Anthrax, caused by the spore-forming bacterium Bacillus anthracis, is a zoonotic disease that affects humans and animals throughout the world. In North America, anthrax outbreaks occur in livestock and wildlife species. Vaccine administration in wildlife is untenable; the most effective form of management is surveillance and decontamination of carcasses. Successful management is critical because untreated carcasses can create infectious zones increasing risk for other susceptible hosts. We studied the bacterium in a re-emerging anthrax zone in southwest Montana. In 2008, a large anthraxepizootic primarily affected a domestic bison (Bison bison) herd and the male segment of a free-ranging elk (Cervus elaphus) herd in southwestern Montana. Following the outbreak, we initiated a telemetry study on elk to evaluate resource selection during the anthrax season to assist with anthrax management. We used a mixed effects generalized linear model (GLM) to estimate resource selection by male elk, and we mapped habitat preferences across the landscape. We overlaid preferred habitats on ecological niche model-based estimates of B. anthracis presence. We observed significant overlap between areas with a high predicted probability of male elk selection and B. anthracis potential. These potentially risky areas of elk and B. anthracis overlap were broadly spread over public and private lands. Future outbreaks in the region are probable, and this analysis identified the spatial extent of the risk area in the region, which can be used to prioritize anthrax surveillance.
Predicting the spatial distribution of animals is an important and widely used tool with applications in wildlife management, conservation, and population health. Wildlife telemetry technology coupled with the availability of spatial data and GIS software have facilitated advancements in species distribution modeling. There are also challenges related to these advancements including the accurate and appropriate implementation of species distribution modeling methodology. Resource Selection Function (RSF) modeling is a commonly used approach for understanding species distributions and habitat usage, and mapping the RSF results can enhance study findings and make them more accessible to researchers and wildlife managers. Currently, there is no consensus in the literature on the most appropriate method for mapping RSF results, methods are frequently not described, and mapping approaches are not always related to accuracy metrics. We conducted a systematic review of the RSF literature to summarize the methods used to map RSF outputs, discuss the relationship between mapping approaches and accuracy metrics, performed a case study on the implications of employing different mapping methods, and provide recommendations as to appropriate mapping techniques for RSF studies. We found extensive variability in methodology for mapping RSF results. Our case study revealed that the most commonly used approaches for mapping RSF results led to notable differences in the visual interpretation of RSF results, and there is a concerning disconnect between accuracy metrics and mapping methods. We make 5 recommendations for researchers mapping the results of RSF studies, which are focused on carefully selecting and describing the method used to map RSF studies, and relating mapping approaches to accuracy metrics.
IntroductionRecurrent cholera outbreaks have been reported in Cameroon since 1971. However, case fatality ratios remain high, and we do not have an optimal understanding of the epidemiology of the disease, due in part to the diversity of Cameroon’s climate subzones and a lack of comprehensive data at the health district level.Methods/FindingsA unique health district level dataset of reported cholera case numbers and related deaths from 2000–2012, obtained from the Ministry of Public Health of Cameroon and World Health Organization (WHO) country office, served as the basis for the analysis. During this time period, 43,474 cholera cases were reported: 1748 were fatal (mean annual case fatality ratio of 7.9%), with an attack rate of 17.9 reported cases per 100,000 inhabitants per year. Outbreaks occurred in three waves during the 13-year time period, with the highest case fatality ratios at the beginning of each wave. Seasonal patterns of illness differed strikingly between climate subzones (Sudano-Sahelian, Tropical Humid, Guinea Equatorial, and Equatorial Monsoon). In the northern Sudano-Sahelian subzone, highest number of cases tended to occur during the rainy season (July-September). The southern Equatorial Monsoon subzone reported cases year-round, with the lowest numbers during peak rainfall (July-September). A spatial clustering analysis identified multiple clusters of high incidence health districts during 2010 and 2011, which were the 2 years with the highest annual attack rates. A spatiotemporal autoregressive Poisson regression model fit to the 2010–2011 data identified significant associations between the risk of transmission and several factors, including the presence of major waterbody or highway, as well as the average daily maximum temperature and the precipitation levels over the preceding two weeks. The direction and/or magnitude of these associations differed between climate subzones, which, in turn, differed from national estimates that ignored subzones differences in climate variables.Conclusions/SignificanceThe epidemiology of cholera in Cameroon differs substantially between climate subzones. Development of an optimal comprehensive country-wide control strategy for cholera requires an understanding of the impact of the natural and built environment on transmission patterns at the local level, particularly in the setting of ongoing climate change.
A re-emergence of anthrax, a zoonosis caused by the long-lived, spore-forming Bacillus anthracis, occurred with a multispecies outbreak in southwestern Montana in 2008. It substantially impacted a managed herd of about 3,500 free-ranging plains bison ( Bison bison bison) on a large, private ranch southwest of Bozeman, with about 8% mortality and a disproportionate 28% mortality of mature males; a similar high rate occurred in male Rocky Mountain elk ( Cervus canadensis nelson). Grazing herbivores are particularly at risk for anthrax from ingesting spore-contaminated soil and grasses in persistent environmental reservoirs. We predicted areas of mature male bison habitat preference on the landscape by using GPS collar data and a resource selection function model using environmental covariates. We overlaid preferred areas with ecologic niche, model-based predictions of B. anthracis environmental reservoirs to identify areas of high anthrax risk. Overlapping areas were distributed across the ranch and were not confined to pastures associated with the previous outbreak, suggesting that ongoing pasture exclusion alone will not prevent future outbreaks. The data suggested vaccination campaigns should continue for bison, and the results can be used to prioritize carcass surveillance in areas of greatest overlap.
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