Obesity prevalence in the United States is inversely associated with elevation and urbanization, after adjusting for temperature, diet, physical activity, smoking and demographic factors.

Background Culex tritaeniorhynchus is the primary vector of Japanese encephalitis virus (JEV), a leading cause of encephalitis in Asia. JEV is transmitted in an enzootic cycle involving large wading birds as the reservoirs and swine as amplifying hosts. The development of a JEV vaccine reduced the number of JE cases in regions with comprehensive childhood vaccination programs, such as in Japan and the Republic of Korea. However, the lack of vaccine programs or insufficient coverage of populations in other endemic countries leaves many people susceptible to JEV. The aim of this study was to predict the distribution of Culex tritaeniorhynchus using ecological niche modeling.Methods/Principal FindingsAn ecological niche model was constructed using the Maxent program to map the areas with suitable environmental conditions for the Cx. tritaeniorhynchus vector. Program input consisted of environmental data (temperature, elevation, rainfall) and known locations of vector presence resulting from an extensive literature search and records from MosquitoMap. The statistically significant Maxent model of the estimated probability of Cx. tritaeniorhynchus presence showed that the mean temperatures of the wettest quarter had the greatest impact on the model. Further, the majority of human Japanese encephalitis (JE) cases were located in regions with higher estimated probability of Cx. tritaeniorhynchus presence.Conclusions/SignificanceOur ecological niche model of the estimated probability of Cx. tritaeniorhynchus presence provides a framework for better allocation of vector control resources, particularly in locations where JEV vaccinations are unavailable. Furthermore, this model provides estimates of vector probability that could improve vector surveillance programs and JE control efforts.

Satellite imagery of northern Belize is used to examine the relationship between land use and habitats of the malaria vector, the Anopheles mosquito. A land cover classification based on multispectral Système Probatoire d'Observation de la Terra (SPOT) and multitemporal Radarsat images identified 11 land cover classes, including agricultural, forest, and marsh types. Two of the land cover types, Typha domingensis marsh and flooded forest, are habitats of immature Anopheles vestitipennis, and one, Eleocharis spp. marsh, is the habitat for immature Anopheles albimanus. Geographic information systems (GIS) analyses of land cover demonstrate that the amount of Typha domingensis in a marsh is positively correlated with the amount of agricultural land in the adjacent upland and negatively correlated with the amount of adjacent forest. This finding, coupled with field studies documenting higher soil phosphorus in wetlands adjacent to agricultural fields, supports the hypothesis that nutrient runoff is the cause of higher densities of Typha domingensis in marshes adjacent to fields in northern Belize. Thus, agricultural activities can potentially increase Anopheles vestitipennis habitat and thereby increase malaria risk across a broad region where Anopheles vestitipennis is a malaria vector.

BackgroundThe purpose of this study is to create distribution models of two sand fly species, Phlebotomus papatasi (Scopoli) and P. alexandri (Sinton), across the Middle East. Phlebotomus alexandri is a vector of visceral leishmaniasis, while P. papatasi is a vector of cutaneous leishmaniasis and sand fly fever. Collection records were obtained from literature reports from 1950 through 2007 and unpublished field collection records. Environmental layers considered in the model were elevation, precipitation, land cover, and WorldClim bioclimatic variables. Models were evaluated using the threshold-independent area under the curve (AUC) receiver operating characteristic analysis and the threshold-dependent minimum training presence.ResultsFor both species, land cover was the most influential environmental layer in model development. The bioclimatic and elevation variables all contributed to model development; however, none influenced the model as strongly as land cover.ConclusionWhile not perfect representations of the absolute distribution of P. papatasi and P. alexandri, these models indicate areas with a higher probability of presence of these species. This information could be used to help guide future research efforts into the ecology of these species and epidemiology of the pathogens that they transmit.

BackgroundCurrent efforts are underway to quantify the chemical concentration in a treated air space that elicits a spatial repellent (deterrent) response in a vector population. Such information will facilitate identifying the optimum active ingredient (AI) dosage and intervention coverage important for the development of spatial repellent tools – one of several novel strategies being evaluated for vector-borne disease control. This study reports initial findings from air sampling experiments conducted under field conditions to describe the relationship between air concentrations of repellent AIs and deterrent behavior in the dengue vector, Aedes aegypti.MethodsAir samples were taken inside and outdoors of experimental huts located in Pu Tuey Village, Kanchanaburi Province, Thailand in conjunction with mosquito behavioral evaluations. A mark-release-recapture study design using interception traps was used to measure deterrency of Ae. aegypti against 0.00625% metofluthrin coils and DDT-treated fabric (2g/m2) within separate experimental trials. Sentinel mosquito cohorts were positioned adjacent to air sampling locations to monitor knock down responses to AI within the treated air space. Air samples were analyzed using two techniques: the U.S. Environmental Protection Agency (USEPA) Compendium Method TO-10A and thermal desorption (TD).ResultsBoth the USEPA TO-10A and TD air sampling methods were able to detect and quantify volatized AIs under field conditions. Air samples indicated concentrations of both repellent chemicals below thresholds required for toxic responses (mortality) in mosquitoes. These concentrations elicited up to a 58% and 70% reduction in Ae. aegypti entry (i.e., deterrency) into treated experimental huts using metofluthrin coils and DDT-treated fabric, respectively. Minimal knock down was observed in sentinel mosquito cohorts positioned adjacent to air sampling locations during both chemical evaluations.ConclusionsThis study is the first to describe two air sampling methodologies that are appropriate for detecting and quantifying repellent chemicals within a treated air space during mosquito behavior evaluations. Results demonstrate that the quantity of AI detected by the mosquito vector, Ae. aegypti, that elicits repellency is far lower than that needed for toxicity. These findings have important implications for evaluation and optimization of new vector control tools that function through mosquito behavior modification as opposed to mortality.

BackgroundJapanese encephalitis virus (JEV), the causative agent of Japanese encephalitis (JE), is endemic to the Republic of Korea (ROK) where unvaccinated United States (U.S.) military Service members, civilians and family members are stationed. The primary vector of the JEV in the ROK is Culex tritaeniorhynchus. The ecological relationship between Culex spp. and rice fields has been studied extensively; rice fields have been shown to increase the prevalence of Cx. tritaeniorhynchus. This research was conducted to determine if the quantification of rice field land cover surrounding U.S. military installations in the ROK should be used as a parameter in a larger risk model that predicts the abundance of Cx. tritaeniorhynchus populations.Mosquito data from the U.S. Forces Korea (USFK) mosquito surveillance program were used in this project. The average number of female Cx. tritaeniorhynchus collected per trap night for the months of August and September, 2002-2008, was calculated. Rice fields were manually digitized inside 1.5 km buffer zones surrounding U.S. military installations on high-resolution satellite images, and the proportion of rice fields was calculated for each buffer zone.ResultsMosquito data collected from seventeen sample sites were analyzed for an association with the proportion of rice field land cover. Results demonstrated that the linear relationship between the proportion of rice fields and mosquito abundance was statistically significant (R2 = 0.62, r = .79, F = 22.72, p < 0.001).ConclusionsThe analysis presented shows a statistically significant linear relationship between the two parameters, proportion of rice field land cover and log10 of the average number of Cx. tritaeniorhynchus collected per trap night. The findings confirm that agricultural land cover should be included in future studies to develop JE risk prediction models for non-indigenous personnel living at military installations in the ROK.

Anthropogenic land use changes often alter natural patterns of disease transmission. The goal of this study was to determine whether phosphorus input from sugarcane, Saccharum officinarum L., cultivation in northern Belize could pose a significant environmental impact on malaria transmission by changing vegetation structure and composition of wetlands and associated larval habitats. Our primary focus was on the increased dominance of cattail, Typha domingensis Pers., a favored habitat for Anopheles vestitipennis Dyar & Knab. A land cover classification based on satellite imagery was used to select 20 marshes impacted by agricultural runoff and 20 marshes surrounded by forest (nonimpacted). A 100-m transect was established into each of the 40 marshes. Water, vegetation, and larval sampling were conducted at the 0-, 10-, 25-, 50-, and 100-m locations along the transect. Analyses of larval density data indicated that Anopheles albimanus Wiedemann was negatively correlated with percentage of cover of Typha (R2 = 0.39, P < 0.001) but positively correlated with sparse Eleocharis cellulosa Torr. (rush) cover (R2 = 0.19, P < 0.05) and presence of cyanobacterial mats (CBM) (R2 = 0.33, P < 0.0001). An. vestitipennis was found to be positively correlated with percentage of cover of Typha (R2 = 0.19, P < 0.001). Canonical correspondence analysis identified CBM and light as the variables associated with the presence of An. albimanuts larvae, Typha cover with An. vestitipennis larvae, and Eleocharis and absence of light with Anopheles crucians (Wiedemann). A positive correlation also existed between marshes adjacent to agricultural activities and presence of An. vestitipennis (R2 = 0.37, P < 0.05). These results indicate that marshes in proximity to agricultural fields are conducive for Typha growth, thereby providing habitat for the more efficient malaria vector

The Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System Operations (AFHSC-GEIS) initiated a coordinated, multidisciplinary program to link data sets and information derived from eco-climatic remote sensing activities, ecologic niche modeling, arthropod vector, animal disease-host/reservoir, and human disease surveillance for febrile illnesses, into a predictive surveillance program that generates advisories and alerts on emerging infectious disease outbreaks. The program’s ultimate goal is pro-active public health practice through pre-event preparedness, prevention and control, and response decision-making and prioritization. This multidisciplinary program is rooted in over 10 years experience in predictive surveillance for Rift Valley fever outbreaks in Eastern Africa. The AFHSC-GEIS Rift Valley fever project is based on the identification and use of disease-emergence critical detection points as reliable signals for increased outbreak risk. The AFHSC-GEIS predictive surveillance program has formalized the Rift Valley fever project into a structured template for extending predictive surveillance capability to other Department of Defense (DoD)-priority vector- and water-borne, and zoonotic diseases and geographic areas. These include leishmaniasis, malaria, and Crimea-Congo and other viral hemorrhagic fevers in Central Asia and Africa, dengue fever in Asia and the Americas, Japanese encephalitis (JE) and chikungunya fever in Asia, and rickettsial and other tick-borne infections in the U.S., Africa and Asia.