Redefining the Australian Anthrax Belt: Modeling the Ecological Niche and Predicting the Geographic Distribution of Bacillus anthracis

Self-reported critical gaps in the essential knowledge and capacity of spatial epidemiology between the current university education and competency-oriented professional demands in preparing for a future pandemic among public health postgraduates in China: a nationwide cross-sectional survey

BACKGROUND

Spatial epidemiology plays an important role in public health. Yet, it is unclear whether the current university education in spatial epidemiology in China could meet the competency-oriented professional demands. This study aimed to understand the current situation of education and training, practical application, and potential demands in spatial epidemiology among public health postgraduates in China, and to assess the critical gaps in a future emerging infectious diseases (EID) pandemic preparedness and response.

METHODS

This study was divided into three parts. The first part was a comparative study on spatial epidemiology education in international public health postgraduate training. The second part was a cross-sectional survey conducted among public health professionals. The third part was a nationwide cross-sectional survey conducted among public health postgraduates at Chinese universities from October 2020 to February 2021. Data was collected by the WeChat-based questionnaire star survey system and analyzed using the SPSS software.

RESULTS

International education institutions had required public health postgraduates to master the essential knowledge and capacity of spatial epidemiology. A total of 198 public health professionals were surveyed, and they had a median of 4.00 (IQR 3.13-4.53) in demand degree of spatial epidemiology. A total of 1354 public health postgraduates were surveyed from 51 universities. Only 29.41% (15/51) of universities offered spatial epidemiology course. Around 8.05% (109/1354) of postgraduates had learned spatial epidemiology, and had a median of 1.05 (IQR 1.00-1.29) in learning degree and a median of 1.91 (IQR 1.05-2.78) in practical application degree of spatial epidemiology. To enhance professional capacity, 65.95% (893/1354) of postgraduates hoped that universities would deliver a credit-course of spatial epidemiology.

CONCLUSIONS

A huge unmet education and training demand in spatial epidemiology existed in the current education system of public health postgraduates in China. To enhance the competency-oriented professional capacity in preparedness and response to a future pandemic, it is urgent to incorporate the teaching and training of spatial epidemiology into the compulsory curriculum system of public health postgraduates in China.

In Search of Proximate Triggers of Anthrax Outbreaks in Wildlife: A Hypothetical Individual-Based Model of Plasmid Transfer within Bacillus Communities

Bacillus anthracis, the causative agent of anthrax in humans, livestock, and wildlife, exists in a community with hundreds of other species of bacteria in the environment. Work on the genetics of these communities has shown that B. anthracis shares a high percentage of chromosomal genes with both B. thuringiensis and B. cereus, and that phenotypic differences among these bacteria can result from extra-chromosomal DNA in the form of plasmids. We developed a simple hypothetical individual-based model to simulate the likelihood of detecting plasmids with genes encoding anthrax toxins within bacterial communities composed of B. anthracis, B. thuringiensis, and B. cereus, and the surrounding matrix of extra-cellular polymeric substances. Simulation results suggest the horizontal transfer of plasmids with genes encoding anthrax toxins among Bacillus species persisting outside the host could function as a proximate factor triggering anthrax outbreaks.

Anthrax hotspot mapping in Kenya support establishing a sustainable two-phase elimination program targeting less than 6% of the country landmass

Using data collected from previous (n = 86) and prospective (n = 132) anthrax outbreaks, we enhanced prior ecological niche models (ENM) and added kernel density estimation (KDE) approaches to identify anthrax hotspots in Kenya. Local indicators of spatial autocorrelation (LISA) identified clusters of administrative wards with a relatively high or low anthrax reporting rate to determine areas of greatest outbreak intensity. Subsequently, we modeled the impact of vaccinating livestock in the identified hotspots as a national control measure. Anthrax suitable areas included high agriculture zones concentrated in the western, southwestern and central highland regions, consisting of 1043 of 1450 administrative wards, covering 18.5% country landmass, and hosting 30% of the approximately 13 million cattle population in the country. Of these, 79 wards covering 5.5% landmass and hosting 9% of the cattle population fell in identified anthrax hotspots. The rest of the 407 administrative wards covering 81.5% of the country landmass, were classified as low anthrax risk areas and consisted of the expansive low agricultural arid and semi-arid regions of the country that hosted 70% of the cattle population, reared under the nomadic pastoralism. Modelling targeted annual vaccination of 90% cattle population in hotspot administrative wards reduced > 23,000 human exposures. These findings support an economically viable first phase of anthrax control program in low-income countries where the disease is endemic, that is focused on enhanced animal and human surveillance in burden hotspots, followed by rapid response to outbreaks anchored on public education, detection and treatment of infected humans, and ring vaccination of livestock. Subsequently, the global anthrax elimination program focused on sustained vaccination and surveillance in livestock in the remaining few hotspots for a prolonged period (> 10 years) may be implemented.

Drivers and potential distribution of anthrax occurrence and incidence at national and sub-county levels across Kenya from 2006 to 2020 using INLA

Anthrax is caused by, Bacillus anthracis, a soil-borne bacterium that infects grazing animals. Kenya reported a sharp increase in livestock anthrax cases from 2005, with only 12% of the sub-counties (decentralised administrative units used by Kenyan county governments to facilitate service provision) accounting for almost a third of the livestock cases. Recent studies of the spatial extent of B. anthracis suitability across Kenya have used approaches that cannot capture the underlying spatial and temporal dependencies in the surveillance data. To address these limitations, we apply the first Bayesian approach using R-INLA to analyse a long-term dataset of livestock anthrax case data, collected from 2006 to 2020 in Kenya. We develop a spatial and a spatiotemporal model to investigate the distribution and socio-economic drivers of anthrax occurrence and incidence at the national and sub-county level. The spatial model was robust to geographically based cross validation and had a sensitivity of 75% (95% CI 65-75) against withheld data. Alarmingly, the spatial model predicted high intensity of anthrax across the Northern counties (Turkana, Samburu, and Marsabit) comprising pastoralists who are often economically and politically marginalized, and highly predisposed to a greater risk of anthrax. The spatiotemporal model showed a positive link between livestock anthrax risk and the total human population and the number of exotic dairy cattle, and a negative association with the human population density, livestock producing households, and agricultural land area. Public health programs aimed at reducing human-animal contact, improving access to healthcare, and increasing anthrax awareness, should prioritize these endemic regions.

The potential distribution of Bacillus anthracis suitability across Uganda using INLA

To reduce the veterinary, public health, environmental, and economic burden associated with anthrax outbreaks, it is vital to identify the spatial distribution of areas suitable for Bacillus anthracis, the causative agent of the disease. Bayesian approaches have previously been applied to estimate uncertainty around detected areas of B. anthracis suitability. However, conventional simulation-based techniques are often computationally demanding. To solve this computational problem, we use Integrated Nested Laplace Approximation (INLA) which can adjust for spatially structured random effects, to predict the suitability of B. anthracis across Uganda. We apply a Generalized Additive Model (GAM) within the INLA Bayesian framework to quantify the relationships between B. anthracis occurrence and the environment. We consolidate a national database of wildlife, livestock, and human anthrax case records across Uganda built across multiple sectors bridging human and animal partners using a One Health approach. The INLA framework successfully identified known areas of species suitability in Uganda, as well as suggested unknown hotspots across Northern, Eastern, and Central Uganda, which have not been previously identified by other niche models. The major risk factors for B. anthracis suitability were proximity to water bodies (0-0.3 km), increasing soil calcium (between 10 and 25 cmolc/kg), and elevation of 140-190 m. The sensitivity of the final model against the withheld evaluation dataset was 90% (181 out of 202 = 89.6%; rounded up to 90%). The prediction maps generated using this model can guide future anthrax prevention and surveillance plans by the relevant stakeholders in Uganda.

Spatiotemporal Patterns of Anthrax, Vietnam, 1990–2015

Anthrax is a priority zoonosis for control in Vietnam. The geographic distribution of anthrax remains to be defined, challenging our ability to target areas for control. We analyzed human anthrax cases in Vietnam to obtain anthrax incidence at the national and provincial level. Nationally, the trendline for cases remained at ≈61 cases/year throughout the 26 years of available data, indicating control efforts are not effectively reducing disease burden over time. Most anthrax cases occurred in the Northern Midlands and Mountainous regions, and the provinces of Lai Chau, Dien Bien, Lao Cai, Ha Giang, Cao Bang, and Son La experienced some of the highest incidence rates. Based on spatial Bayes smoothed maps, every region of Vietnam experienced human anthrax cases during the study period. Clarifying the distribution of anthrax in Vietnam will enable us to better identify risk areas for improved surveillance, rapid clinical care, and livestock vaccination campaigns.

Detection of Toxoplasma gondii oocysts in soil and risk mapping in an island environment in the Northeast of Brazil

Toxoplasmosis is an emerging and re-emerging infectious disease that can be transmitted through a contaminated environment. Environmental contamination is an emergency health issue, and determining its occurrence is fundamental to a One Health approach. In this study, we addressed the extent of environmental contamination and viability of Toxoplasma gondii oocysts in soil in different environments on Fernando de Noronha Island, Brazil. In addition, we performed species distribution modelling to predict the environmental suitability for coccidia persistence in the studied area. Soil samples were collected in 14 neighbourhoods of the Island and in the four main squares, creating a total of 95 soil samples (five samples per site). The samples were analyzed by the polymerase chain reaction (PCR) technique for the presence of the 18S ribosomal DNA gene of Apicomplexan protozoa, followed by genetic sequencing. We obtained 4.2% (4/95) positive soil samples with 100% similarity for T. gondii sequences. Two out of four positive sites on PCR showed viability of T. gondii oocysts through the mouse bioassay technique. As a result of the application of the species distribution modelling, environmental adequacy for the coccidia was observed throughout the Island. The results confirm the contamination of the soil in this insular environment by T. gondii oocysts and the environmental suitability by modelling application. These findings are an alert for the possibility of infection in animals and humans by contaminated soil, and for contamination of the maritime environment in addition to water resources for consumption by the local population.

Modeling the environmental suitability for Bacillus anthracis in the Qinghai Lake Basin, China

Bacillus anthracis is a gram-positive, rod-shaped and endospore-forming bacterium that causes anthrax, a deadly disease to livestock and, occasionally, to humans. The spores are extremely hardy and may remain viable for many years in soil. Previous studies have identified East Qinghai and neighbouring Gansu in northwest China as a potential source of anthrax infection. This study was carried out to identify conditions and areas in the Qinghai Lake basin that are environmentally suitable for B. anthracis distribution. Anthrax occurrence data from 2005-2016 and environmental variables were spatially modeled by a maximum entropy algorithm to evaluate the contribution of the variables to the distribution of B. anthracis. Principal Component Analysis and Variance Inflation Analysis were adopted to limit the number of environmental variables and minimize multicollinearity. Model performance was evaluated using AUC (area under the curve) ROC (receiver operating characteristics) curves. The three variables that contributed most to the suitability model for B. anthracis are a relatively high annual mean temperature of -2 to 0°C, (53%), soil type classified as; cambisols and kastanozems (35%), and a high human population density of 40 individuals per km2 (12%). The resulting distribution map identifies the permanently inhabited rim of the Qinghai Lake as highly suitable for B. anthracis. Our environmental suitability map and the identified variables provide the nature reserve managers and animal health authorities readily available information to devise both surveillance strategy and control strategy (administration of vaccine to livestock) in B. anthracis suitable regions to abate future epidemics.

Modelling the ecological niche of naturally occurring anthrax at global and circumpolar extents using an ensemble modelling framework

Bacillus anthracis, the causative agent of anthrax, is a spore-forming bacterium that primarily affects herbivorous livestock, wildlife and humans exposed to direct contact with infected animal carcasses or products. To date, there are a limited number of studies that have delineated the potential global distribution of anthrax, despite the importance of the disease from both an economic and public health standpoint. This study compiled occurrence data (n = 874) of confirmed human and animal cases from 1954 to 2021 in 94 countries. Using an ensemble ecological niche model framework, we developed updated maps of the global predicted ecological suitability of anthrax to measure relative risk at multiple scales of analysis, including a model for circumpolar regions. Additionally, we produced maps quantifying the disease transmission risk associated with anthrax to cattle, sheep and goat populations. Environmental suitability for B. anthracis globally is concentred throughout Eurasia, sub-Saharan Africa, the Americas, Southeast Asia, Australia and Oceania. Suitable environments for B. anthracis at the circumpolar scale extend above the Arctic Circle into portions of Russia, Canada, Alaska and northern Scandinavia. Environmental factors driving B. anthracis suitability globally include vegetation, land surface temperature, soil characteristics, primary climate conditions and topography. At the circumpolar scale, suitability is influenced by soil factors, topography and the derived climate characteristics. The greatest risk to livestock is concentrated within the Indian subcontinent, Australia, Anatolia, the Caucasus region, Central Asia, the European Union, Argentina, Uruguay, China, the United States, Canada and East Africa. This study expands on previous work by providing enhanced knowledge of the potential spatial distribution of anthrax in the Southern Hemisphere, sub-Saharan Africa, Asia and circumpolar regions of the Northern Hemisphere. We conclude that these updated maps will provide pertinent information to guide disease control programs, inform policymakers and raise awareness at the global level to lessen morbidity and mortality among animals and humans located in environmentally suitable areas.

A framework for integrating inferred movement behavior into disease risk models

Movement behavior is an important contributor to habitat selection and its incorporation in disease risk models has been somewhat neglected. The habitat preferences of host individuals affect their probability of exposure to pathogens. If preference behavior can be incorporated in ecological niche models (ENMs) when data on pathogen distributions are available, then variation in such behavior may dramatically impact exposure risk. Here we use data from the anthrax endemic system of Etosha National Park, Namibia, to demonstrate how integrating inferred movement behavior alters the construction of disease risk maps. We used a Maximum Entropy (MaxEnt) model that associated soil, bioclimatic, and vegetation variables with the best available pathogen presence data collected at anthrax carcass sites to map areas of most likely Bacillus anthracis (the causative bacterium of anthrax) persistence. We then used a hidden Markov model (HMM) to distinguish foraging and non-foraging behavioral states along the movement tracks of nine zebra (Equus quagga) during the 2009 and 2010 anthrax seasons. The resulting tracks, decomposed on the basis of the inferred behavioral state, formed the basis of step-selection functions (SSFs) that used the MaxEnt output as a potential predictor variable. Our analyses revealed different risks of exposure during different zebra behavioral states, which were obscured when the full movement tracks were analyzed without consideration of the underlying behavioral states of individuals. Pathogen (or vector) distribution models may be misleading with regard to the actual risk faced by host animal populations when specific behavioral states are not explicitly accounted for in selection analyses. To more accurately evaluate exposure risk, especially in the case of environmentally transmitted pathogens, selection functions could be built for each identified behavioral state and then used to assess the comparative exposure risk across relevant states. The scale of data collection and analysis, however, introduces complexities and limitations for consideration when interpreting results.

Remote Sensing and GIS-Based Suitability Mapping of Termite Habitat in the African Savanna: A Case Study of the Lowveld in Kruger National Park

Termites (Isoptera) are among the most globally dominant macroinvertebrates in terrestrial environments and are an ecologically important group of soil biota in tropical and subtropical ecosystems. These insects function as essential ecosystem engineers that facilitate nutrient cycling, especially in the regulation of the physical and chemical properties of soil and the decomposition of organic matter that maintains heterogeneity in tropical and subtropical ecosystems. Termites, like all living organisms, require certain environmental parameters to support the distribution, abundance, and activities of the species. South Africa’s Kruger National Park (KNP)—one of the most important protected areas in the world and a popular safari tourist destination—is an extraordinary savanna ecosystem in which termite mounds, or termitaria, are widely distributed. A range of biotic and abiotic factors found in the natural environment of KNP provide highly suitable ecological conditions for termite habitat range, and thus the development of termitaria. Previous research has shown that the most important factors affecting habitat suitability for termites and the geographic distribution of termitaria include climate factors, land cover, and other environmental characteristics such as soil composition and plant-litter biomass. However, the specific environmental mechanisms that regulate termite occurrence and the spatial distribution of termitaria in KNP are not fully understood, especially in the context of climate and land-cover changes. The present study examines the relationship between the spatial distribution of termitaria and selected climate and environmental factors in the Kruger Lowveld region, which contains one of the largest numbers of termitaria in KNP. Using high-resolution satellite imagery, 8200 training points of termitaria occurrence were collected throughout the study area to train classifiers and produce land-cover-classification maps for the Kruger Lowveld region of interest. We then applied a hybrid approach through the integration of remote sensing (RS) and a GIS-based analytical hierarchy process (AHP) and frequency-ratio (FR) methods to model the relationship between the spatial distribution of termitaria and selected environmental variables and to produce suitability maps. To our knowledge, this study is the first of its kind to examine the influence of combined sets of environmental attributes on the spatial distribution of termitaria in the Lowveld region of KNP. The results indicate that moderately and highly suitable conditions for termite range tolerance and termitaria development are correlated with undulating plains with clay soils, greater distance to drainage streams, high solar radiation, and low depth of groundwater. The findings of this study shed light on the need for future research that investigates the impact of climate and land-cover changes on termite habitat range and spatial distribution and that can inform park managers and policymakers about Kruger National Park and other protected areas with similar environmental conditions.

Bacillus anthracis Phylogeography: New Clues From Kazakhstan, Central Asia

This article describes Bacillus anthracis strains isolated in Kazakhstan since the 1950s until year 2016 from sixty-one independent events associated with anthrax in humans and animals. One hundred and fifty-four strains were first genotyped by Multiple Locus VNTR (variable number of tandem repeats) Analysis (MLVA) using 31 VNTR loci. Thirty-five MLVA31 genotypes were resolved, 28 belong to the A1/TEA group, five to A3/Sterne-Ames group, one to A4/Vollum and one to the B clade. This is the first report of the presence of the B-clade in Kazakhstan. The MLVA31 results and epidemiological data were combined to select a subset of seventy-nine representative strains for draft whole genome sequencing (WGS). Strains from Kazakhstan significantly enrich the known phylogeny of the Ames group polytomy, including the description of a new branch closest to the Texas, United States A.Br.Ames sublineage stricto sensu. Three among the seven currently defined branches in the TEA polytomy are present in Kazakhstan, “Tsiankovskii”, “Heroin”, and “Sanitary Technical Institute (STI)”. In particular, strains from the STI lineage are largely predominant in Kazakhstan and introduce numerous deep branching STI sublineages, demonstrating a high geographic correspondence between “STI” and Kazakhstan, Central Asia. This observation is a strong indication that the TEA polytomy emerged after the last political unification of Asian steppes in the fourteenth century of the Common Era. The phylogenetic analysis of the Kazakhstan data and of currently available WGS data of worldwide origin strengthens our understanding of B. anthracis geographic expansions in the past seven centuries.

Identifying Edaphic Factors and Normalized Difference Vegetation Index Metrics Driving Wildlife Mortality From Anthrax in Kenya’s Wildlife Areas

Anthrax, an acute disease of homeotherms caused by soil-borne Bacillus anthracis is implicated in dramatic declines in wildlife mainly in sub-Saharan Africa. Anthrax outbreaks are often localized in space and time. Therefore, understanding predictors of the spatial and temporal occurrence of anthrax in wildlife areas is useful in supporting early warning and improved response and targeting measures to reduce the impact of epizootic risk on populations. Spatial localization of anthrax is hypothesized to be driven by edaphic factors, while the temporal outbreaks are thought to be driven by extreme weather events including temperature, humidity, rainfall, and drought. Here, we test the role of select edaphic factors and normalized difference vegetation index (NDVI) metrics driven by vegetation structure and climate variability on the spatial and temporal patterns of wildlife mortality from anthrax in key wildlife areas in Kenya over a 20-year period, from 2000 to 2019. There was a positive association between the number of anthrax outbreaks and the total number of months anthrax was reported during the study period and the nitrogen and organic carbon content of the soil in each wildlife area. The monthly occurrence (timing) of anthrax in Lake Nakuru (with the most intense outbreaks) was positively related to the previous month’s spatial heterogeneity in NDVI and monthly NDVI deviation from 20-year monthly means. Generalized linear models revealed that the number of months anthrax was reported in a year (intensity) was positively related to spatial heterogeneity in NDVI, total organic carbon and cation exchange capacity of the soil. These results, examined in the light of experimental studies on anthrax persistence and amplification in the soil enlighten on mechanisms by which these factors are driving anthrax outbreaks and spatial localization.

Mapping habitat suitability for Asiatic black bear and red panda in Makalu Barun National Park of Nepal from Maxent and GARP models

Habitat evaluation is essential for managing wildlife populations and formulating conservation policies. With the rise of innovative powerful statistical techniques in partnership with Remote Sensing, GIS and GPS techniques, spatially explicit species distribution modeling (SDM) has rapidly grown in conservation biology. These models can help us to study habitat suitability at the scale of the species range, and are particularly useful for examining the overlapping habitat between sympatric species. Species presence points collected through field GPS observations, in conjunction with 13 different topographic, vegetation related, anthropogenic, and bioclimatic variables, as well as a land cover map with seven classification categories created by support vector machine (SVM) were used to implement Maxent and GARP ecological niche models. With the resulting ecological niche models, the suitable habitat for asiatic black bear (Ursus thibetanus) and red panda (Ailurus fulgens) in Nepal Makalu Barun National Park (MBNP) was predicted. All of the predictor variables were extracted from freely available remote sensing and publicly shared government data resources. The modeled results were validated by using an independent dataset. Analysis of the regularized training gain showed that the three most important environmental variables for habitat suitability were distance to settlement, elevation, and mean annual temperature. The habitat suitability modeling accuracy, characterized by the mean area under curve, was moderate for both species when GARP was used (0.791 for black bear and 0.786 for red panda), but was moderate for black bear (0.857), and high for red panda (0.920) when Maxent was used. The suitable habitat estimated by Maxent for black bear and red panda was 716 km2 and 343 km2 respectively, while the suitable area determined by GARP was 1074 km2 and 714 km2 respectively. Maxent predicted that the overlapping area was 83% of the red panda habitat and 40% of the black bear habitat, while GARP estimated 88% of the red panda habitat and 58% of the black bear habitat overlapped. The results of land cover exhibited that barren land covered the highest percentage of area in MBNP (36.0%) followed by forest (32.6%). Of the suitable habitat, both models indicated forest as the most preferred land cover for both species (63.7% for black bear and 61.6% for red panda from Maxent; 59.9% black bear and 58.8% for red panda from GARP). Maxent outperformed GARP in terms of habitat suitability modeling. The black bear showed higher habitat selectivity than red panda. We suggest that proper management should be given to the overlapping habitats in the buffer zone. For remote and inaccessible regions, the proposed methods are promising tools for wildlife management and conservation, deserving further popularization.

An Estimate of Global Anthrax Prevalence in Livestock: A Meta-analysis

Background and Aim:

Anthrax, caused by the soil-borne spore-forming bacteria called Bacillus anthracis, is a zoonotic disease that persists worldwide in livestock and wildlife and infects humans. It is a great hazard to livestock; henceforth, evaluating the global concerns about the disease occurrence in livestock is essential. This study was conducted to estimate the global prevalence of anthrax and predict high-risk regions, which could be an input to veterinarians to take necessary steps to control and avoid the disease.

Materials and Methods:

A literature review was performed using online databases, namely, PubMed, Google Scholar, Scopus, Biomed Central, and Science Direct, to extract relevant publications worldwide between 1992 and 2020.</AQ9> Initially, 174 articles were selected, and after scrutinizing, 24 articles reporting the prevalence of anthrax were found to be adequate for the final meta-analysis. The statistical study was accompanied by employing fixed effects and random effects models using R.

Results:

The pooled prevalence of anthrax globally was 28% (95% confidence interval, 26-30%) from 2452 samples through the fixed effects model. Continent-wise subgroup analysis through the random effects model revealed that the pooled prevalence of anthrax was highest in Africa (29%) and least in North America (21%).

Conclusion:

In these publications, anthrax causes economic loss to farmers and, thus, to the world. Hence, controlling anthrax infections in high-risk regions are essential by implementing appropriate control measures to decrease the effect of the disease, thereby reducing economic loss.

Modeling the Potential Future Distribution of Anthrax Outbreaks under Multiple Climate Change Scenarios for Kenya

The climate is changing, and such changes are projected to cause global increase in the prevalence and geographic ranges of infectious diseases such as anthrax. There is limited knowledge in the tropics with regards to expected impacts of climate change on anthrax outbreaks. We determined the future distribution of anthrax in Kenya with representative concentration pathways (RCP) 4.5 and 8.5 for year 2055. Ecological niche modelling (ENM) of boosted regression trees (BRT) was applied in predicting the potential geographic distribution of anthrax for current and future climatic conditions. The models were fitted with presence-only anthrax occurrences (n = 178) from historical archives (2011-2017), sporadic outbreak surveys (2017-2018), and active surveillance (2019-2020). The selected environmental variables in order of importance included rainfall of wettest month, mean precipitation (February, October, December, July), annual temperature range, temperature seasonality, length of longest dry season, potential evapotranspiration and slope. We found a general anthrax risk areal expansion i.e., current, 36,131 km2, RCP 4.5, 40,012 km2, and RCP 8.5, 39,835 km2. The distribution exhibited a northward shift from current to future. This prediction of the potential anthrax distribution under changing climates can inform anticipatory measures to mitigate future anthrax risk.

Modeling the spatial distribution of anthrax in southern Kenya

BACKGROUND

Anthrax is an important zoonotic disease in Kenya associated with high animal and public health burden and widespread socio-economic impacts. The disease occurs in sporadic outbreaks that involve livestock, wildlife, and humans, but knowledge on factors that affect the geographic distribution of these outbreaks is limited, challenging public health intervention planning.

METHODS

Anthrax surveillance data reported in southern Kenya from 2011 to 2017 were modeled using a boosted regression trees (BRT) framework. An ensemble of 100 BRT experiments was developed using a variable set of 18 environmental covariates and 69 unique anthrax locations. Model performance was evaluated using AUC (area under the curve) ROC (receiver operating characteristics) curves.

RESULTS

Cattle density, rainfall of wettest month, soil clay content, soil pH, soil organic carbon, length of longest dry season, vegetation index, temperature seasonality, in order, were identified as key variables for predicting environmental suitability for anthrax in the region. BRTs performed well with a mean AUC of 0.8. Areas highly suitable for anthrax were predicted predominantly in the southwestern region around the shared Kenya-Tanzania border and a belt through the regions and highlands in central Kenya. These suitable regions extend westwards to cover large areas in western highlands and the western regions around Lake Victoria and bordering Uganda. The entire eastern and lower-eastern regions towards the coastal region were predicted to have lower suitability for anthrax.

CONCLUSION

These modeling efforts identified areas of anthrax suitability across southern Kenya, including high and medium agricultural potential regions and wildlife parks, important for tourism and foreign exchange. These predictions are useful for policy makers in designing targeted surveillance and/or control interventions in Kenya. We thank the staff of Directorate of Veterinary Services under the Ministry of Agriculture, Livestock and Fisheries, for collecting and providing the anthrax historical occurrence data.

Anthrax in the Amhara regional state of Ethiopia; spatiotemporal analysis and environmental suitability modeling with an ensemble approach

Anthrax is one of the most neglected tropical disease affecting humans, livestock, and wildlife worldwide. The disease is caused by soil-borne spore-forming bacteria called Bacillus anthracis. A machine learning algorithm with the biomod2 package of R software was used to develop a predictive map for the Amhara regional state of Ethiopia. One hundred twenty-eight georeferenced confirmed outbreak reports of anthrax in livestock and 11 bioclimatic, eight soil characteristics, and three livestock density variables were used to train the model. The algorithm was set to run 3-fold with a total of 27 outputs for the nine selected models. An ensemble model was developed with ROC evaluation metrics set at 0.8. The ensemble model showed an improved performance than the individual models (KAPPA, TSS, and ROC values of 0.86, 0.93, and 0.99, respectively). Variables like annual precipitation (22.51 %), precipitation of warmest quarter (14.17 %), precipitation of wettest month (11.61 %), cattle density (9.67 %), sheep density (6.6 %), annual maximum temperature (6.17 %), altitude/elevation (5.24 %), and sand content (4.83 %) contributed the highest share in the ensemble model. The predicted suitable areas were primarily in the Central and Southern parts of the region. West Gojam and South Gondar zones were found highly suitable; while parts of Waghemira, North Wollo, and South Wollo were not significantly suitable. Besides, East Gojam, North Gondar, and Awi administrative zones were also reasonably suitable to Bacillus anthracis. The study can be used as a basis in the planning of prevention and control approaches of anthrax outbreaks in the region. Administrative zones like West Gojam, South Gondar, Awi, and East Gojam have to be prioritized as a risky-areas in the planning of preventive measures of anthrax in the region.

Genetic Diversity of Australian Bacillus anthracis Isolates Revealed by Multiple-Locus Variable-Number Tandem Repeat Analysis

Outbreaks of anthrax occur sporadically in Australia and most commonly in the "anthrax belt", a region which extends from southern Queensland through the centre of New South Wales and into northern Victoria. Little is known about the epidemiological links between Bacillus anthracis isolates taken from different outbreaks and the diversity of strains within Australia. We used multiple-locus variable-number tandem repeat analysis employing 25 markers (MLVA25) to genotype 99 B. anthracis isolates from an archival collection of Australian isolates. MLVA25 genotyping revealed eight unique genotypes which clustered within the previously defined A3 genotype of B. anthracis. Genotyping of B. anthracis strains from outbreaks of disease in Victoria identified the presence of multiple genotypes associated with these outbreaks. The geographical distribution of genotypes within Australia suggests that a single genotype was introduced into the eastern states of Australia, followed by the spread and localised differentiation of the pathogen (MLVA25 genotypes MG1-MG6) throughout the anthrax belt. In contrast, unexplained occurrences of disease in areas outside of this anthrax belt which are associated with different genotypes, (MLVA25 genotypes MG7 and MG8) indicate separate introductions of B. anthracis into Australia.

Exploring environmental coverages of species: a new variable contribution estimation methodology for rulesets from the genetic algorithm for rule-set prediction

Variable contribution estimation for, and determination of variable importance within, ecological niche models (ENMs) remain an important area of research with continuing challenges. Most ENM algorithms provide normally exhaustive searches through variable space; however, selecting variables to include in models is a first challenge. The estimation of the explanatory power of variables and the selection of the most appropriate variable set within models can be a second challenge. Although some ENMs incorporate the variable selection rubric inside the algorithms, there is no integrated rubric to evaluate the variable importance in the Genetic Algorithm for Ruleset Production (GARP). Here, we designed a novel variable selection methodology based on the rulesets generated from a GARP experiment. The importance of the variables in a GARP experiment can be estimated based on the consideration of the prevalence of each environmental variable in the dominant presence rules of the best subset of models and its coverage. We tested the performance of this variable selection method based on simulated species with both weak and strong responses to simulated environmental covariates. The variable selection method generally performed well during the simulations with over 2/3 of the trials correctly identifying most covariates. We then predict the distribution of Toxostoma rufum (a bird with a cosmopolitan distribution) in the continental United States (US) and apply our variable selection procedure as a real-world example. We found that the distribution of T. rufum could be accurately modeled with 13 or 10 of 21 variables, using an UI cutoff of 0.5 or 0.25, respectively, arriving at parsimonious environmental coverages with good model accuracy. We also provide tools to simulate species distributions for testing ENM approaches using R.

Predicting the periodic risk of anthrax in livestock in Victoria, Australia, using meteorological data

Cases of anthrax in livestock are infrequently and irregularly reported in the state of Victoria, Australia; however, their impact on individual livestock, farming communities and the government agencies tasked with containing these outbreaks is high. This infrequency has been anecdotally associated with differences in annual and local weather patterns. In this study, we used historical anthrax cases and meteorological data from weather stations throughout Victoria to train a generalized linear mixed effects model to predict the daily odds of a case of anthrax occurring in each shire in the coming 30 days. Meteorological variables were transformed to deviations from the mean values for temperature or cumulative values for rainfall in the shire across all years. Shire was incorporated as a random effect to account for meteorological variation between shires. The model incorporated a post hoc weighting for the frequency of historic cases within each shire and the spatial contribution of each shire to the recently redefined Australian Anthrax Belt. Our model reveals that anthrax cases were associated with drier summer conditions (OR 0.96 (95% CI 0.95-0.97) and OR 0.98 (95% CI 0.97-0.99) for every mm increase in rainfall during September and December, respectively) and cooler than average spring (OR 0.20 (95% CI 0.11-0.52) for every °C increase in minimum daily temperature during November and warmer than average summer temperatures (OR 1.45 (95% CI 1.29-1.61) for every °C increase in maximum daily temperature during January. Cases were also preceded by a 40-day period of cooler, drier temperatures (OR 0.5 (95% CI 0.27-0.74) for every °C increase in maximum daily temperature and OR 0.96 (95% CI 0.95-0.97) for every mm increase in rainfall followed by a warmer than average minimum (or nightly) temperature 10 days immediately before the case (OR 1.46 (95% CI 1.35-1.58) for every °C increase in maximum daily temperature). These coefficients of this training model were then applied daily to meteorological data for each shire, and output of these models was presented as a choropleth and timeline plot in a Shiny web application. The application builds on previous spatial modelling and provides Victorian agencies with a tool to engage at-risk farmers and guide discussions towards anthrax control. This application can contribute to the wider rejuvenation of anthrax knowledge and control in Victoria and corroborates the anecdote that increased odds of disease can be linked to meteorological events.

Potential distributions of Bacillus anthracis and Bacillus cereus biovar anthracis causing anthrax in Africa

BACKGROUND

Bacillus cereus biovar anthracis (Bcbva) is an emergent bacterium closely related to Bacillus anthracis, the etiological agent of anthrax. The latter has a worldwide distribution and usually causes infectious disease in mammals associated with savanna ecosystems. Bcbva was identified in humid tropical forests of Côte d'Ivoire in 2001. Here, we characterize the potential geographic distributions of Bcbva in West Africa and B. anthracis in sub-Saharan Africa using an ecological niche modeling approach.

METHODOLOGY/PRINCIPAL FINDINGS

Georeferenced occurrence data for B. anthracis and Bcbva were obtained from public data repositories and the scientific literature. Combinations of temperature, humidity, vegetation greenness, and soils values served as environmental variables in model calibrations. To predict the potential distribution of suitable environments for each pathogen across the study region, parameter values derived from the median of 10 replicates of the best-performing model for each pathogen were used. We found suitable environments predicted for B. anthracis across areas of confirmed and suspected anthrax activity in sub-Saharan Africa, including an east-west corridor from Ethiopia to Sierra Leone in the Sahel region and multiple areas in eastern, central, and southern Africa. The study area for Bcbva was restricted to West and Central Africa to reflect areas that have likely been accessible to Bcbva by dispersal. Model predicted values indicated potential suitable environments within humid forested environments. Background similarity tests in geographic space indicated statistical support to reject the null hypothesis of similarity when comparing environments associated with B. anthracis to those of Bcbva and when comparing humidity values and soils values individually. We failed to reject the null hypothesis of similarity when comparing environments associated with Bcbva to those of B. anthracis, suggesting that additional investigation is needed to provide a more robust characterization of the Bcbva niche.

CONCLUSIONS/SIGNIFICANCE

This study represents the first time that the environmental and geographic distribution of Bcbva has been mapped. We document likely differences in ecological niche-and consequently in geographic distribution-between Bcbva and typical B. anthracis, and areas of possible co-occurrence between the two. We provide information crucial to guiding and improving monitoring efforts focused on these pathogens.

Predicting the Geographic Distribution of the Bacillus anthracis A1.a/Western North American Sub-Lineage for the Continental United States: New Outbreaks, New Genotypes, and New Climate Data

Bacillus anthracis, the causative pathogen of anthrax, is a spore-forming, environmentally maintained bacterium that continues to be a veterinary health problem with outbreaks occurring primarily in wildlife and livestock. Globally, the genetic populations of B. anthracis include multiple lineages, and each may have different ecological requirements and geographical distributions. It is, therefore, essential to identify environmental associations within lineages to predict geographical distributions and risk areas with improved accuracy. Here, we model the ecological niche and predict the geography of the most widespread sublineage of B. anthracis in the continental United States using updated MERRA-derived (Modern Era Retrospective analysis for Research and Applications; the NASA atmospheric data reanalysis of satellite information with multiple data products) bioclimate variables (i.e., MERRAclim data) and updated soil variables. We filter the occurrence data associated with the A1.a/Western North American sub-lineage of B. anthracis from historical anthrax outbreaks using the multiple-locus variable-number tandem repeat system. In addition, we also incorporate recent cases associated with B. anthracis A1.a sub-lineage from 2008 to 2012 in Montana, Colorado, and Texas. Our results provide the predicted distribution of the A1.a sub-lineage of B. anthracis for the United States with better predictive accuracy and higher spatial resolution than previous estimates. Our prediction serves as an improved disease risk map to better inform anthrax surveillance and control in the United States, particularly the Dakotas and Montana where this sub-lineage is persistent.

Phylogenetic Placement of Isolates Within the Trans-Eurasian Clade A.Br.008/009 of Bacillus anthracis

The largest phylogenetic lineage known to date of the anthrax pathogen Bacillus anthracis is the wide-spread, so-called Trans-Eurasian clade systematically categorized as the A.Br.008/009 group sharing two defining canonical single-nucleotide polymorphisms (canSNP). In this study, we genome-sequenced a collection of 35 B. anthracis strains of this clade, derived from human infections, animal outbreaks or soil, mostly from European countries isolated between 1936 and 2008. The new data were subjected to comparative chromosomal analysis, together with 75 B. anthracis genomes available in public databases, and the relative placements of these isolates were determined within the global phylogeny of the A.Br.008/009 canSNP group. From this analysis, we have detected 3754 chromosomal SNPs, allowing the assignation of the new chromosomal sequences to established sub-clades, to define new sub-clades, such as two new Spanish, one Bulgarian or one German group(s), or to introduce orphan lineages. SNP-based results were compared with that of a multilocus variable number of tandem repeat analysis (MLVA). This analysis indicated that MLVA typing might provide additional information in cases when genomics yields identical genotypes or shows only minor differences. Introducing the delayed mismatch amplification assay (DMAA) PCR-analysis, we developed a cost-effective method to interrogate for a set of ten phylogenetically informative SNPs within genomes of A.Br.008/009 canSNP clade strains of B. anthracis. By this approach, additional 32 strains could be assigned to five of ten defined clades.

Linking Geospatial and Laboratory Sciences to Define Mechanisms behind Landscape Level Drivers of Anthrax Outbreaks

Background: A seasonal predictor of anthrax outbreaks is rainfall, which may be approximated by NDVI using remote sensing. How rainfall or vegetative green-up influences bacterial physiology or microecology to drive anthrax outbreaks is not known. Methods: Rainfall and NDVI dependency of anthrax epizootics was demonstrated with global and local phenological analysis. Growth analysis of B. anthracis in response to pH and calcium gradients was carried out. The influence of pH and calcium levels on expression of toxin and sporulation related proteins in broth culture models was characterized using engineered B. anthracis luminescent reporter strains. Results: Short-term bacterial growth and longer-term bacterial survival were altered by pH and calcium. These conditions also played a major role in pagA and sspB promoter-driven luminescent expression in B. anthracis. Conclusions: Rainfall induced cycling of pH and calcium in soils plays a plausible role in amplifying spore load and persistence in endemic anthrax zones. Observed evidence of B. anthracis favoring soil alkalinity and high soil calcium levels in the environment were linked to physiological conditions that promote bacterial growth, survival, toxin secretion and spore formation; illustrating the utility of bringing laboratory-based (controlled) microbiology experiments into the fold of zoonotic disease ecology.

Perceptions of anthrax in livestock from Victorian dairy farmers in the Goulburn-Murray region of Victoria, Australia

To inform future anthrax surveillance and response activities and to revitalise the communication strategy for producers and their communities, seven dairy farmers in the Goulburn-Murray region of Victoria participated in a Design Thinking process to create a better method to share information about the annual probability of anthrax in their region. Design Thinking is a structured, user-centric design process that begins with intentionally un-structured interviews. Following each interview, transcripts are disassembled into common themes identified by clustering similar statements from these interviews. This short contribution presents these themes re-framed into eight core statements. These statements provide a framework for the remainder of the Design Thinking process but in isolation provide a reference for stake-holding agencies seeking to maximise farmer participation in surveillance programs for early anthrax detection, to encourage active farmer participation during a response and to minimise any anthrax-associated stigma by affected farmers post-response.

The global distribution of Bacillus anthracis and associated anthrax risk to humans, livestock and wildlife

Bacillus anthracis is a spore-forming, Gram-positive bacterium responsible for anthrax, an acute infection that most significantly affects grazing livestock and wild ungulates, but also poses a threat to human health. The geographic extent of B. anthracis is poorly understood, despite multi-decade research on anthrax epizootic and epidemic dynamics; many countries have limited or inadequate surveillance systems, even within known endemic regions. Here, we compile a global occurrence dataset of human, livestock and wildlife anthrax outbreaks. With these records, we use boosted regression trees to produce a map of the global distribution of B. anthracis as a proxy for anthrax risk. We estimate that 1.83 billion people (95% credible interval (CI): 0.59-4.16 billion) live within regions of anthrax risk, but most of that population faces little occupational exposure. More informatively, a global total of 63.8 million poor livestock keepers (95% CI: 17.5-168.6 million) and 1.1 billion livestock (95% CI: 0.4-2.3 billion) live within vulnerable regions. Human and livestock vulnerability are both concentrated in rural rainfed systems throughout arid and temperate land across Eurasia, Africa and North America. We conclude by mapping where anthrax risk could disrupt sensitive conservation efforts for wild ungulates that coincide with anthrax-prone landscapes.

An Ecological Framework for Modeling the Geography of Disease Transmission

Ecological niche modeling (ENM) is widely employed in ecology to predict species’ potential geographic distributions in relation to their environmental constraints and is rapidly becoming the gold-standard method for disease risk mapping. However, given the biological complexity of disease systems, the traditional ENM framework requires reevaluation. We provide an overview of the application of ENM to disease systems and propose a theoretical framework based on the biological properties of both hosts and parasites to produce reliable outputs resembling disease system distributions. Additionally, we discuss the differences between biological considerations when implementing ENM for distributional ecology and epidemiology. This new framework will help the field of disease ecology and applications of biogeography in the epidemiology of infectious diseases.

Infectious diseases greatly impact human health, biodiversity, and global economies, highlighting the need to understand and predict their distributions.

Ecological niche modeling (ENM) was not originally designed to explicitly reconstruct complex biological phenomena such as diseases or parasitism, requiring a reevaluation of the traditional framework.

We provide an integrative ENM framework for disease systems that considers suitable host availability, parasite ecologies, and different scales of modeling.

Disease transmission is driven by factors related to parasite availability and host exposure and susceptibility, which can be incorporated in ENM frameworks.

Geographic shifts in Aedes aegypti habitat suitability in Ecuador using larval surveillance data and ecological niche modeling: Implications of climate change for public health vector control

Arboviral disease transmission by Aedes mosquitoes poses a major challenge to public health systems in Ecuador, where constraints on health services and resource allocation call for spatially informed management decisions. Employing a unique dataset of larval occurrence records provided by the Ecuadorian Ministry of Health, we used ecological niche models (ENMs) to estimate the current geographic distribution of Aedes aegypti in Ecuador, using mosquito presence as a proxy for risk of disease transmission. ENMs built with the Genetic Algorithm for Rule-Set Production (GARP) algorithm and a suite of environmental variables were assessed for agreement and accuracy. The top model of larval mosquito presence was projected to the year 2050 under various combinations of greenhouse gas emissions scenarios and models of climate change. Under current climatic conditions, larval mosquitoes were not predicted in areas of high elevation in Ecuador, such as the Andes mountain range, as well as the eastern portion of the Amazon basin. However, all models projected to scenarios of future climate change demonstrated potential shifts in mosquito distribution, wherein range contractions were seen throughout most of eastern Ecuador, and areas of transitional elevation became suitable for mosquito presence. Encroachment of Ae. aegypti into mountainous terrain was estimated to affect up to 4,215 km² under the most extreme scenario of climate change, an area which would put over 12,000 people currently living in transitional areas at risk. This distributional shift into communities at higher elevations indicates an area of concern for public health agencies, as targeted interventions may be needed to protect vulnerable populations with limited prior exposure to mosquito-borne diseases. Ultimately, the results of this study serve as a tool for informing public health policy and mosquito abatement strategies in Ecuador.

The yellow fever mosquito (Aedes aegypti) is a medically important vector of arboviral diseases in Ecuador, such as dengue fever and chikungunya. Managing Ae. aegypti is a challenge to public health agencies in Latin America, where the use of limited resources must be planned in an efficient, targeted manner. The spatial distribution of Ae. aegypti can be used as a proxy for risk of disease exposure, guiding policy formation and decision-making. We used ecological niche models in this study to predict the range of Ae. aegypti in Ecuador, based on agency larval mosquito surveillance records and layers of environmental predictors (e.g. climate, elevation, and human population). The best models of current range were then projected to the year 2050 under a variety of greenhouse gas emissions scenarios and models of climate change. All modeled future scenarios predicted shifts in the range of Ae. aegypti, allowing us to assess human populations that may be at risk of becoming exposed to Aedes vectored diseases. As climate changes, we predict that communities living in areas of transitional elevation along the Andes mountain range are vulnerable to the expansion of Ae. aegypti.

Ecological niche modeling the potential geographic distribution of four Culicoides species of veterinary significance in Florida, USA

Epizootic hemorrhagic disease (EHD) is a viral arthropod-borne disease affecting wild and domestic ruminants, caused by infection with epizootic hemorrhagic disease virus (EHDV). EHDV is transmitted to vertebrate animal hosts by biting midges in the genus Culicoides Latreille (Diptera: Ceratopogonidae). Culicoides sonorensis Wirth and Jones is the only confirmed vector of EHDV in the United States but is considered rare in Florida and not sufficiently abundant to support EHDV transmission. This study used ecological niche modeling to map the potential geographical distributions and associated ecological variable space of four Culicoides species suspected of transmitting EHDV in Florida, including Culicoides insignis Lutz, Culicoides stellifer (Coquillett), Culicoides debilipalpis Hoffman and Culicoides venustus Lutz. Models were developed with the Genetic Algorithm for Rule Set Production in DesktopGARP v1.1.3 using species occurrence data from field sampling along with environmental variables from WorldClim and Trypanosomiasis and Land use in Africa. For three Culicoides species (C. insignis, C. stellifer and C. debilipalpis) 96-98% of the presence points were predicted across the Florida landscape (63.8% - 72.5%). For C. venustus, models predicted 98.00% of presence points across 27.4% of Florida. Geographic variations were detected between species. Culicoides insignis was predicted to be restricted to peninsular Florida, and in contrast, C. venustus was predicted to be primarily in north Florida and the panhandle region. Culicoides stellifer and C. debilipalpis were predicted nearly statewide. Environmental conditions also differed by species, with some species' ranges predicted by more narrow ranges of variables than others. The Normalized Difference Vegetation Index (NDVI) was a major predictor of C. venustus and C. insignis presence. For C. stellifer, Land Surface Temperature, Middle Infrared were the most limiting predictors of presence. The limiting variables for C. debilipalpis were NDVI Bi-Annual Amplitude and NDVI Annual Amplitude at 22.5% and 28.1%, respectively. The model outputs, including maps and environmental variable range predictions generated from these experiments provide an important first pass at predicting species of veterinary importance in Florida. Because EHDV cannot exist in the environment without the vector, model outputs can be used to estimate the potential risk of disease for animal hosts across Florida. Results also provide distribution and habitat information useful for integrated pest management practices.

Temporal patterns of anthrax outbreaks among livestock in Lesotho, 2005-2016

Background

Although anthrax is endemic in Lesotho, limited information is available on the patterns of the disease among livestock animals. This study investigated temporal patterns of anthrax outbreaks and cases among livestock animals in Lesotho.

Methods

Secondary data of anthrax outbreaks reported to the Department of Livestock Services between January 2005 and December 2016 was used for this study. Proportions of anthrax outbreaks and cases, and their corresponding 95% confidence interval were calculated and compared across year, season, month and region using the Chi-square or Fisher’s exact test. The autoregression model was used to evaluate annual trends of anthrax outbreaks and cases.

Results

A total of 38 outbreaks were reported in the Lowlands districts of Lesotho. District was significantly (p<0.0001) associated with outbreaks and cases, with the highest proportions of outbreaks (52.6%) and cases (70.2%) reported in Maseru. Significantly (p = 0.0004) higher proportions of anthrax outbreaks (78.9%) and cases (95.1%) were reported in the rainy-hot season compared to the dry-cold season. Five hundred and twenty-six (n = 526) anthrax cases were reported with significantly (p<0.0001) higher proportion of cases (70.3%) in cattle compared to other species. Higher proportion of anthrax cases (35.9%) were reported in 2008 and during the months of February (30.8%) and April (30.2%). There was no significant annual trend in anthrax outbreaks (r = 0.0282; p = 0.6213) and cases (r = 0.0873; p = 0.3512) over the study period.

Conclusion

The burden of anthrax in Lesotho is significantly higher in cattle. Anthrax outbreaks occur only in the lowland districts and follow a seasonal pattern. Therefore, more effort should be targeted at curbing the disease in cattle and the lowlands districts. Furthermore, there should be heightened monitoring of cases in the rainy season to ensure that resultant carcasses are disposed of appropriately to minimise future outbreaks.

Prediction of the potential global distribution for Biomphalaria straminea, an intermediate host for Schistosoma mansoni

BACKGROUND

Schistosomiasis is a snail-borne parasitic disease and is endemic in many tropical and subtropical countries. Biomphalaria straminea, an intermediate host for Schistosoma mansoni, is native to the southeastern part of South America and has established in other regions of South America, Central America and southern China during the last decades. S. mansoni is endemic in Africa, the Middle East, South America and the Caribbean. Knowledge of the potential global distribution of this snail is essential for risk assessment, monitoring, disease prevention and control.

METHODS AND FINDINGS

A comprehensive database of cross-continental occurrence for B. straminea was compiled to construct ecological models. We used several approaches to investigate the distribution of B. straminea, including direct comparison of climatic conditions, principal component analysis and niche overlap analyses to detect niche shifts. We also investigated the impacts of bioclimatic and human factors, and then used the bioclimatic and footprint layers to predict the potential distribution of B. straminea at global scale. We detected niche shifts accompanying the invasions of B. straminea in the Americas and China. The introduced populations had enlarged its habitats to subtropical regions where annual mean temperature is relatively low. Annual mean temperature, isothermality and temperature seasonality were identified as most important climatic features for the occurrence of B. straminea. Additionally, human factors improved the model prediction (P<0.001). Our model showed that under current climate conditions the snail should mostly be confined to the tropic and subtropic regions, including South America, Central America, Sub-Saharan Africa and Southeast Asia.

CONCLUSIONS

Our results confirmed that niche shifts took place in the invasions of B. straminea, in which bioclimatic and human factors played an important role. Our model predicted the global distribution of B. straminea based on habitat suitability, which would help for prioritizing monitoring and management efforts for B. straminea control in the context of ongoing climate change and human disturbances.

Spores and soil from six sides: interdisciplinarity and the environmental biology of anthrax (Bacillus anthracis)

Environmentally transmitted diseases are comparatively poorly understood and managed, and their ecology is particularly understudied. Here we identify challenges of studying environmental transmission and persistence with a six-sided interdisciplinary review of the biology of anthrax (Bacillus anthracis). Anthrax is a zoonotic disease capable of maintaining infectious spore banks in soil for decades (or even potentially centuries), and the mechanisms of its environmental persistence have been the topic of significant research and controversy. Where anthrax is endemic, it plays an important ecological role, shaping the dynamics of entire herbivore communities. The complex eco-epidemiology of anthrax, and the mysterious biology of Bacillus anthracis during its environmental stage, have necessitated an interdisciplinary approach to pathogen research. Here, we illustrate different disciplinary perspectives through key advances made by researchers working in Etosha National Park, a long-term ecological research site in Namibia that has exemplified the complexities of the enzootic process of anthrax over decades of surveillance. In Etosha, the role of scavengers and alternative routes (waterborne transmission and flies) has proved unimportant relative to the long-term persistence of anthrax spores in soil and their infection of herbivore hosts. Carcass deposition facilitates green-ups of vegetation to attract herbivores, potentially facilitated by the role of anthrax spores in the rhizosphere. The underlying seasonal pattern of vegetation, and herbivores' immune and behavioural responses to anthrax risk, interact to produce regular 'anthrax seasons' that appear to be a stable feature of the Etosha ecosystem. Through the lens of microbiologists, geneticists, immunologists, ecologists, epidemiologists, and clinicians, we discuss how anthrax dynamics are shaped at the smallest scale by population genetics and interactions within the bacterial communities up to the broadest scales of ecosystem structure. We illustrate the benefits and challenges of this interdisciplinary approach to disease ecology, and suggest ways anthrax might offer insights into the biology of other important pathogens. Bacillus anthracis, and the more recently emerged Bacillus cereus biovar anthracis, share key features with other environmentally transmitted pathogens, including several zoonoses and panzootics of special interest for global health and conservation efforts. Understanding the dynamics of anthrax, and developing interdisciplinary research programs that explore environmental persistence, is a critical step forward for understanding these emerging threats.

Ecological suitability modeling for anthrax in the Kruger National Park, South Africa

The spores of the soil-borne bacterium, Bacillus anthracis, which causes anthrax are highly resistant to adverse environmental conditions. Under ideal conditions, anthrax spores can survive for many years in the soil. Anthrax is known to be endemic in the northern part of Kruger National Park (KNP) in South Africa (SA), with occasional epidemics spreading southward. The aim of this study was to identify and map areas that are ecologically suitable for the harboring of B. anthracis spores within the KNP. Anthrax surveillance data and selected environmental variables were used as inputs to the maximum entropy (Maxent) species distribution modeling method. Anthrax positive carcasses from 1988–2011 in KNP (n = 597) and a total of 40 environmental variables were used to predict and evaluate their relative contribution to suitability for anthrax occurrence in KNP. The environmental variables that contributed the most to the occurrence of anthrax were soil type, normalized difference vegetation index (NDVI) and precipitation. Apart from the endemic Pafuri region, several other areas within KNP were classified as ecologically suitable. The outputs of this study could guide future surveillance efforts to focus on predicted suitable areas for anthrax, since the KNP currently uses passive surveillance to detect anthrax outbreaks.

A retrospective study of anthrax on the Ghaap Plateau, Northern Cape province of South Africa, with special reference to the 2007-2008 outbreaks

Anthrax is a zoonotic disease caused by the gram-positive, endospore-forming and soil-borne bacterium Bacillus anthracis. When in spore form, the organism can survive in dormancy in the environment for decades. It is a controlled disease of livestock and wild ungulates in South Africa. In South Africa, the two enzootic regions are the Kruger National Park and the Ghaap Plateau in the Northern Cape province. Farms on the Plateau span thousands of hectares comprising of wildlife - livestock mixed use farming. In 2007-2008, anthrax outbreaks in the province led to government officials intervening to aid farmers with control measures aimed at preventing further losses. Because of the ability of the organism to persist in the environment for prolonged periods, an environmental risk or isolation survey was carried out in 2012 to determine the efficacy of control measures employed during the 2007-2008, anthrax outbreaks. No B. anthracis could be isolated from the old carcass sites, even when bone fragments from the carcasses were still clearly evident. This is an indication that the control measures and protocols were apparently successful in stemming the continuity of spore deposits at previously positive carcass sites.