Preventive veterinary medicine最新文献

{"title":"Frequency and risk factors of dogwalk incidents and injuries in agility dogs","authors":"Leena Inkilä,&nbsp;Anna Boström,&nbsp;Heli K. Hyytiäinen","doi":"10.1016/j.prevetmed.2025.106771","DOIUrl":"10.1016/j.prevetmed.2025.106771","url":null,"abstract":"<div><div>Approximately 5–12 % of agility dog injuries occur on the dogwalk, according to survey studies. The rate of falls and injuries related to dogwalk exposure is unknown. Here, a two-part retrospective online survey was conducted to collect data on dogwalk incidents and injuries in 1603 Finnish agility dogs (232 included in both parts) over the six months preceding participation in the study. Data was collected before and after a competition regulation update affecting dogwalk approaches. Risk factors were evaluated with multivariate logistic regression models. Fall(s) from the dogwalk were reported in 15.2 % of responses, close call(s) in 30.1 % and injury secondary to dogwalk incident in 3.7 % during six months. There were estimated 2.6 falls (95 % CI 2.4–2.9) and 0.6 injuries (95 % CI 0.4–0.7) per 1000 dogwalks (n = 1538). Among incidents, 5 % (86/1705) resulted in an injury. Significant risk factors for falls and/or other incidents included higher wither height (OR 1.33–1.74 per 10 cm) and greater exposure to the dogwalk (OR 1.03–1.06 per 10 dogwalks) (n = 452 to n = 1308). Age (OR 0.77–0.87 per year) and dogs’ higher competition level were significant protective factors for falls and/or other incidents (n = 452 to n = 1308). Border Collies (OR 2.73, p = 0.004), taller dogs (OR 1.43 per 10 cm, p = 0.033) and dogs of inexperienced handlers (p = 0.003) had an increased odds of injury (n = 1308). Reduction in the incidence after the regulation update was not detected. The current dogwalk poses a risk to agility dogs’ welfare, requiring further scientific studies to investigate safety improvements.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"248 ","pages":"Article 106771"},"PeriodicalIF":2.4,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145834532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"When beef cattle drink less: Automated water intake monitoring as an early warning for respiratory disease during the adaptation period at the fattening unit","authors":"Luisa Magrin,&nbsp;Simone Dante,&nbsp;Barbara Contiero,&nbsp;Lorenzo Serva,&nbsp;Flaviana Gottardo,&nbsp;Giulio Cozzi","doi":"10.1016/j.prevetmed.2025.106772","DOIUrl":"10.1016/j.prevetmed.2025.106772","url":null,"abstract":"<div><div>Bovine respiratory disease (BRD) remains the leading health and welfare challenge in intensively finished beef cattle. It is the primary cause of antimicrobial treatments and a major source of economic losses due to reduced performance, increased mortality, and high therapeutic costs. Early, non-invasive indicators of BRD are urgently needed to improve its timely detection and mitigate the negative impact on cattle health and farm economics. With a view to precision livestock farming, this study investigated whether the automatic recording of individual drinking behavior and water consumption could provide some useful indicators of early BRD detection during the critical adaptation period of beef cattle at the fattening unit. The study involved 92 Limousine cattle (64 bulls, 28 heifers) from six different batches imported from France between May 2021 and December 2022. An innovative electronic drinking station equipped with radio-frequency identification and flow sensors automatically recorded individual drinking events, water intake, and time spent drinking during the 4 weeks of adaptation at the fattening farm. During the same time period, individual cattle daily health checks were performed by the farm veterinarian, recording all therapeutic treatments for BRD. Forty-five of the 92 animals (49 %) received at least one treatment for BRD during the 4-week adaptation period. In most cases, the first treatment was administered within the first two weeks of arrival (11.2 ± 6.9 days). Animals treated two or more times for BRD exhibited persistently lower daily water intake compared with untreated animals (20.9 vs. 27.3 L/day, respectively), particularly during the first two weeks after arrival. Two days before treatment, affected animals showed a significant reduction in daily water intake compared with healthy ones, whereas daily drinking time and number of visits to the drinker remained unchanged. Risk analysis revealed that cattle with individual water intake below 20.8 L/day increased by over fourfold the odds ratio of developing BRD. Additionally, groups of beef cattle arriving during autumn–winter exhibited a higher BRD occurrence than those arriving in late spring or early summer. These outcomes encourage the use of automatic devices to monitor the individual drinking behaviour during the adaptation period, as they could help identify conditions in which animals may be at higher risk of developing respiratory diseases.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"247 ","pages":"Article 106772"},"PeriodicalIF":2.4,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145804784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an Infectious Disease Vulnerability Index (IDVI) for dairy farms: A data-driven approach to assessing risk and informing biosecurity practices","authors":"Johnbosco U. Osuagwu ,&nbsp;Julia M. Smith ,&nbsp;Scott C. Merrill","doi":"10.1016/j.prevetmed.2025.106770","DOIUrl":"10.1016/j.prevetmed.2025.106770","url":null,"abstract":"<div><div>Dairy farms are vulnerable to a wide range of infectious diseases, which can have significant economic and public health consequences. However, there remains a lack of a robust, farm-level tool that assesses their disease vulnerability. The primary objective of this study was to develop and validate the Infectious Disease Vulnerability Index (IDVI) as a tool for assessing dairy farm vulnerability to disease, aimed at enhancing biosecurity strategies and prioritizing high-risk farms for targeted interventions. Survey data on biosecurity practices, farm management, and animal movement were analyzed using K-Prototypes clustering, dimensionality reduction, optimal cluster determination, stability assessment, and validation. The clustering analysis revealed three distinct farm clusters, characterized by low, medium, and high disease vulnerability index categories. Cluster quality was assessed using silhouette scores (mean = 0.69) and Davies-Bouldin Index (mean = 0.44), with bootstrap resampling (200 iterations) confirming stability, and Friedman’s Test showing statistically distinct risk clusters. Following permutation testing, the factors with the most impact on the infectious disease vulnerability clusters included specific farm characteristics such as organic status and the total number of dairy animals, animal movement practices including frequency of bull calf movements and the average number of heifers leaving the farm during a shipment, farm contacts including hunters and dead animal haulers, and farm biosecurity practices including farm equipment transport practices, engaging in dairy animal exhibitions, and not having quarantine facilities with water, feed, and air separated from other farm animals. The IDVI offers a promising measure of comparing disease risk profiles, validated through bootstrapped silhouette scoring, statistical analysis, and permutation importance analysis. By leveraging the IDVI, dairy farmers, veterinarians, and animal health authorities can identify high-risk farms, implement targeted interventions to improve biosecurity, reduce disease transmission, and consequently enhance their outbreak preparedness.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"247 ","pages":"Article 106770"},"PeriodicalIF":2.4,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-based detection of subclinical and clinical ketosis in Holstein cows using sensor data during the transition period","authors":"Eunjeong Jeon ,&nbsp;Jongkyoo Kim ,&nbsp;Mooyoung Jung ,&nbsp;Jihwan Lee ,&nbsp;Donghyeon Kim ,&nbsp;Seungmin Ha","doi":"10.1016/j.prevetmed.2025.106769","DOIUrl":"10.1016/j.prevetmed.2025.106769","url":null,"abstract":"<div><div>Ketosis, a metabolic disorder in dairy cows, poses a risk of substantial economic losses, particularly when it progresses to clinical forms. Previous prediction models relied on smart farming data and binary classification, without incorporating risk factors such as calf birth weight. Therefore, we aimed to develop a multiclass classification model to differentiate non- (NK), subclinical (SCK), and clinical (CK) ketosis in Holstein cows by integrating behavioral indicators, cow-specific traits, and environmental variables. We hypothesized that integrating these diverse data sources would improve the ability of the model to accurately classify ketosis severity during the transition period. A total of 132 Holsteins were monitored for 21 d after calving using automatic monitoring (HR-TAG). Input features included activity, rumination time, calving age, calf birth weight, and calving season. Blood β-hydroxybutyrate concentrations were measured at eight time points, and cows were classified into NK (&lt;1.2 mmol/L), SCK (1.2–2.9 mmol/L), or CK (≥3.0 mmol/L) groups based on the highest BHBA value recorded across the sampling period. Five machine-learning algorithms—K-nearest neighbors, decision tree, random forest, support vector machine, and extreme gradient boosting (XGBoost)—were trained on 70 % of the dataset and optimized using 10-fold cross-validation, and final model performance was evaluated on the remaining 30 % test set. XGBoost performed best, achieving an accuracy, sensitivity, specificity, F-measure, kappa, and an area under the curve of 0.959, 0.935, 0.966, 0.951, 0.918, and 0.950, respectively. Feature importance analysis identified calving age, calf birth weight, and calving season as key predictors for ketosis severity. These results demonstrate that sensor-based behavioral traits, together with cow-specific characteristics and environmental factors, enable accurate classification of ketosis severity and support the application of precision dairy technologies for early detection and tailored herd management.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"248 ","pages":"Article 106769"},"PeriodicalIF":2.4,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145799683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Behavioural drivers of on-farm biosecurity implementation in livestock: A literature overview with insights for research","authors":"Mehmet Murat Dogusan ,&nbsp;Helena C. De Carvalho Ferreira ,&nbsp;Sebastián Jesús Moya Durán ,&nbsp;Lidiia Moskalenko ,&nbsp;Marnie Louise Brennan ,&nbsp;Daniele De Meneghi ,&nbsp;Maria Rodrigues Da Costa ,&nbsp;Giovanna Ciaravino ,&nbsp;Rui Gaspar","doi":"10.1016/j.prevetmed.2025.106768","DOIUrl":"10.1016/j.prevetmed.2025.106768","url":null,"abstract":"<div><div>Global livestock intensification heightens disease risks, making effective biosecurity crucial. However, the inconsistent adoption of biosecurity measures and the behavioural drivers behind this variability are not fully understood. This review assessed the current state of knowledge and identified evidence gaps regarding drivers influencing stakeholders’ decision-making and the implementation of biosecurity practices, to clarify why well-established measures are not consistently applied and to guide research addressing the factors shaping biosecurity implementation.</div><div>Following PRISMA 2020 guidelines, a systematic search up to October 2023 was conducted across PubMed, Web of Science, and Scopus. Using a literature overview methodology, we retrieved relevant review articles on biosecurity decision-making (first phase), from which we identified relevant original research cited within them (second phase). Thematic analysis used the Capability, Opportunity and Motivation Behaviour (COM-B) model, with the Theoretical Domains Framework (TDF) guiding the coding procedure.</div><div>Of 811 reviews initially retrieved, 37 were included. From these, 205 original research articles were identified, of which 78 were included. Most original studies originated from Europe and Central Asia (n = 38), highlighting geographical biases. Research mainly targeted farmers (n = 78), with few studies targeting veterinarians (n = 6). While 45 articles addressed all three COM-B components, beyond half (n = 46) reported four or fewer TDF domains, suggesting important knowledge gaps in the literature.</div><div>Future studies should target understudied regions, TDF domains (e.g. Skills, Goals and Reinforcement) and stakeholders (e.g. farmers) to effectively implement biosecurity measures. This will help the livestock sector adopt evidence-based biosecurity and adhering to it, improving animal health and resilience worldwide.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"248 ","pages":"Article 106768"},"PeriodicalIF":2.4,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145878950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of stability and triangulation-based methods to improve identification of risk factors for lameness in ewes","authors":"Naomi S. Prosser ,&nbsp;Laura E. Green ,&nbsp;Martin J. Green","doi":"10.1016/j.prevetmed.2025.106767","DOIUrl":"10.1016/j.prevetmed.2025.106767","url":null,"abstract":"<div><div>Lameness has serious impact on sheep health and profitability. In the UK, the largest-scale questionnaire investigating risk factors for lameness (107 questions and 1260 respondents) identified 20 significant variables using stepwise Poisson regression. It is now known that stepwise procedures with wide data can result in overfit models. This research reanalysed these data, using methods that minimise the likelihood of overfitting and therefore reduce the probability of identifying false positive variables. Poisson and log-normal regression models were built with six different variable selection methods, stability selection and triangulation. Six variables were selected in the final triangulated models associated with a reduced prevalence of lameness, fewer than the 20 variables selected in the original analysis. These six variables covered early treatment of individual sheep, treating sheep with any severity of lameness, avoiding routine foot trimming and avoiding footbathing to treat underrunning footrot. Early treatment of individual lame sheep had the highest population attributable fraction for reduction of lameness. Our results highlight the importance of addressing overfitting when fitting models to wide data and the usefulness of triangulating results across different model types. The results strengthen the evidence that the greatest reduction in lameness nationwide would be achieved if farmers treated the first lame sheep in a group rather than waiting until more become lame.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"247 ","pages":"Article 106767"},"PeriodicalIF":2.4,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145768790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Building an institutionalised in-service field epidemiology capacity-building program: Experiences and lessons learned from the China Field Epidemiology Training Program for Veterinarians (CFETPV)","authors":"Honglin Yang ,&nbsp;Quangang Xu ,&nbsp;Chaojian Shen ,&nbsp;Xinjie Wei ,&nbsp;Fusheng Guo ,&nbsp;Julian A. Drewe ,&nbsp;Javier Guitian ,&nbsp;Kachen Wongsathapornchai ,&nbsp;John Edwards ,&nbsp;Dirk Pfeiffer ,&nbsp;Youming Wang ,&nbsp;Hao Tang","doi":"10.1016/j.prevetmed.2025.106766","DOIUrl":"10.1016/j.prevetmed.2025.106766","url":null,"abstract":"<div><div>The increasing threats of zoonotic and transboundary animal diseases highlight the urgent need for a skilled veterinary epidemiology workforce. Before 2010, China had limited capacity in this field. To address this gap, the China Field Epidemiology Training Program for Veterinarians (CFETPV) was established as a competency-based, in-service training program. This study assesses the contributions of CFETPV in enhancing epidemiology practice within animal health services, supporting alumni professional development, and enabling institutional integration in the government system.</div><div>A quantitative study design was employed, drawing on two alumni surveys conducted in 2019 and 2024, alongside routine program monitoring, administrative data and program progress briefs. Surveys assessed alumni’s application of epidemiological competencies in field study, teaching and policy engagement. Descriptive analyses summarised alumni profiles and contributions.</div><div>Since 2010, CFETPV has trained 265 professionals through its introductory course and graduated 153 from the two-year program across 31 provinces. Trainees completed 305 field practices during the training. After graduation, alumni conducted 730 epidemiological investigations and studies, contributed to 297 risk assessments, supported major disease control efforts and informed 98 national and provincial guidelines. In 2019, CFETPV became fully funded by the Chinese government, achieving full integration into the national veterinary service.</div><div>The successful integration was supported by an adaptive competency framework aligned with national priorities, strong alumni support, robust local trainer and mentor networks and consistent stakeholder engagement. These experiences offer insights for countries developing competency-based, in-service veterinary epidemiology training embedded within public veterinary services to strengthen animal health systems and One Health capacity.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"247 ","pages":"Article 106766"},"PeriodicalIF":2.4,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145768797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biosecurity practices useful for porcine reproductive and respiratory syndrome control and eradication on commercial swine farms using machine learning models","authors":"Shoki Akiyama ,&nbsp;Yosuke Sasaki","doi":"10.1016/j.prevetmed.2025.106764","DOIUrl":"10.1016/j.prevetmed.2025.106764","url":null,"abstract":"<div><div>It is well known that porcine reproductive and respiratory syndrome (PRRS) decreases herd productivity and leads to economic loss, and it is believed that biosecurity practices are effective for the control and eradication of PRRS. This study aimed to prioritize biosecurity practices useful for PRRS control and eradication by using a machine learning algorithm. Biosecurity practices on 258 Japanese breeding farms were assessed using a biosecurity assessment tool. Random forest analysis was used to assess relevant features based on feature importance. In study 1, each farm was divided into two groups (PRRS controlled or not controlled), and the most relevant biosecurity practices for PRRS control were investigated. Seven features were selected as associated with PRRS control, and results identified the prioritization of semen management and the maintenance of a controlled barn environment to be critical elements for PRRS control. In study 2, each farm was divided into two groups (PRRS-free or not free of PRRS), and the most relevant biosecurity practices for PRRS eradication were investigated. Fourteen features were identified as critically associated with PRRS eradication, and results showed that the stringent management of replacement gilts, the exclusive use of semen from PRRS-free sources, and a comprehensive awareness of farm location were essential elements for PRRS eradication. In conclusion, this research underscores the significant divergence in biosecurity strategies required for effective PRRS control compared with those for eradication.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"247 ","pages":"Article 106764"},"PeriodicalIF":2.4,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145747117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing U.S. swine farm preparedness for infectious foreign animal diseases with rapid access to biosecurity information","authors":"Christian Fleming ,&nbsp;Kelsey Mills ,&nbsp;Nicolas C. Cardenas ,&nbsp;Jason A. Galvis ,&nbsp;Cesar Corzo ,&nbsp;Denílson dos Santos Ebling ,&nbsp;Gustavo Machado","doi":"10.1016/j.prevetmed.2025.106765","DOIUrl":"10.1016/j.prevetmed.2025.106765","url":null,"abstract":"<div><div>The U.S. Secure Pork Supply (SPS) Plan is a voluntary program that establishes biosecurity standards to maintain business continuity. The role of biosecurity in disease spread is well recognized, yet the U.S. swine industry lacks knowledge of individual farm biosecurity and the efficacy of existing measures.</div><div>Here, we (i) described a consortium among the swine industry, government, and academia that formed the Rapid Access Biosecurity application (RABapp™), (ii) summarized the farm characteristics and biosecurity of premises in RABapp™, (iii) mapped RABapp™’s biosecurity coverage of the U.S. swine population, and (iv) evaluated associations between biosecurity measures and reports of porcine reproductive and respiratory syndrome virus (PRRSV) and porcine epidemic diarrhea virus (PEDV) using multivariable logistic regression.</div><div>RABapp™, used in 31 states, represented 42% of the U.S. commercial swine population. In total, 76% (234/307) of Agricultural Statistics Districts were identified as biosecurity deserts, with less than half of their swine population represented in RABapp™. Requiring footwear or clothing changes, multiple carcass disposal locations, greater distance from neighboring swine premises, using bait for rodent control, and carcass burial significantly reduced the odds of PRRSV/PEDV occurrence. Conversely, rendering carcasses, deep pit or tank manure storage, and land application of manure were associated with increased odds of infection.</div><div>This study demonstrated the national importance of RABapp™ as a centralized repository and mapped SPS plan adoption. Curtailing high-risk practices and reinforcing the identified measures could help reduce the circulation of endemic disease and strengthen industry preparedness for future foreign animal disease emergencies.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"248 ","pages":"Article 106765"},"PeriodicalIF":2.4,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145966727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic modelling of burden of livestock diseases on domestic ruminants in Ethiopia","authors":"Wudu T. Jemberu ,&nbsp;Gemma Chaters ,&nbsp;Theodore J.D. Knight-Jones ,&nbsp;William Gilbert ,&nbsp;Stephen Kwok ,&nbsp;Mieghan Bruce ,&nbsp;Benjamin Huntington ,&nbsp;Jonathan Rushton","doi":"10.1016/j.prevetmed.2025.106761","DOIUrl":"10.1016/j.prevetmed.2025.106761","url":null,"abstract":"<div><div>This study, carried out in 2022–2023, quantified the financial burden of disease in cattle, sheep and goats in Ethiopia for the year 2021 using the animal health loss envelope (AHLE) metric. The AHLE measures all cause disease burden, avoidable and non-avoidable, as the difference in the financial performance of a livestock production system (e.g., gross margin) comparing a scenario where animals are in an ideal state of health to the current situation. A stochastic dynamic population model (DPM) was employed to calculate the gross margin for an average farm and for the national herd under these current and ideal health scenarios. Data for parametrizing the DPM were derived from secondary sources and expert elicitation. The stochastic DPM was simulated for 10,000 iterations and results are reported as means with 95 % percentile intervals (PI)<strong>.</strong> The annual AHLE per average farm was estimated at USD 1209 (95 %PI:392–2470) in cattle, USD 158 (95 %PI:66–292) in sheep and USD 416 (95 %PI:136–847) in goats. At national level, the annual AHLE in ruminants was USD 18.39 billion with USD 15.42 billion (95 % PI:12.70–18.57) in cattle, USD 1.04 billion (95 % PI:0.84–1.30) in sheep, and USD 1.93 billion (95 % PI:1.64–2.25) in goats. Morbidity losses constituted the largest component of the AHLE, exceeding 50 % across all species, while animal health expenditure represented the smallest component, accounting for less than 2 % of AHLE in all species. This high disease burden, with minimal contribution from animal health expenditure, indicates significant opportunity for improvement through investment in animal health.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"247 ","pages":"Article 106761"},"PeriodicalIF":2.4,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145757477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}