Ecological niche modeling of Bacillus anthracis on three continents: evidence for genetic-ecological divergence?

Mapping high probability area for the Bacillus anthracis occurrence in wildlife protected area, South Omo, Ethiopia

Anthrax is a zoonotic disease caused by a spore-forming gram-positive bacterium, Bacillus anthracis. Increased anthropogenic factors inside wildlife-protected areas may worsen the spillover of the disease at the interface. Consequently, environmental suitability prediction for B. anthracis spore survival to locate a high-risk area is urgent. Here, we identified a potentially suitable habitat and a high-risk area for appropriate control measures. Our result revealed that a relatively largest segment of Omo National Park, about 23.7% (1,218 square kilometers) of the total area; 36.6% (711 square kilometers) of Mago National Park, and 29.4% (489 square kilometers) of Tama wildlife Reserve predicted as a high-risk area for the anthrax occurrence in the current situation. Therefore, the findings of this study provide the priority area to focus on and allocate resources for effective surveillance, prevention, and control of anthrax before it causes devastating effects on wildlife.

The persistence of time: the lifespan of Bacillus anthracis spores in environmental reservoirs

Anthrax is a lethal bacterial zoonosis primarily affecting herbivorous wildlife and livestock. Upon host death Bacillus anthracis vegetative cells form spores capable of surviving for years in soil. Anthrax transmission requires host exposure to large spore doses. Thus, conditions that facilitate higher spore concentrations or promote spore survival will increase the probability that a pathogen reservoir infects future hosts. We investigated abiotic and pathogen genomic variation in relation to spore concentrations in surface soils (0-1 cm depth) at 40 plains zebra (Equus quagga) anthrax carcass sites in Namibia. Specifically, how initial spore concentrations and spore survival were affected by seasonality associated with the timing of host mortality, local soil characteristics, and pathogen genomic variation. Zebras dying of anthrax in wet seasons-the peak season for anthrax in Etosha National Park-had soil spore concentrations 1.36 orders of magnitude higher than those that died in dry seasons. No other variables considered affected spore concentrations, and spore survival rates did not differ among sites. Surface soils at these pathogen reservoirs remained culture positive for a range of 3.8-10.4 years after host death. Future research could evaluate if seasonal patterns in spore concentrations are driven by differences in sporulation success or levels of terminal bacteremia.

Predicting Suitable Areas for African Swine Fever Outbreaks in Wild Boars in South Korea and Their Implications for Managing High-Risk Pig Farms

African swine fever (ASF) is a highly contagious disease affecting domestic pigs and wild boars, with no effective vaccine or treatment available. In South Korea, extensive measures have been implemented to prevent ASF transmission between wild boars and ASF spillover from wild boars to pig farm sectors, including the search for ASF-infected carcasses in mountainous forests and the installation of fences across wide areas of these forests. To determine the priority search range for infected carcasses and establish pig farm-centered quarantine measures, it is necessary to predict the specific path of ASF outbreaks in wild boars and identify pig farms at high risk of ASF spillover from wild boars. Here, we aimed to predict suitable areas and geographical paths for ASF outbreaks in wild boars using the MaxEnt model and shortest-path betweenness centrality analysis. The analysis identified a high frequency of ASF outbreaks in areas with a suitability value ≥0.4 on the suitability map and in areas within a 1.8 km range from the path on the shortest-path map, indicating these areas were high-risk zones for ASF outbreaks. Among the 5063 pig farms analyzed, 37 were in the high-risk zone on the suitability map, 499 were in the high-risk zone on the shortest-path map, and 9 were in both risk zones. Of the 51 pig farm sectors with a dense distribution of pig farms (kernel density ≥ 8), 25 sectors were in contact with or partially overlapped the high risk zone on the suitability map, 18 sectors were located within the high risk zone on the shortest-path map, and 14 sectors were located within both risk zones. These findings aided in determining the priority range for searches for wild boar carcasses and enabled the establishment of preemptive ASF prevention measures around the pig farming sectors that are at risk of ASF spillover from wild boars.

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.

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.

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.

Participatory mapping identifies risk areas and environmental predictors of endemic anthrax in rural Africa

Disease mapping reveals geographical variability in incidence, which can help to prioritise control efforts. However, in areas where this is most needed, resources to generate the required data are often lacking. Participatory mapping, which makes use of indigenous knowledge, is a potential approach to identify risk areas for endemic diseases in low- and middle-income countries. Here we combine this method with Geographical Information System-based analyses of environmental variables as a novel approach to study endemic anthrax, caused by the spore-forming bacterium Bacillus anthracis, in rural Africa. Our aims were to: (1) identify high-risk anthrax areas using community knowledge; (2) enhance our understanding of the environmental characteristics associated with these areas; and (3) make spatial predictions of anthrax risk. Community members from the Ngorongoro Conservation Area (NCA), northern Tanzania, where anthrax is highly prevalent in both animals and humans, were asked to draw areas they perceived to pose anthrax risks to their livestock on geo-referenced maps. After digitisation, random points were generated within and outside the defined areas to represent high- and low-risk areas, respectively. Regression analyses were used to identify environmental variables that may predict anthrax risk. Results were combined to predict how the probability of being a high-risk area for anthrax varies across space. Participatory mapping identified fourteen discrete high-risk areas ranging from 0.2 to 212.9 km² in size and occupying 8.4% of the NCA. Areas that pose a high risk of anthrax were positively associated with factors that increase contact with Bacillus anthracis spores rather than those associated with the pathogen's survival: close proximity to inland water bodies, where wildlife and livestock congregate, and low organic carbon content, which may indicate an increased likelihood of animals grazing close to soil surface and ingesting spores. Predicted high-risk areas were located in the centre of the NCA, which is likely to be encountered by most herds during movements in search for resources. We demonstrate that participatory mapping combined with spatial analyses can provide novel insights into the geography of disease risk. This approach can be used to prioritise areas for control in low-resource settings, especially for diseases with environmental transmission.

Immunological Evidence of Variation in Exposure and Immune Response to Bacillus anthracis in Herbivores of Kruger and Etosha National Parks

Exposure and immunity to generalist pathogens differ among host species and vary across spatial scales. Anthrax, caused by a multi-host bacterial pathogen, Bacillus anthracis, is enzootic in Kruger National Park (KNP), South Africa and Etosha National Park (ENP), Namibia. These parks share many of the same potential host species, yet the main anthrax host in one (greater kudu (Tragelaphus strepsiceros) in KNP and plains zebra (Equus quagga) in ENP) is only a minor host in the other. We investigated species and spatial patterns in anthrax mortalities, B. anthracis exposure, and the ability to neutralize the anthrax lethal toxin to determine if observed host mortality differences between locations could be attributed to population-level variation in pathogen exposure and/or immune response. Using serum collected from zebra and kudu in high and low incidence areas of each park (18- 20 samples/species/area), we estimated pathogen exposure from anti-protective antigen (PA) antibody response using enzyme-linked immunosorbent assay (ELISA) and lethal toxin neutralization with a toxin neutralization assay (TNA). Serological evidence of pathogen exposure followed mortality patterns within each system (kudus: 95% positive in KNP versus 40% in ENP; zebras: 83% positive in ENP versus 63% in KNP). Animals in the high-incidence area of KNP had higher anti-PA responses than those in the low-incidence area, but there were no significant differences in exposure by area within ENP. Toxin neutralizing ability was higher for host populations with lower exposure prevalence, i.e., higher in ENP kudus and KNP zebras than their conspecifics in the other park. These results indicate that host species differ in their exposure to and adaptive immunity against B. anthracis in the two parks. These patterns may be due to environmental differences such as vegetation, rainfall patterns, landscape or forage availability between these systems and their interplay with host behavior (foraging or other risky behaviors), resulting in differences in exposure frequency and dose, and hence immune response.

The roles of environmental variation and parasite survival in virulence-transmission relationships

Disease outbreaks are a consequence of interactions among the three components of a host-parasite system: the infectious agent, the host and the environment. While virulence and transmission are widely investigated, most studies of parasite life-history trade-offs are conducted with theoretical models or tractable experimental systems where transmission is standardized and the environment controlled. Yet, biotic and abiotic environmental factors can strongly affect disease dynamics, and ultimately, host-parasite coevolution. Here, we review research on how environmental context alters virulence-transmission relationships, focusing on the off-host portion of the parasite life cycle, and how variation in parasite survival affects the evolution of virulence and transmission. We review three inter-related 'approaches' that have dominated the study of the evolution of virulence and transmission for different host-parasite systems: (i) evolutionary trade-off theory, (ii) parasite local adaptation and (iii) parasite phylodynamics. These approaches consider the role of the environment in virulence and transmission evolution from different angles, which entail different advantages and potential biases. We suggest improvements to how to investigate virulence-transmission relationships, through conceptual and methodological developments and taking environmental context into consideration. By combining developments in life-history evolution, phylogenetics, adaptive dynamics and comparative genomics, we can improve our understanding of virulence-transmission relationships across a diversity of host-parasite systems that have eluded experimental study of parasite life history.

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.

Spatial clustering of livestock Anthrax events associated with agro-ecological zones in Kenya, 1957-2017

BACKGROUND

Developing disease risk maps for priority endemic and episodic diseases is becoming increasingly important for more effective disease management, particularly in resource limited countries. For endemic and easily diagnosed diseases such as anthrax, using historical data to identify hotspots and start to define ecological risk factors of its occurrence is a plausible approach. Using 666 livestock anthrax events reported in Kenya over 60 years (1957-2017), we determined the temporal and spatial patterns of the disease as a step towards identifying and characterizing anthrax hotspots in the region.

METHODS

Data were initially aggregated by administrative unit and later analyzed by agro-ecological zones (AEZ) to reveal anthrax spatio-temporal trends and patterns. Variations in the occurrence of anthrax events were estimated by fitting Poisson generalized linear mixed-effects models to the data with AEZs and calendar months as fixed effects and sub-counties as random effects.

RESULTS

The country reported approximately 10 anthrax events annually, with the number increasing to as many as 50 annually by the year 2005. Spatial classification of the events in eight counties that reported the highest numbers revealed spatial clustering in certain administrative sub-counties, with 12% of the sub-counties responsible for over 30% of anthrax events, whereas 36% did not report any anthrax disease over the 60-year period. When segregated by AEZs, there was significantly greater risk of anthrax disease occurring in agro-alpine, high, and medium potential AEZs when compared to the agriculturally low potential arid and semi-arid AEZs of the country (p < 0.05). Interestingly, cattle were > 10 times more likely to be infected by B. anthracis than sheep, goats, or camels. There was lower risk of anthrax events in August (P = 0.034) and December (P = 0.061), months that follow long and short rain periods, respectively.

CONCLUSION

Taken together, these findings suggest existence of certain geographic, ecological, and demographic risk factors that promote B. anthracis persistence and trasmission in the disease hotspots.

Decontamination of soil contaminated at the surface with Bacillus anthracis spores using dry thermal treatment

In the event of a large, aerosol release of Bacillus anthracis spores in a major metropolitan area, soils and other outdoor materials may become contaminated with the biological agent. A study was conducted to assess the in-situ remediation of soil using a dry thermal treatment approach to inactivate a B. anthracis spore surrogate inoculated into soil samples. The study was conducted in two phases, using loam, clay and sand-based soils, as well as biological indicators and spore-inoculated stainless-steel coupons. Initial experiments were performed in an environmental test chamber with temperatures controlled between 80 and 110 °C, with and without added humidity, and with contact times ranging from 4 h to 7 weeks. Tests were then scaled up to assess the thermal inactivation of spores in small soil columns, in which a heating plate set to 141 °C was applied to the soil surface. These column tests were conducted to assess time requirements to inactivate spores as a function of soil depth and soil type. Results from the initial phase of testing showed that increasing the temperature and relative humidity reduced the time requirements to achieve samples in which no surrogate spores were detected. For the test at 80 °C with no added humidity, 49 days were required to achieve soil samples with no spores detected in clay and loam. At 110 °C, 24 h were required to achieve samples in which no spores were detected. In the column tests, no spores were detected at the 2.5 cm depth at four days and at the 5.1 cm depth at 21 days, for two of the three soils. The experiments described in the study demonstrate the feasibility of using dry thermal techniques to decontaminate soils that have been surficially contaminated with B. anthracis spores.

Insights into antimicrobial peptides in fighting anthrax: A review

Anthrax is an infectious disease occurring worldwide and is a threat to global society due to its possible misuse as a biological weapon. Bacillus anthracis is the etiologic agent of this disease which can be transmitted via inhalation, ingestion, and skin contact. Globally, it is estimated around 2000 anthrax cases occur per year. Upon infection, the organism can cause cytolysis of macrophage and produce exotoxin capable of inducing edema and lymphatic blockage. Another challenge posed by the organism is the ability to form spores in harsh conditions. Various antibiotics have been used to fight the disease. However, like many other microbes, B. anthracis may develop resistance, thus the discovery of new therapeutics is urgently required. Antimicrobial peptides (AMPs) have been discovered since 1980s and attracted researchers in the antimicrobial field. In this review, the work and studies on the attempts to discover potent AMPs to treat anthrax together with the brief overview of the synthesis and modification pathways of several AMPs have been presented.

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.

An Introductory Framework for Choosing Spatiotemporal Analytical Tools in Population-Level Eco-Epidemiological Research

Spatiotemporal visualization and analytical tools (SATs) are increasingly being applied to risk-based surveillance/monitoring of adverse health events affecting humans, animals, and ecosystems. Different disciplines use diverse SATs to address similar research questions. The juxtaposition of these diverse techniques provides a list of options for researchers who are new to population-level spatial eco-epidemiology. Here, we are conducting a narrative review to provide an overview of the multiple available SATs, and introducing a framework for choosing among them when addressing common research questions across disciplines. The framework is comprised of three stages: (a) pre-hypothesis testing stage, in which hypotheses regarding the spatial dependence of events are generated; (b) primary hypothesis testing stage, in which the existence of spatial dependence and patterns are tested; and (c) secondary-hypothesis testing and spatial modeling stage, in which predictions and inferences were made based on the identified spatial dependences and associated covariates. In this step-wise process, six key research questions are formulated, and the answers to those questions should lead researchers to select one or more methods from four broad categories of SATs: (T1) visualization and descriptive analysis; (T2) spatial/spatiotemporal dependence and pattern recognition; (T3) spatial smoothing and interpolation; and (T4) geographic correlation studies (i.e., spatial modeling and regression). The SATs described here include both those used for decades and also other relatively new tools. Through this framework review, we intend to facilitate the choice among available SATs and promote their interdisciplinary use to support improving human, animal, and ecosystem health.

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 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.

Recurrent Anthrax Outbreaks in Humans, Livestock, and Wildlife in the Same Locality, Kenya, 2014-2017

Epidemiologic data indicate a global distribution of anthrax outbreaks associated with certain ecosystems that promote survival and viability of Bacillus anthracis spores. Here, we characterized three anthrax outbreaks involving humans, livestock, and wildlife that occurred in the same locality in Kenya between 2014 and 2017. Clinical and epidemiologic data on the outbreaks were collected using active case finding and review of human, livestock, and wildlife health records. Information on temporal and spatial distribution of prior outbreaks in the area was collected using participatory epidemiology. The 2014-2017 outbreaks in Nakuru West subcounty affected 15 of 71 people who had contact with infected cattle (attack rate = 21.1%), including seven with gastrointestinal, six with cutaneous, and two with oropharyngeal forms of the disease. Two (13.3%) gastrointestinal human anthrax cases died. No human cases were associated with infected wildlife. Of the 54 cattle owned in 11 households affected, 20 died (attack rate = 37%). The 2015 outbreak resulted in death of 10.5% of the affected herbivorous wildlife at Lake Nakuru National Park, including 745 of 4,500 African buffaloes (species-specific mortality rate = 17%) and three of 18 endangered white rhinos (species-specific mortality rate = 16%). The species mortality rate ranged from 1% to 5% for the other affected wildlife species. Participatory epidemiology identified prior outbreaks between 1973 and 2011 in the same area. The frequency and severity of outbreaks in this area suggests that it is an anthrax hotspot ideal for investigating risk factors associated with long-term survival of anthrax spores and outbreak occurrence.

Comparison of spatiotemporal patterns of historic natural Anthrax outbreaks in Minnesota and Kazakhstan

Disease spread in populations is a consequence of the interaction between host, pathogen, and environment, i.e. the epidemiological triad. Yet the influences of each triad component may vary dramatically for different settings. Comparison of environmental, demographic, socio-economic, and historical backgrounds may support tailoring site-specific control measures. Because of the long-term survival of Bacillus anthracis, Anthrax is a suitable example for studying the influence of triad components in different endemic settings. We compared the spatiotemporal patterns of historic animal Anthrax records in two endemic areas, located at northern latitudes in the western and eastern hemispheres. Our goal was to compare the spatiotemporal patterns in Anthrax progression, intensity, direction, and recurrence (disease hot spots), in relation to epidemiological factors and potential trigger events. Reported animal cases in Minnesota, USA (n = 289 cases between 1912 and 2014) and Kazakhstan (n = 3,997 cases between 1933 and 2014) were analyzed using the spatiotemporal directionality test and the spatial scan statistic. Over the last century Anthrax occurrence in Minnesota was sporadic whereas Kazakhstan experienced a long-term epidemic. Nevertheless, the seasonality was comparable between sites, with a peak in August. Declining number of cases at both sites was attributed to vaccination and control measures. The spatiotemporal directionality test detected a relative northeastern directionality in disease spread for long-term trends in Minnesota, whereas a southwestern directionality was observed in Kazakhstan. In terms of recurrence, the maximum timespans between cases at the same location were 55 and 60 years for Minnesota and Kazakhstan, respectively. Disease hotspots were recognized in both settings, with spatially overlapping clusters years apart. Distribution of the spatiotemporal cluster radii between study sites supported suggestion of site-specific control zones. Spatiotemporal patterns of Anthrax occurrence in both endemic regions were attributed to multiple potential trigger events including major river floods, changes in land use, agriculture, and susceptible livestock populations. Results here help to understand the long-term epidemiological dynamics of Anthrax while providing suggestions to the design and implementation of prevention and control programs, in endemic settings.

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.

Modeling R₀ for Pathogens with Environmental Transmission: Animal Movements, Pathogen Populations, and Local Infectious Zones

How a disease is transmitted affects our ability to determine R₀, the average number of new cases caused by an infectious host at the onset of an epidemic. R₀ becomes progressively more difficult to compute as transmission varies from directly transmitted diseases to diseases that are vector-borne to environmentally transmitted diseases. Pathogens responsible for diseases with environmental transmission are typically maintained in environmental reservoirs that exhibit a complex spatial distribution of local infectious zones (LIZs). Understanding host encounters with LIZs and pathogen persistence within LIZs is required for an accurate R₀ and modeling these contacts requires an integrated geospatial and dynamical systems approach. Here we review how interactions between host and pathogen populations and environmental reservoirs are driven by landscape-level variables, and synthesize the quantitative framework needed to formulate outbreak response and disease control.

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.

High probability areas for ASF infection in China along the Russian and Korean borders

African swine fever (ASF) is a transcontinental, contagious, fatal virus disease of pig with devastating socioeconomic impacts. Interaction between infected wild boar and domestic pig may spread the virus. The disease is spreading fast from the west of Eurasia towards ASF-free China. Consequently, prediction of the distribution of ASF along the Sino-Russian-Korean borders is urgent. Our area of interest is Northeast China. The reported ASF-locations in 11 contiguous countries from the Baltic to the Russian Federation were extracted from the archive of the World Organization for Animal Health from July 19, 2007 to March 27, 2017. The locational records of the wild boar were obtained from literature. The environmental predictor variables were downloaded from the WorldClim website. Spatial rarefication and pair-wise geographic distance comparison were applied to minimize spatial autocorrelation of presence points. Principal component analysis (PCA) was used to minimize multi-collinearity among predictor variables. We selected the maximum entropy algorithm for spatial modelling of ASF and wild boar separately, combined the wild boar prediction with the domestic pig census in a single map of suids and overlaid the ASF with the suids map. The accuracy of the models was assessed by the AUC. PCA delivered five components accounting for 95.7% of the variance. Spatial autocorrelation was shown to be insignificant for both ASF and wild boar records. The spatial models showed high mean AUC (0.92 and 0.97) combined with low standard deviations (0.003 and 0.006) for ASF and wild boar, respectively. The overlay of the ASF and suids maps suggests that a relatively short sector of the Sino-Russian border has a high probability entry point of ASF at current conditions. Two sectors of the Sino-Korean border present an elevated risk.

Climatic influence on anthrax suitability in warming northern latitudes

Climate change is impacting ecosystem structure and function, with potentially drastic downstream effects on human and animal health. Emerging zoonotic diseases are expected to be particularly vulnerable to climate and biodiversity disturbance. Anthrax is an archetypal zoonosis that manifests its most significant burden on vulnerable pastoralist communities. The current study sought to investigate the influence of temperature increases on geographic anthrax suitability in the temperate, boreal, and arctic North, where observed climate impact has been rapid. This study also explored the influence of climate relative to more traditional factors, such as livestock distribution, ungulate biodiversity, and soil-water balance, in demarcating risk. Machine learning was used to model anthrax suitability in northern latitudes. The model identified climate, livestock density and wild ungulate species richness as the most influential features in predicting suitability. These findings highlight the significance of warming temperatures for anthrax ecology in northern latitudes, and suggest potential mitigating effects of interventions targeting megafauna biodiversity conservation in grassland ecosystems, and animal health promotion among small to midsize livestock herds.

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.

Going through the motions: incorporating movement analyses into disease research

Though epidemiology dates back to the 1700s, most mathematical representations of epidemics still use transmission rates averaged at the population scale, especially for wildlife diseases. In simplifying the contact process, we ignore the heterogeneities in host movements that complicate the real world, and overlook their impact on spatiotemporal patterns of disease burden. Movement ecology offers a set of tools that help unpack the transmission process, letting researchers more accurately model how animals within a population interact and spread pathogens. Analytical techniques from this growing field can also help expose the reverse process: how infection impacts movement behaviours, and therefore other ecological processes like feeding, reproduction, and dispersal. Here, we synthesise the contributions of movement ecology in disease research, with a particular focus on studies that have successfully used movement-based methods to quantify individual heterogeneity in exposure and transmission risk. Throughout, we highlight the rapid growth of both disease and movement ecology and comment on promising but unexplored avenues for research at their overlap. Ultimately, we suggest, including movement empowers ecologists to pose new questions, expanding our understanding of host-pathogen dynamics and improving our predictive capacity for wildlife and even human diseases.

A Framework for Modeling Emerging Diseases to Inform Management

The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.

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.

Maximum entropy modeling risk of anthrax in the Republic of Kazakhstan

The objective of this study was to zone the territory of the Republic of Kazakhstan (RK) into risk categories according to the probability of anthrax emergence in farm animals as stipulated by the re-activation of preserved natural foci. We used historical data on anthrax morbidity in farm animals during the period 1933 - 2014, collected by the veterinary service of the RK. The database covers the entire territory of the RK and contains 4058 anthrax outbreaks tied to 1798 unique locations. Considering the strongly pronounced natural focality of anthrax, we employed environmental niche modeling (Maxent) to reveal patterns in the outbreaks' linkages to specific combinations of environmental factors. The set of bioclimatic factors BIOCLIM, derived from remote sensing data, the altitude above sea level, the land cover type, the maximum green vegetation fraction (MGVF) and the soil type were examined as explanatory variables. The model demonstrated good predictive ability, while the MGVF, the bioclimatic variables reflecting precipitation level and humidity, and the soil type were found to contribute most significantly to the model. A continuous probability surface was obtained that reflects the suitability of the study area for the emergence of anthrax outbreaks. The surface was turned into a categorical risk map by averaging the probabilities within the administrative divisions at the 2nd level and putting them into four categories of risk, namely: low, medium, high and very high risk zones, where very high risk refers to more than 50% suitability to the disease re-emergence and low risk refers to less than 10% suitability. The map indicated increased risk of anthrax re-emergence in the districts along the northern, eastern and south-eastern borders of the country. It was recommended that the national veterinary service uses the risk map for the development of contra-epizootic measures aimed at the prevention of anthrax re-emergence in historically affected regions of the RK. The map can also be considered when developing large-scale construction projects in the areas comprising preserved soil foci of anthrax.

Modeling the Ecological Niche of Bacillus anthracis to Map Anthrax Risk in Kyrgyzstan

Anthrax, caused by the environmental bacterium Bacillus anthracis, is an important zoonosis nearly worldwide. In Central Asia, anthrax represents a major veterinary and public health concern. In the Republic of Kyrgyzstan, ongoing anthrax outbreaks have been reported in humans associated with handling infected livestock and contaminated animal by-products such as meat or hides. The current anthrax situation has prompted calls for improved insights into the epidemiology, ecology, and spatial distribution of the disease in Kyrgyzstan to better inform control and surveillance. Disease control for both humans and livestock relies on annual livestock vaccination ahead of outbreaks. Toward this, we used a historic database of livestock anthrax reported from 1932 to 2006 mapped at high resolution to develop an ecological niche model-based prediction of B. anthracis across Kyrgyzstan and identified spatial clusters of livestock anthrax using a cluster morphology statistic. We also defined the seasonality of outbreaks in livestock. Cattle were the most frequently reported across the time period, with the greatest number of cases in late summer months. Our niche models defined four areas as suitable to support pathogen persistence, the plateaus near Talas and Bishkek, the valleys of western Kyrgyzstan along the Fergana Valley, and the low-lying areas along the shore of Lake Isyk-Kul. These areas should be considered "at risk" for livestock anthrax and subsequent human cases. Areas defined by the niche models can be used to prioritize anthrax surveillance and inform efforts to target livestock vaccination campaigns.

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

The ecology and distribution of B. anthracis in Australia is not well understood, despite the continued occurrence of anthrax outbreaks in the eastern states of the country. Efforts to estimate the spatial extent of the risk of disease have been limited to a qualitative definition of an anthrax belt extending from southeast Queensland through the centre of New South Wales and into northern Victoria. This definition of the anthrax belt does not consider the role of environmental conditions in the distribution of B. anthracis. Here, we used the genetic algorithm for rule-set prediction model system (GARP), historical anthrax outbreaks and environmental data to model the ecological niche of B. anthracis and predict its potential geographic distribution in Australia. Our models reveal the niche of B. anthracis in Australia is characterized by a narrow range of ecological conditions concentrated in two disjunct corridors. The most dominant corridor, used to redefine a new anthrax belt, parallels the Eastern Highlands and runs from north Victoria to central east Queensland through the centre of New South Wales. This study has redefined the anthrax belt in eastern Australia and provides insights about the ecological factors that limit the distribution of B. anthracis at the continental scale for Australia. The geographic distributions identified can help inform anthrax surveillance strategies by public and veterinary health agencies.

This study explores the spatial ecology of Bacillus anthracis, the causative agent of anthrax disease, in Australia. Globally, anthrax is a neglected zoonotic disease that primarily affect herbivores and incidentally humans and all warm-blooded animals. Here, we used historic anthrax outbreaks for the period 1996–2013 and environmental factors in an ecological niche modelling framework to quantitatively define the ecological niche of B. anthracis using a genetic algorithm. This was projected onto the continental landscape of Australia to predict the geographic distribution of the pathogen. The ecological niche of B. anthracis is characterized by a narrow range of ecological conditions, which are geographically concentrated in two disjunct corridors: a dominant corridor paralleling the Eastern Highlands runs from north Victoria to central east Queensland through the centre of New South Wales, while another corridor was predicted in the southwest of Western Australia. These findings provide an estimate of the potential geographic distribution of B. anthracis, and can help inform anthrax disease surveillance across Australia.

Predicting Disease Risk, Identifying Stakeholders, and Informing Control Strategies: A Case Study of Anthrax in Montana

Infectious diseases that affect wildlife and livestock are challenging to manage and can lead to large-scale die-offs, economic losses, and threats to human health. The management of infectious diseases in wildlife and livestock is made easier with knowledge of disease risk across space and identifying stakeholders associated with high-risk landscapes. This study focuses on anthrax, caused by the bacterium Bacillus anthracis, risk to wildlife and livestock in Montana. There is a history of anthrax in Montana, but the spatial extent of disease risk and subsequent wildlife species at risk are not known. Our objective was to predict the potential geographic distribution of anthrax risk across Montana, identify wildlife species at risk and their distributions, and define stakeholders. We used an ecological niche model to predict the potential distribution of anthrax risk. We overlaid susceptible wildlife species distributions and land ownership delineations on our risk map. We found that there was an extensive region across Montana predicted as potential anthrax risk. These potentially risky landscapes overlapped the ranges of all 6 ungulate species considered in the analysis and livestock grazing allotments, and this overlap was on public and private land for all species. Our findings suggest that there is the potential for a multi-species anthrax outbreak on multiple landscapes across Montana. Our potential anthrax risk map can be used to prioritize landscapes for surveillance and for implementing livestock vaccination programs.

Historical evolution of human anthrax from occupational disease to potentially global threat as bioweapon

PURPOSE

Anthrax is caused by Bacillus anthracis, which can naturally infect livestock, wildlife and occupationally exposed humans. However, for its resistance due to spore formation, ease of dissemination, persistence in the environment and high virulence, B. anthracis has been considered the most serious bioterrorism agent for a long time. During the last century anthrax evolved from limited natural disease to potentially global threat if used as bioweapon. Several factors may mitigate the consequences of an anthrax attack, including 1. the capability to promptly recognize and manage the illness and its public health consequences; 2. the limitation of secondary contamination risk through an appropriate decontamination; and 3. the evolution of genotyping methods (for microbes characterization at high resolution level) that can influence the course and/or focus of investigations, impacting the response of the government to an attack.

METHODS

A PubMed search has been done using the key words “bioterrorism anthrax”.

RESULTS

Over one thousand papers have been screened and the most significant examined to present a comprehensive literature review in order to discuss the current knowledge and strategies in preparedness for a possible deliberate release of B. anthracis spores and to indicate the most current and complete documents in which to deepen.

CONCLUSIONS

The comprehensive analysis of the two most relevant unnatural anthrax release events, Sverdlovsk in the former Soviet Union (1979) and the contaminated letters in the USA (2001), shows that inhalational anthrax may easily and cheaply be spread resulting in serious consequences. The damage caused by an anthrax attack can be limited if public health organization, first responders, researchers and investigators will be able to promptly manage anthrax cases and use new technologies for decontamination methods and in forensic microbiology.

Elk Resource Selection and Implications for Anthrax Management in Montana

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.

Bacillus anthracis Diversity and Geographic Potential across Nigeria, Cameroon and Chad: Further Support of a Novel West African Lineage

Zoonoses, diseases affecting both humans and animals, can exert tremendous pressures on human and veterinary health systems, particularly in resource limited countries. Anthrax is one such zoonosis of concern and is a disease requiring greater public health attention in Nigeria. Here we describe the genetic diversity of Bacillus anthracis in Nigeria and compare it to Chad, Cameroon and a broader global dataset based on the multiple locus variable number tandem repeat (MLVA-25) genetic typing system. Nigerian B. anthracis isolates had identical MLVA genotypes and could only be resolved by measuring highly mutable single nucleotide repeats (SNRs). The Nigerian MLVA genotype was identical or highly genetically similar to those in the neighboring countries, confirming the strains belong to this unique West African lineage. Interestingly, sequence data from a Nigerian isolate shares the anthrose deficient genotypes previously described for strains in this region, which may be associated with vaccine evasion. Strains in this study were isolated over six decades, indicating a high level of temporal strain stability regionally. Ecological niche models were used to predict the geographic distribution of the pathogen for all three countries. We describe a west-east habitat corridor through northern Nigeria extending into Chad and Cameroon. Ecological niche models and genetic results show B. anthracis to be ecologically established in Nigeria. These findings expand our understanding of the global B. anthracis population structure and can guide regional anthrax surveillance and control planning.

Anthrax, caused by the soil-borne bacterium Bacillus anthracis, is a disease with important public health and national security implications globally. Understanding the global genetic diversity of the pathogen is important for epidemiological and forensic investigations of anthrax events. Toward this, we describe B. anthracis genetic diversity in Nigeria and confirm it belongs to a unique West African genetic group not yet reported beyond neighboring Cameroon and Chad and Mali. This refines the global phylogeny of B. anthracis, allowing the development of more accurate diagnostics. We coupled these efforts with ecological niche modeling to map the geographic distribution of this strain group across the region. Suitable habitat for the pathogen is predicted across central Nigeria from west to east into Cameroon and Chad. Understanding the geography of B. anthracis plays an important role in informing public health by targeting disease control to high risk regions. This is particularly important in resource limited areas where intervention strategies are constrained and zoonotic disease risk is high.

Spatial and temporal epidemiological analysis in the Big Data era

Concurrent with global economic development in the last 50 years, the opportunities for the spread of existing diseases and emergence of new infectious pathogens, have increased substantially. The activities associated with the enormously intensified global connectivity have resulted in large amounts of data being generated, which in turn provides opportunities for generating knowledge that will allow more effective management of animal and human health risks. This so-called Big Data has, more recently, been accompanied by the Internet of Things which highlights the increasing presence of a wide range of sensors, interconnected via the Internet. Analysis of this data needs to exploit its complexity, accommodate variation in data quality and should take advantage of its spatial and temporal dimensions, where available. Apart from the development of hardware technologies and networking/communication infrastructure, it is necessary to develop appropriate data management tools that make this data accessible for analysis. This includes relational databases, geographical information systems and most recently, cloud-based data storage such as Hadoop distributed file systems. While the development in analytical methodologies has not quite caught up with the data deluge, important advances have been made in a number of areas, including spatial and temporal data analysis where the spectrum of analytical methods ranges from visualisation and exploratory analysis, to modelling. While there used to be a primary focus on statistical science in terms of methodological development for data analysis, the newly emerged discipline of data science is a reflection of the challenges presented by the need to integrate diverse data sources and exploit them using novel data- and knowledge-driven modelling methods while simultaneously recognising the value of quantitative as well as qualitative analytical approaches. Machine learning regression methods, which are more robust and can handle large datasets faster than classical regression approaches, are now also used to analyse spatial and spatio-temporal data. Multi-criteria decision analysis methods have gained greater acceptance, due in part, to the need to increasingly combine data from diverse sources including published scientific information and expert opinion in an attempt to fill important knowledge gaps. The opportunities for more effective prevention, detection and control of animal health threats arising from these developments are immense, but not without risks given the different types, and much higher frequency, of biases associated with these data.