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Abstract Background Anopheles arabiensis is a particularly opportunistic feeder and efficient vector of Plasmodium falciparum in Africa and may invade areas outside its normal range, including areas separated by expanses of barren desert. The purpose of this paper is to demonstrate how spatial models can project future irrigated cropland and potential, new suitable habitat for vectors such as An. arabiensis. Methods Two different but complementary spatial models were linked to demonstrate their synergy for assessing re-invasion potential of An. arabiensis into Upper Egypt as a function of irrigated cropland expansion by 2050. The first model (The Land Change Modeler) was used to simulate changes in irrigated cropland using a Markov Chain approach, while the second model (MaxEnt) uses species occurrence points, land cover and other environmental layers to project probability of species presence. Two basic change scenarios were analysed, one involving a more conservative business-as-usual (BAU) assumption and second with a high probability of desert-to-cropland transition (Green Nile) to assess a broad range of potential outcomes by 2050. Results The results reveal a difference of 82,000 sq km in potential An. arabiensis range between the BAU and Green Nile scenarios. The BAU scenario revealed a highly fragmented set of small, potential habitat patches separated by relatively large distances (maximum distance = 64.02 km, mean = 12.72 km, SD = 9.92), while the Green Nile scenario produced a landscape characterized by large patches separated by relatively shorter gaps (maximum distance = 49.38, km, mean = 4.51 km, SD = 7.89) that may be bridged by the vector. Conclusions This study provides a first demonstration of how land change and species distribution models may be linked to project potential changes in vector habitat distribution and invasion potential. While gaps between potential habitat patches remained large in the Green Nile scenario, the models reveal large areas of future habitat connectivity that may facilitate the re-invasion of An. arabiensis from Sudan into Upper Egypt. The methods used are broadly applicable to other land cover changes as they influence vector distribution, particularly those related to tropical deforestation and urbanization processes.

Abstract Background Anopheles albimanus is among the most important vectors of human malaria in Mesoamerica and the Caribbean Basin (M-C). Here, we use topographic data and 1950–2000 climate (near present), and future climate (2080) layers obtained from general circulation models (GCMs) to project the probability of the species’ presence, p(s), using the species distribution model MaxEnt. Results The projected near-present distribution parameterized with 314 presence points related well to the known geographic distribution in the study region. Different model experiments suggest that the range of An. albimanus based on near-present climate surfaces covered at least 1.27 million km2 in the M-C, although 2080 range was projected to decrease to 1.19 million km2. Modeled p(s) was generally highest in Mesoamerica where many of the original specimens were collected. MaxEnt projected near-present maximum elevation at 1,937 m whereas 2080 maximum elevation was projected at 2,118 m. 2080 climate scenarios generally showed increased p(s) in Mesoamerica, although results varied for northern South America and no major range expansion into the mid-latitudes was projected by 2080. Conclusions MaxEnt experiments with near present and future climate data suggest that An. albimanus is likely to invade high-altitude (>2,000 m) areas by 2080 and therefore place many more people at risk of malaria in the M-C region even though latitudinal range expansion may be limited.

Abstract Background Geographic profiling is a statistical tool originally developed in criminology to prioritise large lists of suspects in cases of serial crime. Here, we use two data sets - one historical and one modern - to show how it can be used to locate the sources of infectious disease. Results First, we re-analyse data from a classic epidemiological study, the 1854 London cholera outbreak. Using 321 disease sites as input, we evaluate the locations of 13 neighbourhood water pumps. The Broad Street pump - the outbreak's source- ranks first, situated in the top 0.2% of the geoprofile. We extend our study with an analysis of reported malaria cases in Cairo, Egypt, using 139 disease case locations to rank 59 mosquitogenic local water sources, seven of which tested positive for the vector Anopheles sergentii. Geographic profiling ranks six of these seven sites in positions 1-6, all in the top 2% of the geoprofile. In both analyses the method outperformed other measures of spatial central tendency. Conclusions We suggest that geographic profiling could form a useful component of integrated control strategies relating to a wide variety of infectious diseases, since evidence-based targeting of interventions is more efficient, environmentally friendly and cost-effective than untargeted intervention.

We evaluated how the presence of sugar sources impacted the distribution of Aedes aegypti in different habitats in Durán, Ecuador. Land cover and normalized difference vegetation index maps were used to guide a random point sampling routine to select study grids (30 m x 30 m) in low vegetation (LV) and high vegetation (HV). Five individual plants, at one home in the LV and HV grid, were treated with a different colored, non-attractive, 60% sucrose solution to determine mosquito feeding and movement. Sugar alone is not attractive to mosquitoes, so spraying vegetation with a dyed sugar solution can be used for visual determination of sugar feeding. Outdoor collections using BG sentinel traps and indoor collections using aspirators were conducted at the treatment home and with collection points at 20, 40, and 60 m surrounding the treatment home for three consecutive days. A total of 3,245 mosquitoes in two genera, Aedes and Culex, was collected. The proportion of stained Ae. aegypti females was 56.8% (510/898) and 0% for males. For Culex, 63.9% (248/388) females and 36.1% (140/388) males were collected stained. Aedes aegypti and Culex spp. were found up to 60 m stained in both LV and HV grids. Significantly more stained females Ae. aegypti were found inside homes compared to females and males of Culex spp. in both habitats. This study identifies that outdoor sugar feeding is a common behavior of Ae. aegypti and can be targeted as a control strategy in urban habitats in Latin America. [ABSTRACT FROM AUTHOR]

Background The Middle East North Africa (MENA) region is under continuous threat of the re-emergence of West Nile virus (WNV) and Rift Valley Fever virus (RVF), two pathogens transmitted by the vector species Culex pipiens. Predicting areas at high risk for disease transmission requires an accurate model of vector distribution, however, most Cx. pipiens distribution modeling has been confined to temperate, forested habitats. Modeling species distributions across a heterogeneous landscape structure requires a flexible modeling method to capture variation in mosquito response to predictors as well as occurrence data points taken from a sufficient range of habitat types. Methods We used presence-only data from Egypt and Lebanon to model the population distribution of Cx. pipiens across a portion of the MENA that also encompasses Jordan, Syria, and Israel. Models were created with a set of environmental predictors including bioclimatic data, human population density, hydrological data, and vegetation indices, and built using maximum entropy (Maxent) and boosted regression tree (BRT) methods. Models were created with and without the inclusion of human population density. Results Predictions of Maxent and BRT models were strongly correlated in habitats with high probability of occurrence (Pearson's r = 0.774, r = 0.734), and more moderately correlated when predicting into regions that exceeded the range of the training data (r = 0.666,r = 0.558). All models agreed in predicting high probability of occupancy around major urban areas, along the banks of the Nile, the valleys of Israel, Lebanon, and Jordan, and southwestern Saudi Arabia. The most powerful predictors of Cx. pipiens habitat were human population density (60.6% Maxent models, 34.9% BRT models) and the seasonality of the enhanced vegetation index (EVI) (44.7% Maxent, 16.3% BRT). Maxent models tended to be dominated by a single predictor. Areas of high probability corresponded with sites of independent surveys or previous disease outbreaks. Conclusions Cx. pipiens occurrence was positively associated with areas of high human population density and consistent vegetation cover, but was not significantly driven by temperature and rainfall, suggesting human-induced habitat change such as irrigation and urban infrastructure has a greater influence on vector distribution in this region than in temperate zones. [ABSTRACT FROM AUTHOR]