Prevalence, Distribution, and Development of an Ecological Niche Model of Dermacentor variabilis Ticks Positive for Rickettsia montanensis.

Rickettsia montanensis has long been considered a nonpathogenic member of the spotted fever group rickettsiae. However, the infection potential of R. montanensis is being revisited in light of its recent association with a case of human infection in the United States and the possibility that additional cases may have been misdiagnosed as Rocky Mountain spotted fever. To this end, DNA was extracted from American dog ticks (Dermacentor variabilis) removed from Department of Defense (DoD) personnel and their dependents at DoD medical treatment facilities (MTFs) during 2002-2012 (n = 4792). These 4792 samples were analyzed for the presence of R. montanensis (n = 36; 2.84%) and all vector DNA was confirmed to be of D. variabilis origin using a novel Dermacentor genus-specific quantitative real-time polymerase chain reaction procedure, Derm, and a novel Dermacentor species multilocus sequence typing assay. To assess the risk of R. montanensis infection, the positive and negative samples were geographically mapped utilizing MTF site locations. Tick localities were imported into a geographical information systems (GIS) program, ArcGIS, for mapping and analysis. The ecological niche modeling (ENM) program, Maxent, was used to estimate the probability of tick presence in eastern United States using locations of both R. montanensis-positive and -negative ticks, climate, and elevation data. The ENM for R. montanensis-positive D. variabilis estimated high probabilities of the positive ticks occurring in two main areas, including the northern Midwest and mid-Atlantic portions of the northeastern regions of United States, whereas the R. montanensis-negative D. variabilis tick model showed a wider estimated range. The results suggest that R. montanensis-positive and -negative D. variabilis have different ranges where humans may be at risk and are influenced by similar and different factors.

The AFHSC-Division of GEIS Operations Predictive Surveillance Program: a multidisciplinary approach for the early detection and response to disease outbreaks.

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.

Genetic diversity of equine piroplasms in Greece with a note on speciation within Theileria genotypes (T. equi and T. equi-like).

Equine piroplasms in Greece were studied using the reverse line blot hybridization (RLB) assay. Three genotypes consisting of two Theileria (T. equi and T. equi-like) and one Babesia (B. caballi-like) were identified. Of 787 samples tested, 371 (47.14%) hybridised to catchall probe (probe specifically designed to capture any piroplasm species present in a sample), 346 (43.96%) to T. equi probe, 364 (46.25%) to T. equi-like probe, 0 (0%) to B. caballi probe and 3 (0.38%) to B. caballi-like probe. Seven samples gave faint signals with the catchall probe only, indicating the presence of known or unknown piroplasm species, or a novel genotype or a known genotype occurring at a very low level of parasitemia. A partial sequence (509 bp) of the V4 region of the 18S rRNA gene of a T. equi-like isolate showed only 99% similarity with the reference T. equi-like isolates from Northern Spain from which the detecting probe used in the present study was designed but showed 100% similarity with the T. equi-like variants from Southern Spain. This indicated a noticeable degree of polymorphism within the population of T. equi-like. No unusual parasites previously reported in horses, such as B. canis canis and B. bovis were detected in this study. The values of the bioclimatic variables were very similar between the geographic locations for T. equi and T. equi-like genotypes, suggesting the two are not yet different species as hypothesized by some authors but are possibly undergoing a speciation process within Theileria genotypes. Both T. equi and T. equi-like were found in predominantly forest type land cover.

Geographic distribution modeling and spatial cluster analysis for equine piroplasms in Greece.

Maximum entropy ecological niche modeling and spatial scan statistic were utilized to predict the geographic range and to investigate clusters of infections for equine piroplasms in Greece, using the Maxent and SaTScan programs, respectively. The eastern half of the country represented the culminating area with high probabilities (p>0.75) of presence of equine piroplasms and encompassed most regions with high concentration of equid host populations. The most important environmental factor that contributed to the ecological niche modeling was land cover followed by temperature. Significant clusters (p<0.0001) were detected for Babesia caballi and Theileria equi infections in North and Central regions of Greece, respectively, which have significant equine populations. Maximum entropy ecological niche modeling and spatial scan statistic have proved to be useful tools for the surveillance of animal diseases.

Ecological niche model of Phlebotomus alexandri and P. papatasi (Diptera: Psychodidae) in the Middle East.

BACKGROUND: The 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. RESULTS: For 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. CONCLUSION: While 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.

Predicted geographic ranges for North American sylvatic Trichinella species.

Because of a lack of comprehensive surveys, the geographic distributions of the North American species of encapsulating Trichinella (T. nativa and its variant T6, T. murrelli, and T. spiralis) are poorly characterized in detail. These species are potentially zoonotic; therefore, biogeographic information is critical to monitoring their status and any distribution changes due to climatic and man-made environmental impacts. The maximum entropy (Maxent) program was used to model predicted ranges for these sylvatic Trichinella spp., using a limited number of available location records with confirmed species identifications collected over 55 yr throughout North America. The resulting prediction models were shown to be robust, and the species maps created are presented. The predicted range of T. nativa is primarily north of the 48 degrees - 52 degrees latitudes, overlapping the Tundra, sub-Arctic, and Warm Continental eco-regions. Its sympatric genotypic variant, T6, has a predicted range covering primarily the sub-Arctic and mountainous Temperate Steppe eco-regions, the latter extending below 48 degrees N latitude. In the east, the T6 range includes the Warm Continental and the mountainous Hot Continental eco-regions; the T6 range is also predicted to extend to the Sierra Madre Mountains of Mexico. The most probable range of T. murrelli is centered in the Midwest within the Hot Continental and Prairie eco-regions, with an extension southward to the Subtropical and Tropical/Subtropical Steppe and Desert eco-regions. In the west, it exists in a restricted range characterized as mountainous Mediterranean. The most probable distribution of sylvatic T. spiralis is along the humid east North American coast (Hot Continental south to Subtropical), and along the coast of northwest North America (Marine) to Alaska (subArctic and Tundra). Its most southerly range extends into central Mexico (Tropical/Subtropical Desert). The difference in relative freeze resistance between T. nativa/T6 and T. murrelli undoubtedly accounts for much of this geographic separation. However, the factors responsible for the absence of a more southerly distribution of T. nativa are not obvious, given the overlap in host range with T. murrelli. The maximum July temperature appears to have a significant effect on this distribution pattern. The results of the model building highlight subjects for future research on the biotic and abiotic factors important in determining Trichinella spp. distributions and directions for model validation research.

A cost comparison of two malaria control methods in Kyunggi Province, Republic of Korea, using remote sensing and geographic information systems.

A cost-comparison of two methods for the control of malaria in the Republic of Korea was performed. The cost of larviciding with methoprene granules was estimated at $93.48/hectare. The annual cost of providing chemoprophylaxis was estimated at $37.53/person. Remote sensing and geographic information systems were used to obtain estimates of the size of vector larval habitats around two U.S. Army camps, allowing an estimate of the cost of larviciding around each of the camps. This estimate was compared to the cost of providing chloroquine and primaquine chemoprophylaxis for the camp populations. Costs on each of the camps differed by the size of the larval habitats and the size of the at-risk population. These tools allow extrapolation of larval surveillance data to a regional scale while simultaneously providing site-specific cost analysis, thus reducing the cost and labor associated with vector surveillance over large areas.