome of S. damnosum s.l. was investigated.

Methodology/Principal findings
Blood samples from people living in onchocerciasis-endemic areas in Ghana were collected during the wet season; samples from people living in Accra, a blackfly-free area, were considered negative controls and compared to samples from blackfly-free locations in Sudan. Blackflies were collected by HLCs and dissected to extract their salivary glands. An ELISA measuring anti-S. damnosum s.l. salivary IgG and IgM was optimized and used to quantify the humoral immune response of 958 individuals. Both immunoassays differentiated negative controls from endemic participants. Salivary proteins were separated by gel-electrophoresis, and antigenic proteins visualized by immunoblot. Liquid chromatography mass spectrometry (LC–MS/MS) was performed to characterize the proteome of S. damnosum s.l. salivary glands. Several antigenic proteins were recognized, with the major ones located around 15 and 40 kDa. LC–MS/MS identified the presence of antigen 5-related protein, apyrase/nucleotidase, and hyaluronidase.

Conclusions/Significance
This study validated for the first time human immunoassays that quantify humoral immune responses as potential markers of exposure to blackfly bites. These assays have the potential to facilitate understanding patterns of exposure as well as evaluating the impact of vector control on biting rates. Future studies need to investigate seasonal fluctuations of these antibody responses, potential cross-reactions with other bloodsucking arthropods, and thoroughly identify the most immunogenic proteins.

/pdf/human-immune-response-against-salivary-antigens-of-simulium-5bi7imhcck.pdf

Human immune response against salivary antigens of Simulium damnosum s.l.: A new epidemiological marker for exposure to blackfly bites in onchocerciasis endemic areas.

Maha E. Osman

Papers

Risk mapping of visceral leishmaniasis: The role of local variation in rainfall and altitude on the presence and incidence of Kala-Azar in eastern Sudan

Human antibody reaction against recombinant salivary proteins of Phlebotomus orientalis in Eastern Africa.

Human immune response against salivary antigens of Simulium damnosum s.l.: A new epidemiological marker for exposure to blackfly bites in onchocerciasis endemic areas.