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

A case study on anthrax in an eight-month old infant at Kyrgyz Republic

Anthrax remains a threat, especially in countries like Kyrgyzstan with developed livestock farming. Despite preventive efforts, sporadic outbreaks endure on an annual basis, transmitted from infected animals to humans. Here, we report a severe anthrax case in an 8-month-old child known to be caused when a sick calf was slaughtered in the neighborhood without proper protocols, resulting in intra-family infection. This underscores the importance of swift diagnosis, treatment, preventive measures, and awareness of zoonotic infections, animal vaccination and adherence to sanitary and veterinary protocols.

Predicting potential transmission risk of Everglades virus in Florida using mosquito blood meal identifications

The overlap between arbovirus host, arthropod vectors, and pathogen distributions in environmentally suitable habitats represents a nidus where risk for pathogen transmission may occur. Everglades virus (EVEV), subtype II Venezuelan equine encephalitis virus (VEEV), is endemic to southern Florida where it is transmitted by the endemic vector Culex cedecei between muroid rodent hosts. We developed an ecological niche model (ENM) to predict areas in Florida suitable for EVEV transmission based upon georeferenced vector-host interactions from PCR-based blood meal analysis from blood-engorged female Cx. cedecei females. Thirteen environmental variables were used for model calibration, including bioclimatic variables derived from Daymet 1 km daily temperature and precipitation values, and land use and land cover data representing percent land cover derived within a 2.5 km buffer from 2019 National Land Cover Database (NLCD) program. Maximum temperature of the warmest month, minimum temperature of the coldest month, and precipitation of the driest month contributed 31.6%, 28.5% and 19.9% to ENM performance. The land cover types contributing the greatest to the model performance were percent landcover of emergent herbaceous and woody wetlands which contributed 5.2% and 4.3% to model performance, respectively. Results of the model output showed high suitability for Cx. cedecei feeding on rodents throughout the southwestern portion of the state and pockets of high suitability along the northern east coast of Florida, while areas with low suitability included the Miami-Dade metropolitan area and most of northern Florida and the Panhandle. Comparing predicted distributions of Cx. cedecei feeding upon rodent hosts in the present study to historical human cases of EVEV disease, as well as antibodies in wildlife show substantial overlap with areas predicted moderate to highly suitable for these vector/host associations. As such, the findings of this study likely predict the most accurate distribution of the nidus of EVEV to date, indicating that this method allows for better inference of potential transmission areas than models which only consider the vector or vertebrate host species individually. A similar approach using host blood meals of other arboviruses can be used to predict potential areas of virus transmission for other vector-borne diseases.

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.

Seasonality and Ecological Suitability Modelling for Anthrax (Bacillus anthracis) in Western Africa

Simple Summary

Anthrax is a globally distributed, neglected, underreported, soil-borne zoonotic disease. In West Africa, the disease is hyper-endemic, severely affecting the livestock sector. Many challenges exist to control the disease in this region, particularly constraints on financial and human resources. Therefore, methods that can be utilized to improve reporting, guide and prioritize surveillance and control activities and rationalize the allocation of limited resources are crucial. In this study, we showed how to optimize the use of fragmented, heterogeneous and limited precise reporting data of anthrax in Burkina Faso, Ghana, Togo, Benin and Niger to understand risk periods as well as identify and predict risk areas. To achieve this, we used anthrax data from different databases in combination with environmental and climate variables and geospatial remote sensing techniques. Our study demonstrated that the number of anthrax outbreaks by month increase with the increasing monthly rates of change in precipitation and normalized difference vegetation index (NDVI) during the transition period from the dry to the wet season. Livestock density, precipitation, NDVI and alkaline soils were the main predictors of anthrax suitability in the region. Our findings on anthrax seasonality and ecological suitability can inform surveillance, prevention and control programs undertaken by animal and public health authorities and enhance collaborative One Health strategies.

Abstract

Anthrax is hyper-endemic in West Africa affecting wildlife, livestock and humans. Prediction is difficult due to the lack of accurate outbreak data. However, predicting the risk of infection is important for public health, wildlife conservation and livestock economies. In this study, the seasonality of anthrax outbreaks in West Africa was investigated using climate time series and ecological niche modeling to identify environmental factors related to anthrax occurrence, develop geospatial risk maps and identify seasonal patterns. Outbreak data in livestock, wildlife and humans between 2010 and 2018 were compiled from different sources and analyzed against monthly rates of change in precipitation, normalized difference vegetation index (NDVI) and land surface temperature. Maximum Entropy was used to predict and map the environmental suitability of anthrax occurrence. The findings showed that: (i) Anthrax outbreaks significantly (99%) increased with incremental changes in monthly precipitation and vegetation growth and decremental changes in monthly temperature during January–June. This explains the occurrence of the anthrax peak during the early wet season in West Africa. (ii) Livestock density, precipitation seasonality, NDVI and alkaline soils were the main predictors of anthrax suitability. (iii) Our approach optimized the use of limited and heterogeneous datasets and ecological niche modeling, demonstrating the value of integrated disease notification data and outbreak reports to generate risk maps. Our findings can inform public, animal and environmental health and enhance national and regional One Health disease control strategies.

John HK, Richards AL, Ryan SJ. Exploring the Niche of Rickettsia montanensis (Rickettsiales: Rickettsiaceae) Infection of the American Dog Tick (Acari: Ixodidae), Using Multiple Species Distribution Model Approaches

The American dog tick, Dermacentor variabilis (Say) (Acari: Ixodidae), is a vector for several human disease-causing pathogens such as tularemia, Rocky Mountain spotted fever, and the understudied spotted fever group rickettsiae (SFGR) infection caused by Rickettsia montanensis. It is important for public health planning and intervention to understand the distribution of this tick and pathogen encounter risk. Risk is often described in terms of vector distribution, but greatest risk may be concentrated where more vectors are positive for a given pathogen. When assessing species distributions, the choice of modeling framework and spatial layers used to make predictions are important. We first updated the modeled distribution of D. variabilis and R. montanensis using maximum entropy (MaxEnt), refining bioclimatic data inputs, and including soil variables. We then compared geospatial predictions from five species distribution modeling frameworks. In contrast to previous work, we additionally assessed whether the R. montanensis positive D. variabilis distribution is nested within a larger overall D. variabilis distribution, representing a fitness cost hypothesis. We found that 1) adding soil layers improved the accuracy of the MaxEnt model; 2) the predicted 'infected niche' was smaller than the overall predicted niche across all models; and 3) each model predicted different sizes of suitable niche, at different levels of probability. Importantly, the models were not directly comparable in output style, which could create confusion in interpretation when developing planning tools. The random forest (RF) model had the best measured validity and fit, suggesting it may be most appropriate to these data.

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.

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.

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.

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.

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.

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.

The Bacillus cereus Group: Bacillus Species with Pathogenic Potential

The Bacillus cereus group includes several Bacillus species with closely related phylogeny. The most well-studied members of the group, B. anthracis, B. cereus, and B. thuringiensis, are known for their pathogenic potential. Here, we present the historical rationale for speciation and discuss shared and unique features of these bacteria. Aspects of cell morphology and physiology, and genome sequence similarity and gene synteny support close evolutionary relationships for these three species. For many strains, distinct differences in virulence factor synthesis provide facile means for species assignment. B. anthracis is the causative agent of anthrax. Some B. cereus strains are commonly recognized as food poisoning agents, but strains can also cause localized wound and eye infections as well as systemic disease. Certain B. thuringiensis strains are entomopathogens and have been commercialized for use as biopesticides, while some strains have been reported to cause infection in immunocompromised individuals. In this article we compare and contrast B. anthracis, B. cereus, and B. thuringiensis, including ecology, cell structure and development, virulence attributes, gene regulation and genetic exchange systems, and experimental models of disease.

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.