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

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 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.

Artificial Intelligence Models for Zoonotic Pathogens: A Survey

Zoonotic diseases or zoonoses are infections due to the natural transmission of pathogens between species (animals and humans). More than 70% of emerging infectious diseases are attributed to animal origin. Artificial Intelligence (AI) models have been used for studying zoonotic pathogens and the factors that contribute to their spread. The aim of this literature survey is to synthesize and analyze machine learning, and deep learning approaches applied to study zoonotic diseases to understand predictive models to help researchers identify the risk factors, and develop mitigation strategies. Based on our survey findings, machine learning and deep learning are commonly used for the prediction of both foodborne and zoonotic pathogens as well as the factors associated with the presence of the pathogens.

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.

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.

First PCR Confirmed anthrax outbreaks in Ethiopia—Amhara region, 2018–2019

Background

Anthrax is a disease that affects humans and animals. In Ethiopia, anthrax is a reportable disease and assumed to be endemic, although laboratory confirmation has not been routinely performed until recently. We describe the findings from the investigation of two outbreaks in Amhara region.

Methods

Following reports of suspected outbreaks in Wag Hamra zone (Outbreak 1) and South Gondar zone (Outbreak 2), multi-sectoral teams involving both animal and public health officials were deployed to investigate and establish control programs. A suspect case was defined as: sudden death with rapid bloating or bleeding from orifice(s) with unclotted blood (animals); and signs compatible with cutaneous, ingestion, or inhalation anthrax ≤7 days after exposure to a suspect animal (humans). Suspect human cases were interviewed using a standard questionnaire. Samples were collected from humans with suspected anthrax (Outbreak 1 and Outbreak 2) as well as dried meat of suspect animal cases (Outbreak 2). A case was confirmed if a positive test was returned using real-time polymerase chain reaction (qPCR).

Results

In Outbreak 1, a total of 49 cows died due to suspected anthrax and 22 humans developed symptoms consistent with cutaneous anthrax (40% attack rate), two of whom died due to suspected ingestion anthrax. Three people were confirmed to have anthrax by qPCR. In Outbreak 2, anthrax was suspected to have caused the deaths of two livestock animals and one human. Subsequent investigation revealed 18 suspected cases of cutaneous anthrax in humans (27% attack rate). None of the 12 human samples collected tested positive, however, a swab taken from the dried meat of one animal case (goat) was positive by qPCR.

Conclusion

We report the first qPCR-confirmed outbreaks of anthrax in Ethiopia. Both outbreaks were controlled through active case finding, carcass management, ring vaccination of livestock, training of health professionals and outreach with livestock owners. Human and animal health authorities should work together using a One Health approach to improve case reporting and vaccine coverage.

Unpacking the myth between increased government initiatives and reduced selling of dead live stocks in China: An approach towards exploring hidden danger of zoonotic diseases

Prohibiting the unsafe sale of livestock that have died in production and harmlessly disposing of them are key measures to control and prevent outbreaks of zoonotic diseases and exert a great significance for maintaining meat-derived food and public health safety. However, under the strict implementation of governmental initiatives, some farmers still choose to sell dead livestock unsafely in developing countries such as China, Brazil, Mexico, and Kenya, which have become an important hidden danger in preventing and controlling zoonotic diseases. Based on data from 496 pig farmers in Hebei, Henan, and Hubei, China, the Double Hurdle Model was employed to explore the impact of governmental initiatives on the willingness and proportion of dead pigs sold unsafely by farmers. Besides, based on the heterogeneity of organization participation and breeding scale, the impact of governmental initiatives on different scale farmers' unsafely selling behaviors is also discussed. The results showed that the harmless disposal subsidy significantly reduces farmers' willingness to unsafely sell dead pigs (SW, RC = −0.0666, and SE = 0.0261). Still, the impact on the proportion is weak (SP, RC = −0.0502, and SE = 0.0474). Though the effect of supervision punishment is greatly weakened (SW, RC =−0.0381, and SE = 0.0324; SP, RC = −0.0204 and SE = 0.0263), it can significantly enhance the effect of harmless disposal subsidy by creating a good law-abiding environment (SW, RC = −0.1370, and SE = 0.0374; SP, RC = −0.0820, and SE = 0.0431). Governmental initiatives have an undue impact on the unsafe sale of dead livestock by farmers participating in cooperatives. The effects of these measures on different scale farmers' unsafe sale of dead pigs are highly heterogeneous. In addition, the study also found that food and public health safety risk perceptions are important endogenous drivers for curbing farmers selling dead pigs. This research can also provide important inspiration for other countries. The government should raise farmers' risk perception level of food and public safety, optimize governmental initiatives, play the key role of cooperative organization, increase the proportion of dead pigs harmlessly disposed of, and finally eliminate new hidden dangers in the prevention and control of zoonotic diseases.

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

Background and Aim:

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

Materials and Methods:

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

Results:

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

Conclusion:

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

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

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