Roll-Back Eradication of Bovine Tuberculosis (TB) From Wildlife in New Zealand: Concepts, Evolving Approaches, and Progress

Tuberculosis in wild animals in India

India is renowned for its complex megadiverse ecosystems and abundant biodiversity. Bovine tuberculosis (bTB) often remains synonymous with Mycobacterium bovis infection in cattle. The domain of tuberculosis (TB) among wild animals, induced by members of the Mycobacterium tuberculosis complex organisms (MTBC), is often underexplored and underreported in India. Within this context, instances of wild animal tuberculosis (wTB) have manifested across both captive and free-roaming animals. The sources contributing to wTB in animals can be human, animal, or environmental factors, thus illuminating the complex transmission pathways. The diagnosis of wTB continues to pose a formidable challenge, a consequence of the expansive taxonomic diversity in both the host and the pathogen. Complications inherent in acquiring samples from wildlife, the absence of standardized diagnostic protocols, limited insights into infection prevalence, and resource constraints compound diagnosis. Amidst these, adopting the comprehensive One Health paradigm surfaces as an imperative, accentuating the interconnectedness bridging human, animal, and environmental health. Recognizing key stakeholders and fostering intersectoral collaboration to provide enhanced diagnostic techniques driven by skilled personnel and advanced infrastructure play pivotal roles in a comprehensive strategy. Additionally, leveraging vaccination efforts contributes to effective control. A national wTB surveillance program is a cornerstone, ensuring an integrated and holistic approach to disease management. Through this review, we delve into the current landscape of wTB in India, unveiling its multifaceted challenges, and further explore the multifarious strategies that the One Health approach proffers in this dynamic endeavor.

Are predictions of bovine tuberculosis-infected herds unbiased and precise?

Bovine tuberculosis (bTB) is prevalent among livestock and wildlife in many countries including New Zealand (NZ), a country which aims to eradicate bTB by 2055. This study evaluates predictions related to the numbers of livestock herds with bTB in NZ from 2012 to 2021 inclusive using both statistical and mechanistic (causal) modelling. Additionally, this study made predictions for the numbers of infected herds between 2022 and 2059. This study introduces a new graphical method representing the causal criteria of strength of association, such as R2, and the consistency of predictions, such as mean squared error. Mechanistic modelling predictions were, on average, more frequently (3 of 4) unbiased than statistical modelling predictions (1 of 4). Additionally, power model predictions were, on average, more frequently (3 of 4) unbiased than exponential model predictions (1 of 4). The mechanistic power model, along with annual updating, had the highest R2 and the lowest mean squared error of predictions. It also exhibited the closest approximation to unbiased predictions. Notably, significantly biased predictions were all underestimates. Based on the mechanistic power model, the biological eradication of bTB from New Zealand is predicted to occur after 2055. Disease eradication planning will benefit from annual updating of future predictions.

Bovine tuberculosis control in Fiji: Retrospective study findings for 2015 to 2020

Control of bovine tuberculosis (bTB) is a priority for animal health, biosecurity, and human health authorities in Fiji as evident from the long-term funding of the Bovine Brucellosis and Tuberculosis Eradication and Control program (BTEC) and notable improvements to the program described in this paper. To evaluate the performance of the Fiji BTEC program from 2015 to 2020, all available bTB data for cattle were analyzed. Data sources included BTEC bTB testing records, abattoir records and laboratory records. We integrated all information to quantify the bTB tests applied, bTB positive farms and animals, meat inspection and laboratory findings. Test coverage was highest among dairy cattle in Central Division (~73%), where bTB was highly prevalent with 7.8% of dairy cattle and 61.7% of dairy farms found to be positive between 2015 and 2020. There was no visible downward trend in the apparent prevalence of bTB over the 6-year period. During 2019 and 2020, only 21.3% (51/239) of the tested dairy farms maintained their clear status, another 8.4% (20/239) reverted to infected status after 1 year or more of being bTB clear, and most farms remained infected during these 2 years. Factors observed to be contributing to this situation were persistent infections, related in part to the significant number of untested animals, uncontrolled animal movements, and larger farm size. Similar to other developing countries, bTB remains a serious concern and further strengthening of the program targeting the main contributors to bTB persistence, along with maintenance of a comprehensive reporting and traceability system, industry awareness and government support are needed. Control of bTB in Fiji is a long-term objective that must have multiple stakeholder engagement and regular review to measure success.

Confirming the broadscale eradication success of nutria (Myocastor coypus) from the Delmarva Peninsula, USA

Nutria (Myocastor coypus) were introduced to the eastern shore of Chesapeake Bay, USA in the 1940s. They reached peak densities in the late 1990s, causing massive wetland loss. Beginning in 2002, a systematic plan to eradicate nutria from the 1.7M ha Delmarva Peninsula was implemented. Since that time the nutria population has been effectively reduced, and no nutria have been detected since May 2015. A lack of detection does not equate with complete absence. We address the following three questions. (1) What is the expected probability of nutria eradication from the Delmarva Peninsula as of the end of 2020? (2) If the probability of eradication is below the management target of 0.95, how much more surveillance is required? (3) How sensitive is the estimated probability of eradication to varying levels of public surveillance and modelled population growth rates? These questions were addressed by employing a stochastic spatially-explicit surveillance model that uses data in which no nutria were detected to quantify the probability of complete absence (PoA) over the entire Delmarva Peninsula. We applied an analytical framework that decomposes the spatial risk of survivors and data into management zones, and took advantage of low-cost public reporting of nutria sightings. Active surveillance by the eradication program included detector dog and tracker surveys, shoreline surveys, detection with ground and water platforms (with hair snares), and camera traps. Results showed that the PoA increased with time and surveillance from a beginning PoA in May 2015 of  0.01 to a mean of 0.75 at the end of 2020. This indicates that the PoA on the Delmarva was well below the target threshold of 0.95 for declaring eradication success. However, given continued surveillance without detection, a PoA of 0.95 would be achieved by June 2022. This analysis provides an objective mechanism to align the expectations of policy makers, managers and the public on when eradication of nutria from the entire Delmarva Peninsula should be declared successful.

Using a Modeling Approach to Inform Progress Towards Stoat Eradication From the Orkney Islands

Invasive non-native species eradication attempts are typically large and expensive projects that benefit from the support of quantitative tools, such as population models, to be completed within the scheduled and funded time. Managed ecosystems are constantly changing due to population and ecosystem dynamics. Accordingly, any model predictions need to be updated, using different sources of data, to inform the project about the progress toward eradication. The stoat Mustela erminea was introduced to the hitherto predatory land mammal free Orkney archipelago around 2010. In 2016, a project aiming to eradicate stoats to preserve ecologically and economically important native wildlife was designed and implemented. It entailed a “knockdown” phase followed by a “mopping-up” phase to remove stoats that escaped capture. We used data from this project to iteratively predict the progress toward eradication. We applied spatially explicit individual-based models to estimate the proportion of stoats being exposed to capture, and then compared these simulation-based predictions with removal data, allowing us to estimate changes in the population size through time. We also used sighting data from members of the public to refine eradication probability. We were also able to demonstrate how the initially wide uncertainty gradually diminished as more evidence accumulated. The information derived from different types of data and quantitative models allowed us to track the effectiveness of current trapping approaches and to help to inform project managers about when the project achieved the knockdown phase milestone. Our analyses confirmed that the expected magnitude of the initial knockdown phase has been achieved in some areas, but also revealed spatial and temporal heterogeneity in the distribution of captures, most likely caused by the sequential trapping and stoat movement and trap shy stoats exposed to capture but not caught. This heterogeneity calls for additional data sources (e.g., from camera traps or detection dogs) to estimate the proportion of trap-shy individuals and the size of the untrapped population, and ultimately the feasibility of eradication.