Preventive veterinary medicine最新文献

{"title":"Economic viability of different surveillance strategies for the control of paratuberculosis in Swiss dairy cattle","authors":"Silja Griss ,&nbsp;Gertraud Schüpbach-Regula ,&nbsp;Luís P. Carmo ,&nbsp;Mireille Meylan ,&nbsp;Beat Thomann","doi":"10.1016/j.prevetmed.2025.106685","DOIUrl":"10.1016/j.prevetmed.2025.106685","url":null,"abstract":"<div><div>Paratuberculosis (PTB), or Johne's disease, is a globally prevalent disease caused by <em>Mycobacterium avium</em> subsp. <em>paratuberculosis</em>, leading to significant economic losses in the dairy industry. This study assessed the economic viability of potential PTB surveillance strategies in Switzerland using stochastic simulation models.Two non-targeted surveillance strategies (SS1 and SS2) were assessed under three participation scenarios over ten years. Additionally, a more targeted surveillance strategy (SS3) was evaluated, focusing on historically positive herds.In SS1, herds are screened using sock swab PCR followed by individual faecal PCR testing in sock swab-positive herds. SS2 follows a risk-based approach: in high-risk herds (i.e., previous PTB cases or animals with suggestive symptoms), all cows older than 24 months are tested using serum ELISA, with faecal PCR confirmation. In other herds, only high-risk cows (somatic cell count &gt;200,000/ml or &gt;3 lactation) undergo ELISA testing to determine herd status.In SS3, only animals from herds with recent outbreaks or clinical cases are tested.Neither of the two non-targeted strategies (SS1 and SS2) proves economically beneficial over a ten-year period, with Benefit-Cost Ratios (BCR) below 0.1. In contrast, the targeted strategy (SS3) achieves a BCR of 1.42, a net present value of CHF 568,545, and reaches the break-even point after seven years.These results indicate that targeted control strategies are more economically viable in low-prevalence settings.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"245 ","pages":"Article 106685"},"PeriodicalIF":2.4,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019831","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":"Assessment of seasonality in antimicrobial susceptibility testing and resistance of urinary Escherichia coli from dogs and cats in the United States (2019 – 2022)","authors":"Rasaq A. Ojasanya ,&nbsp;J. Scott Weese ,&nbsp;Kurtis E. Sobkowich ,&nbsp;Anne Deckert ,&nbsp;Donald Szlosek ,&nbsp;Andy Plum ,&nbsp;Theresa M. Bernardo ,&nbsp;Zvonimir Poljak","doi":"10.1016/j.prevetmed.2025.106684","DOIUrl":"10.1016/j.prevetmed.2025.106684","url":null,"abstract":"<div><div>Antimicrobial resistance (AMR) poses a significant global health challenge, impacting humans, animals, and the environment. Dogs and cats are vulnerable to urinary tract infections (UTIs), mostly caused by antimicrobial-resistant <em>Escherichia coli</em>, necessitating antimicrobial susceptibility testing (AST) for optimal treatment. This study investigated and evaluated the seasonality of AST and AMR in urinary <em>E. coli</em> isolates from dogs and cats in the USA and evaluated the potential influence of climatic zones on these patterns. Retrospective data from IDEXX Laboratories, from January 2019 to December 2022, were analyzed. The dataset included 344,862 urinary <em>E. coli</em> isolates (74.2 % from dogs, 25.8 % from cats) tested against seven antimicrobials. Linear regression and negative binomial regression models assessed seasonality and trends, accounting for climatic zone variability. An increasing trend in AST was observed, with a seasonal peak in the summer for both species. Urinary <em>E. coli</em> isolates from dogs and cats had the highest resistance to amoxicillin at 27.9 % (95 % CI: 27.7–28.1) and 28.4 % (95 % CI: 28.1–28.7), respectively, among all antimicrobials tested. Resistance rates significantly declined (<em>p</em> &lt; .01) for all drugs tested in dogs, while in cats, declines were significant only for cefovecin, marbofloxacin, and enrofloxacin. No seasonality in AMR was found at the national level or across climatic zones, though AMR rates varied significantly by climatic zone (<em>p</em> &lt; .01). The hot-humid zone had the highest resistance rates but the lowest AST rates per one million dogs and cats. Seasonality in AST suggests a seasonal pattern for UTIs; however, no seasonal pattern in AMR could be observed nationally or regionally for urinary <em>E. coli</em> isolates.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"245 ","pages":"Article 106684"},"PeriodicalIF":2.4,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019830","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":"Application of computer vision for automated detection of different lesions in pig lungs: An exploratory study","authors":"Matteo Recchia ,&nbsp;Lucia Scuri ,&nbsp;Camilla Allegri ,&nbsp;Claudia Romeo ,&nbsp;Federico Scali ,&nbsp;Antonio Marco Maisano ,&nbsp;Giovanni Santucci ,&nbsp;Giorgio Bontempi ,&nbsp;Simone Canesi ,&nbsp;Laura Sala ,&nbsp;Camilla Recordati ,&nbsp;Eugenio Scanziani ,&nbsp;Sara Panseri ,&nbsp;Sergio Ghidini ,&nbsp;Emanuela Zanardi ,&nbsp;Adriana Ianieri ,&nbsp;Lis Alban ,&nbsp;Giovanni Loris Alborali","doi":"10.1016/j.prevetmed.2025.106672","DOIUrl":"10.1016/j.prevetmed.2025.106672","url":null,"abstract":"<div><div>Accurate classification of lung lesions at necropsy is crucial for guiding the diagnostic process and ensuring effective management of porcine respiratory diseases. <em>Post-mortem</em> inspection of the lungs during slaughter also provides valuable insights into disease occurrence, offering useful feedback on the efficacy of on-farm prevention and control strategies. However, manual assessment protocols may be impaired by high slaughtering speeds and low inter-rater agreement, which limits continuous data collection and hinders comparability. Artificial intelligence, particularly computer vision (CV), may offer a promising alternative. This study aimed to train and test a commercial CV model for segmenting both anatomical structures and lesions in pig lungs. Overall, 1742 lungs were collected at slaughter, examined macroscopically, and photographed laterally. Two veterinarians with expertise in swine pathology manually annotated the acquired images to outline anatomical (i.e., lung, heart, lung lobes), pathological (i.e., bronchopneumonia, fibrinous pleuropneumonia, chronic pleuritis), and artefactual (i.e., parenchymal laceration, bronchoinhalation of blood) classes, forming the reference dataset for model training and testing. Model performance in segmenting these classes varied by confidence threshold, with sensitivity (36–84 %), positive predictive value (62–93 %) and F1 score (52–78 %) indicating imperfect yet improvable performance. Overall, anatomical structure segmentation outperformed lesion detection, likely due to class imbalance in the training dataset and the complexity of pulmonary pathology. Integrating standardized and real-time detection of lung lesions via digital imaging could improve respiratory health surveillance, thereby enhancing the role of abattoirs as strategic epidemiological observatories.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"245 ","pages":"Article 106672"},"PeriodicalIF":2.4,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004730","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":"Artificial intelligence-enhanced walk-over-weighing system for real-time livestock weight monitoring: A novel approach for precision farming","authors":"İsmail Kırbaş","doi":"10.1016/j.prevetmed.2025.106673","DOIUrl":"10.1016/j.prevetmed.2025.106673","url":null,"abstract":"<div><div>Accurate and consistent livestock weight monitoring is a cornerstone of modern precision farming, yet conventional methods remain labor-intensive, induce animal stress, and provide infrequent data. While automated systems have emerged, they often lack the intelligence to translate weight data into actionable health insights. This study introduces and validates a novel Artificial Intelligence (AI)-enhanced Walk-Over-Weighing (WoW) system designed to overcome these limitations through real-time, autonomous monitoring.</div><div>The system integrates a stress-free platform with high-precision load cells, RFID for individual animal identification, and dual ESP32 modules for robust data processing. Its core innovation lies in a dual AI framework: a Random Forest regression model was developed for precise weight prediction under dynamic conditions, while a One-Class Support Vector Machine (SVM) was implemented for unsupervised anomaly detection. The integrated system was validated on a herd of 90 dairy cows (Holstein and Simmental), with its performance evaluated against static reference measurements.</div><div>The results demonstrated exceptional performance. The weight prediction model achieved a coefficient of determination (R²) greater than 0.98 and a Mean Absolute Percentage Error (MAPE) below 0.5 %, signifying high accuracy and reliability even with animal movement. Furthermore, the anomaly detection model proved effective at identifying simulated health events, achieving a classification accuracy of 0.95.</div><div>Crucially, these findings establish that the WoW system transcends simple measurement, functioning as a proactive, non-invasive health monitoring tool. By identifying subtle deviations from expected growth patterns, the platform enables the early detection of potential health issues, thereby enhancing animal welfare, reducing economic losses, and promoting more sustainable, data-driven farming practices.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"245 ","pages":"Article 106673"},"PeriodicalIF":2.4,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081493","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":"Probability of Influenza A virus RNA detection at different pooling levels for commonly used sample types in swine breeding herds","authors":"Daniel Carnevale de Almeida Moraes ,&nbsp;Onyekachukwu Henry Osemeke ,&nbsp;Phillip C. Gauger ,&nbsp;Cesar Amorim Moura ,&nbsp;Giovani Trevisan ,&nbsp;Gustavo S. Silva ,&nbsp;Daniel C.L. Linhares","doi":"10.1016/j.prevetmed.2025.106671","DOIUrl":"10.1016/j.prevetmed.2025.106671","url":null,"abstract":"<div><div>Pooling samples allows for efficient and cost-effective surveillance of endemic pathogens, enabling broader testing coverage and reducing diagnostic costs. Pooling swine samples for influenza A virus surveillance without negatively impacting sensitivity would depend on the sample type, cycle threshold (Ct value), and dilution level. Therefore, this study aimed to compare the probability of IAV reverse transcription real-time polymerase chain reaction (RT-rtPCR) detection at different pooling levels in family oral fluids, udder wipes, and nasal wipes obtained from an endemic swine breeding herd. Forty-five IAV RT-rtPCR-positive samples (15 family oral fluid, 15 udder wipes, and 15 nasal wipes) obtained from an IAV-positive herd were pooled at different levels (undiluted, 1/3, 1/5, and 1/10). For analysis, samples were categorized into three groups based on the undiluted replicates' mean Ct value: Category A - Ct &lt; 30; Category B - Ct between 30 and 34; Category C - Ct between &gt; 34–38. For all sample types, the probability of influenza A virus RNA detection in Ct category A and family oral fluids and udder wipes in Ct category B did not decrease when the dilution level increased to 1/10. In category C of all sample types, the probability of influenza A virus detection decreased as the dilution level increased. These findings suggest that pooling population-based samples can be an effective strategy for swine surveillance, particularly when working with samples with Ct values below 34, and future research in the field is needed to refine recommendations for field implementation.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"245 ","pages":"Article 106671"},"PeriodicalIF":2.4,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989124","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":"Insights into the epidemiological characteristics, temporal changepoints, and space-time clusters of foot and mouth disease outbreaks in the SEACFMD region to support eradication efforts","authors":"Veerasak Punyapornwithaya ,&nbsp;Supitchaya Srisawang ,&nbsp;Chalita Jainonthee ,&nbsp;Wengui Li ,&nbsp;Ronello Abila ,&nbsp;Karma Rinzin ,&nbsp;Ashish Sutar ,&nbsp;Bolortuya Purevsuren","doi":"10.1016/j.prevetmed.2025.106683","DOIUrl":"10.1016/j.prevetmed.2025.106683","url":null,"abstract":"<div><div>Foot and mouth disease (FMD) remains endemic in several countries across Southeast Asia, China, and Mongolia (SEACFMD region), posing an ongoing threat to livestock and trade. This study aimed to investigate the epidemiological characteristics and analyze the spatial and temporal distribution of FMD outbreaks reported across the SEACFMD region. FMD outbreak and virus lineage data from 2015 to 2023 were utilized. Time series decomposition, changepoint detection, and spatio-temporal clustering using space-time permutation and Poisson space-time models were conducted to identify trends, changepoints, and outbreak clusters. Nine countries reported at least one FMD outbreak during the study period. Changepoint analysis revealed significant temporal shifts, including a peak in 2020, followed by a declining trend towards the end of 2023. The O/ME-SA/PanAsia and O/SEA/Mya-98 lineages were dominant between 2015 and 2018, while O/ME-SA/Ind-2001e became predominant from 2019 onwards, particularly in Vietnam and Thailand, and was linked to the incursion of FMD in Indonesia in 2022. Spatio-temporal analyses identified clusters in Mongolia, Thailand, Vietnam, Cambodia, Malaysia, and southern China, with the number and size of clusters influenced by model parameters. The findings highlight the dynamic epidemiology of FMD in the SEACFMD region, characterized by the emergence of dominant lineages, fluctuating outbreak trends, and evidence of transboundary spread. These insights support targeted surveillance, timely response, and strengthened regional collaboration to inform the SEACFMD Roadmap 2026–2030.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"245 ","pages":"Article 106683"},"PeriodicalIF":2.4,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004731","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":"Time to death for on-farm emergency slaughtered cattle in Norway","authors":"Gíslína Skúladóttir ,&nbsp;Ingrid H. Holmøy ,&nbsp;Adam Dunstan Martin","doi":"10.1016/j.prevetmed.2025.106670","DOIUrl":"10.1016/j.prevetmed.2025.106670","url":null,"abstract":"<div><div>Animal welfare and aspects of sustainability are growing concerns in cattle production. In Norway, on-farm emergency slaughter (OFES) accounts for 4.2% of all cattle slaughter. The time animals must wait for killing after veterinary inspection is an important, but unstudied, measure when considering the welfare of animals undergoing OFES. This study investigated 2229 cases of OFES from three regions in Norway. The Norwegian Food Safety Authority gave permission to collect data from physical handwritten OFES certificates collected and stored in each slaughterhouse from four months in 2018. The time from OFES certification to death could be calculated for 2028 cases. Survival analysis was used to investigate the hazard of death from OFES certification. Half of all cases were killed within 2.5<!--> <!-->hours of OFES certification. The condition reported as the reason for OFES significantly affected time from OFES certification to death. Cattle reported to have obstetrical conditions were killed faster than cattle reported to be recumbent (Hazard Ratio 1.74, 95% CI 1.50-2.00). When considering the animal welfare implications of OFES, the length of time an animal is waiting to be killed is critical. The majority (75%) of cases in this study were killed within 4.25<!--> <!-->hours, but the last 5% waited over 20<!--> <!-->hours. This implies that some case selection is employed by personnel involved in the on-farm emergency slaughter process. This study provides information about the time cattle wait for OFES in Norway to allow for evidence-based, rather than anecdotal, discussions about the practice.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"245 ","pages":"Article 106670"},"PeriodicalIF":2.4,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004728","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":"PARAMETRA: A transmission modelling database for livestock diseases","authors":"Alistair Antonopoulos ,&nbsp;Natalia Ciria ,&nbsp;Áine Regan ,&nbsp;Jerrold Tubay ,&nbsp;Giovanna Ciaravino ,&nbsp;Brandon Hayes ,&nbsp;Sébastien Lambert ,&nbsp;Timothée Vergne ,&nbsp;Francisca Velkers ,&nbsp;Evelien Biebaut ,&nbsp;Arvo Viltrop ,&nbsp;Jeroen Dewulf ,&nbsp;Johannes Charlier ,&nbsp;Egil Fischer ,&nbsp;Alberto Allepuz Palau","doi":"10.1016/j.prevetmed.2025.106668","DOIUrl":"10.1016/j.prevetmed.2025.106668","url":null,"abstract":"<div><div>Dynamic modelling of infectious diseases of importance to livestock production is a valuable tool for policy and decision makers. Mathematical and simulation models play an essential role in understanding complex systems, but parameterising these models can be challenging, especially in data-sparse environments. When parameters are unable to be estimated from epidemiological or experimental data, a time-consuming and labour-intensive literature review—to identify suitable literature-informed values—is often necessary. In service of this, here we present PARAMETRA, a parameter database for 20 pathogens of livestock, envisaged as an open-source collaborative tool for the research community to aid in the development of future transmission models of livestock pathogens. Pathogens included in the database so far were selected using a disease prioritisation exercise. Parameters of interest were selected by experts with a strong background in epidemiology and mathematical modelling. We populated the database with over 2000 individual values, covering a wide range of different parameters including transmission rates, diagnostic test efficacies, pathogen survival on surfaces, and the farm and regional level prevalences of selected diseases. Finally, we present an initial illustrative analysis of the database contents and the associated metadata of studies included. One of the principal conclusions we can draw from the data available is that in many cases research is reactive, rather than proactive, with research only tending to focus on specific diseases after outbreaks have already occurred, as is the case for African swine fever for example. This has important implications for future research moving to a more proactive approach for experimental and epidemiological studies based on observations of gaps in the data, and high-risk diseases. This publication represents the first step in development for the PARAMETRA database, which will be updated and expanded in the coming years.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"245 ","pages":"Article 106668"},"PeriodicalIF":2.4,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932835","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":"Modelling spillover risk of highly pathogenic avian influenza from wild birds to poultry in Denmark","authors":"Yangfan Liu ,&nbsp;Lene Jung Kjær ,&nbsp;Anette Ella Boklund ,&nbsp;Michael Ward ,&nbsp;Timme Nyegaard ,&nbsp;Carsten Thure Kirkeby","doi":"10.1016/j.prevetmed.2025.106669","DOIUrl":"10.1016/j.prevetmed.2025.106669","url":null,"abstract":"<div><div>Spillover risks of contagious diseases affecting both wildlife and farm animals are of growing concern. Since late 2020, several waves of highly pathogenic avian influenza virus (HPAIV) clade 2.3.4.4b have been observed in poultry farms in Denmark, impacting the poultry industry. Concurrently, many wild birds have been found infected and dead of this disease. As the epidemic developed, 49 farm outbreaks and over 2000 infected wild birds were detected in Denmark from late 2020–2024. Thus, it is important to investigate the interactions between wild birds and poultry farms and identify the spillover risks of HPAIV from free-living wild birds to domestic poultry. Using a previously developed mechanistic model for HPAIV in Danish wild birds and statistical tests (including correlation tests and logistic regressions), we quantified this spillover risk in Denmark in space and time. The mechanistic model identified a constant hot spot of HPAIV spillover risk in southern Zealand which corresponds to the hot spot previously identified using reported poultry outbreaks. The model estimated farm-specific risks with a precision level of 78 % for the simulated period. The population changes of the barnacle goose (<em>Branta leucopsis</em>) were found to be significantly associated with poultry outbreaks. A 3-week time lag across Denmark between wild bird HPAIV detections and subsequent poultry outbreaks was discovered, together with regional differences of this time lag. Our study showed the relationships between wild bird populations/detections and poultry outbreaks and the simulated weekly risk maps can help decision-making for prevention and surveillance.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"245 ","pages":"Article 106669"},"PeriodicalIF":2.4,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144911675","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":"Network of ship movements and its potential in spreading pathogenic infectious salmon anemia virus among Norwegian fish farms","authors":"Hélène Duault ,&nbsp;Maximilien Bailly ,&nbsp;Mingli Zhao ,&nbsp;Sarah C. Hill ,&nbsp;Guillaume Fournié","doi":"10.1016/j.prevetmed.2025.106667","DOIUrl":"10.1016/j.prevetmed.2025.106667","url":null,"abstract":"<div><div>In Norway, infectious salmon anemia (ISA) is a notifiable and economically important disease. Accurately understanding between-farm transmission remains essential for ISA control and prevention. Using a network approach, our objective was to assess whether ship movements could potentially contribute to the transmission of pathogenic variants of ISA virus (ISAV-HPRΔ) between farms.</div><div>We described yearly static ship contact (reconstructed according to delay between visits: Δ = 1, 8 and 15 days) and company affiliation networks. We assessed the relevance of salmon production areas as subdivisions of these networks. Finally, we identified ship movements that could have resulted in ISAV-HPRΔ transmission between confirmed ISA-HPRΔ cases and explored whether either network was associated with the spatiotemporal distribution of these cases using a permutation test.</div><div>Connectivity was high in ship contact networks, with the largest strongly connected component encompassing ≥ 72 % of farms. Farms’ affiliations and locations in the same or differing production areas influenced their likelihood of being connected, however increasing Δ enabled the connection of distant regions. Both networks were associated with the distribution of ISA cases.</div><div>Ship movements and sharing of equipment or personnel are therefore potential viral transmission pathways. While the ship contact network was well structured by production areas, inadequate disinfection of ships could lead to longer ISAV survival times, thus resulting in long-distance ISAV-HPRΔ transmission events throughout the country. This study highlighted the need to further investigate the role of ships and fomites in fish disease spread; the use of genetic data could provide additional insights.</div></div>","PeriodicalId":20413,"journal":{"name":"Preventive veterinary medicine","volume":"245 ","pages":"Article 106667"},"PeriodicalIF":2.4,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144917171","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}