Modeling the spatial distribution of anthrax in southern Kenya

Multiple pathogens co-exposure and associated risk factors among cattle reared in a wildlife-livestock interface area in Kenya

Introduction

Understanding multi-pathogen infections/exposures in livestock is critical to inform prevention and control measures against infectious diseases. We investigated the co-exposure of foot-and-mouth disease virus (FMDV), Brucella spp., Leptospira spp., and Coxiella burnetii in cattle in three zones stratified by land use change and with different wildlife-livestock interactions in Narok county, Kenya. We also assessed potential risk factors associated with the transmission of these pathogens in cattle.

Methods

We identified five villages purposively, two each for areas with intensive (zone 1) and moderate wildlife-livestock interactions (zone 2) and one for locations with low wildlife-livestock interactions (zone 3). We sampled 1,170 cattle from 390 herds through a cross-sectional study and tested the serum samples for antibodies against the focal pathogens using enzyme-linked immunosorbent assay (ELISA) kits. A questionnaire was administered to gather epidemiological data on the putative risk factors associated with cattle's exposure to the investigated pathogens. Data were analyzed using the Bayesian hierarchical models with herd number as a random effect to adjust for the within-herd clustering of the various co-exposures among cattle.

Results

Overall, 88.0% (95% CI: 85.0-90.5) of the cattle tested positive for at least one of the targeted pathogens, while 41.7% (95% CI: 37.7-45.8) were seropositive to at least two pathogens. FMDV and Brucella spp. had the highest co-exposure at 33.7% (95% CI: 30.9-36.5), followed by FMDV and Leptospira spp. (21.8%, 95% CI: 19.5-24.4), Leptospira spp. and Brucella spp. (8.8%, 95% CI: 7.2-10.6), FMDV and C. burnetii (1.5%, 95% CI: 0.7-2.8), Brucella spp. and C. burnetii (1.0%, 95% CI: 0.3-2.2), and lowest for Leptospira spp. and C. burnetii (0.3%, 95% CI: 0.0-1.2). Cattle with FMDV and Brucella spp., and Brucella spp. and Leptospira spp. co-exposures and those simultaneously exposed to FMDV, Brucella spp. and Leptospira spp. were significantly higher in zone 1 than in zones 2 and 3. However, FMDV and Leptospira spp. co-exposure was higher in zones 1 and 2 than zone 3.

Discussion/conclusion

We recommend the establishment of a One Health surveillance system in the study area to reduce the morbidity of the targeted zoonotic pathogens in cattle and the risks of transmission to humans.

Impact of infectious diseases on wild bovidae populations in Thailand: insights from population modelling and disease dynamics

The wildlife and livestock interface is vital for wildlife conservation and habitat management. Infectious diseases maintained by domestic species may impact threatened species such as Asian bovids, as they share natural resources and habitats. To predict the population impact of infectious diseases with different traits, we used stochastic mathematical models to simulate the population dynamics over 100 years for 100 times in a model gaur (Bos gaurus) population with and without disease. We simulated repeated introductions from a reservoir, such as domestic cattle. We selected six bovine infectious diseases; anthrax, bovine tuberculosis, haemorrhagic septicaemia, lumpy skin disease, foot and mouth disease and brucellosis, all of which have caused outbreaks in wildlife populations. From a starting population of 300, the disease-free population increased by an average of 228% over 100 years. Brucellosis with frequency-dependent transmission showed the highest average population declines (-97%), with population extinction occurring 16% of the time. Foot and mouth disease with frequency-dependent transmission showed the lowest impact, with an average population increase of 200%. Overall, acute infections with very high or low fatality had the lowest impact, whereas chronic infections produced the greatest population decline. These results may help disease management and surveillance strategies support wildlife conservation.

Molecular characterization of an outbreak-involved Bacillus anthracis strain confirms the spillover of anthrax from West Africa

BACKGROUND

Anthrax, a zoonotic disease caused by the spore-forming bacterium Bacillus anthracis, remains a major global public health concern, especially in countries with limited resources. Sierra Leone, a West African country historically plagued by anthrax, has almost been out of report on this disease in recent decades. In this study, we described a large-scale anthrax outbreak affecting both animals and humans and attempted to characterize the pathogen using molecular techniques.

METHODS

The causative agent of the animal outbreak in Port Loko District, Sierra Leone, between March and May 2022 was identified using the nanopore sequencing technique. A nationwide active surveillance was implemented from May 2022 to June 2023 to monitor the occurrence of anthrax-specific symptoms in humans. Suspected cases were subsequently verified using quantitative polymerase chain reaction. Full-genome sequencing was accomplished by combining long-read and short-read sequencing methods. Subsequent phylogenetic analysis was performed based on the full-chromosome single nucleotide polymorphisms.

RESULTS

The outbreak in Port Loko District, Sierra Leone, led to the death of 233 animals between March 26th and May 16th, 2022. We ruled out the initial suspicion of Anaplasma species and successfully identified B. anthracis as the causative agent of the outbreak. As a result of the government's prompt response, out of the 49 suspected human cases identified during the one-year active surveillance, only 6 human cases tested positive, all within the first month after the official declaration of the outbreak. The phylogenetic analysis indicated that the BaSL2022 isolate responsible for the outbreak was positioned in the A.Br.153 clade within the TransEuroAsian group of B. anthracis.

CONCLUSIONS

We successfully identified a large-scale anthrax outbreak in Sierra Leone. The causative isolate of B. anthracis, BaSL2022, phylogenetically bridged other lineages in A.Br.153 clade and neighboring genetic groups, A.Br.144 and A.Br.148, eventually confirming the spillover of anthrax from West Africa. Given the wide dissemination of B. anthracis spores, it is highly advisable to effectively monitor the potential reoccurrence of anthrax outbreaks and to launch campaigns to improve public awareness regarding anthrax in Sierra Leone.

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

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

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

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

The potential distribution of Bacillus anthracis suitability across Uganda using INLA

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

A Retrospective Study on the Epidemiology of Anthrax Among Livestock from 2011 to 2020 in Awi Administrative Zone, Amhara Region, Northwest Ethiopia

Background

In Ethiopia, anthrax is the second most important zoonotic disease, next to rabies. Data quantifying occurrence and distribution of animal anthrax in Awi administrative zone of Amhara region, Ethiopia, are limited. Thus, this study was conducted to describe the distribution of animal anthrax between 2011 and 2020 in Awi zone.

Methods

This study used secondary data of animal anthrax that occurred in the Awi zone and reported to the Regional and National Veterinary Authority between 2011 and 2020.

Results

A total of 1262 cases of anthrax in animals and 324 animals that died due to anthrax were reported. The highest number of anthrax cases were reported in 2012 (n = 671), sharing 48.9% of the 10-year animal anthrax reported. However, the highest number of animal death due to anthrax (n = 104) was reported in 2014. The overall case fatality rate of anthrax was 25.67% (n = 324). The highest animal anthrax cases (n = 984; 77.97%) and deaths (n = 259; 79.94%) were recorded in Bovine. The highest cases of anthrax were registered in May (n = 313), while no anthrax case was reported during December. The highest and lowest number of animal death due to anthrax were reported during July (n = 64) and January (n = 6), respectively. The highest number of anthrax cases was reported in the hot-dry season (n = 479; 37.96%) whereas the lowest was reported during the cold-dry season (n = 30; 2.38%).

Conclusion

The current study revealed a considerable number of animal anthrax cases and deaths in Awi zone every year. Hence, it is necessary for practicing prevention strategies including immunization programs before the peak season of anthrax outbreaks.

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

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

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

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

Anthrax outbreak amidst the COVID-19 pandemic in Africa: Challenges and possible solutions

Anthrax and coronavirus disease 2019 (COVID-19) are both notable zoonoses that have high morbidity and mortality, not to mention adverse socio-economic and health consequences on the communities they ravage. Anthrax wreaks disease amongst mammalian species worldwide and has an endemic distribution in Africa and Asia. Kenya, for example, records an average of 10 outbreaks annually. In 2014 and 2017, it held anthrax attack rates of 15% and 29%, respectively, and case fatality rates of 1–5%. As with COVID-19, effective surveillance, containment, and vaccination programs are crucial in the fight against anthrax. While there is no evidence of direct, human-to-human transmission of anthrax currently, Bacillus anthracis remains a disease of public health concern that serves to fuel the devastating effects of SARS-CoV-2 in African communities. In this commentary, we examine anthrax spread in Africa amidst COVID-19, the challenges faced by these simultaneous zoonoses, and the efforts put to combat both equally.

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.

Ecological Niche Model of Bacillus cereus Group Isolates Containing a Homologue of the pXO1 Anthrax Toxin Genes Infecting Metalworkers in the United States

While Bacillus cereus typically causes opportunistic infections in humans, within the last three decades, severe and fatal infections caused by isolates of the B. cereus group harboring anthrax toxin genes have been reported in the United States. From 1994 to 2020, seven cases of anthrax-like illness resulting from these isolates have been identified. With one exception, the cases have occurred in the Gulf States region of the United States among metalworkers. We aimed to develop an ecological niche model (ENM) to estimate a spatial area conducive to the survival of these organisms based on the presence of known human infections and environmental variables. The estimated ecological niche for B. cereus was modeled with the maximum entropy algorithm (Maxent). Environmental variables contributing most to the model were soil characteristics (cation exchange capacity, carbon content, soil pH), temperature, enhanced vegetation index (EVI), and land surface temperature (LST). Much of the suitable environments were located throughout the Gulf Coast Plain, Texas Backland Prairies, East Central Texas Plains, Edwards Plateau, Cross Timbers, Mississippi Alluvial Plain, and Central Great Plains. These findings may provide additional guidance to narrow potential risk areas to efficiently communicate messages to metalworkers and potentially identify individuals who may benefit from the anthrax vaccine.

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.