Preventive veterinary medicine最新文献

Gonadectomy in dogs is associated with changes in risks of a variety of non-infectious health conditions, but few studies have examined its effects on infectious disease outcomes. The objectives of our study were to estimate the causal effect of gonadectomy on the incidence rate of babesiosis diagnosis, and on the risk of severe babesiosis in diagnosed cases, in dogs 6 months and older seen at a veterinary academic hospital in South Africa from 2013 through 2020. To estimate the effect of gonadectomy on the incidence rate of babesiosis diagnosis in dogs, we conducted a case-control study with incidence density sampling of dogs seen through the hospital’s primary care service, adjusting for sex, age, breed category and weight. We identified 811 cases and selected 3244 time-matched controls. To estimate the effect of gonadectomy on disease severity in dogs with babesiosis, we conducted a retrospective cohort study among all dogs with a diagnosis of babesiosis (n=923), including these 811 cases and a further 112 referred to the hospital, also adjusting for sex, age, breed category and weight. Gonadectomy substantially reduced the incidence rate of babesiosis (total effect incidence rate ratio [IRR] 0.5; 95 % confidence interval [CI] 0.41–0.60) and the risk of severe babesiosis among diagnosed dogs (total effect risk ratio [RR] 0.72; 95 % CI 0.60–0.86). Tipping point sensitivity analysis shows that these effect estimates are robust to unmeasured confounding bias. There was no evidence for modification of the effect of gonadectomy by sex, with effect estimates qualitatively similar for males and females for both outcomes. Compared to females, males had a higher incidence rate of babesiosis (IRR 1.74; 95 % CI 1.49–2.04) and a higher risk of severe disease (RR 1.12; 95 % CI 0.98–1.28). In conclusion, our study shows a robust protective effect of gonadectomy on the incidence and severity of babesiosis in both male and female dogs 6 months of age and older, and contributes important evidence to the debate on the overall risks and benefits of gonadectomy to dogs in this population.

To assess and enhance the application of biosecurity measures in poultry farming, an objective measurement tool (Biocheck.UGent™) was already available for broiler and layer. This study describes the development, validation and application of a risk-based weighted scoring tool for breeder, turkey, duck, free-range layer and free-range broiler production. In collaboration with an expert panel (n= 38), five different questionnaires were developed, following the format of the existing Biocheck.UGent scoring tools. Weights were attributed to external (7–9 subcategories) and internal (3–4 subcategories) biosecurity categories, as well as to the corresponding individual questions within each subcategory. The biosecurity measures were prioritized and weighed based on their relative importance in preventing disease transmission. Upon completion of the questionnaire, and upload of all answers to the Biocheck.UGent website, the algorithm generates a biosecurity score varying between ‘’0’’ which equals the total absence of any biosecurity measure up to ‘’100’’ which refers to full application of all biosecurity measures. The final scoring systems are available online (https://biocheckgent.com/en) for free and have been used to assess biosecurity in 70 breeders, 100 turkeys, 23 ducks, 16 free-range broilers, and 15 free-range layer farms originating from 12 countries so far. On average, the overall biosecurity score (mean ± std. dev) was 78 ± 7 % for breeders, 73 ± 11 % for turkeys, 71 ± 8 % for ducks, 73 ± 8 % for free-range layers and 70 ± 13 % for free-range broilers. There were significant differences (p < 0.05) in biosecurity (both at the overall and subcategory levels) across different poultry types. The overall farm biosecurity score for breeders was significantly higher than that for turkey (p <.001) and duck production (p = 0.001). External biosecurity levels were highest in breeders in comparison to turkeys (p < 0.001), ducks (p = 0.008) and broiler free-range (p = 0.005). There was a notable difference in internal biosecurity levels between duck and turkey (p = 0.041) production as well. The study contributed to the poultry biosecurity database which allows benchmarking of the biosecurity levels of the users’ farm results to national or international averages, indicating room for improvement and aiding to motivate stakeholders to enhance their biosecurity levels.

Bluetongue disease is an infectious disease transmitted by Culicoides as vectors, mainly infecting ruminants. Because ruminants play an important role in animal husbandry in China, the outbreak of bluetongue disease can cause serious economic losses. Maxent model was applied to predict the distribution of bluetongue in China based on the data derived from domestic and foreign academic literature databases including CNKI, Wanfang Database, PubMed, Web of Science and Google Scholar. The results showed that annual mean temperature (BIO1), precipitation in driest month (BIO14), sheep density (SD) and altitude (Elev) were the relevant variables of bioclimatic suitable zones for bluetongue disease. Precipitation in wettest month (BIO13), BIO1, BIO14, Elev were the main variables affecting the habitat of the bluetongue vector Culicoides. The most suitable climate for bluetongue infection occurs in southern China, central China and parts of Xinjiang. The suitable living areas of Culicoides are mainly located in southern, central and eastern China, and the overlap of the two suitable areas is high. The study suggested that southern, central, and eastern China are high-risk areas for bluetongue due to the significant overlap of suitable habitats for both the disease and its vector. Implementing effective surveillance and targeted control strategies in these regions is crucial for mitigating the impact of bluetongue disease.

This study describes the association of non-esterified fatty acids (NEFA) and calcium concentrations at calving with early lactation disease, reproductive performance and culling in 646 dairy cows from 13 commercial grazing dairy herds in Uruguay. During one year, health events were recorded from calving to 30 days in milk (DIM). The first author visited each farm every 20 days. During each visit, body condition score (BCS) was recorded (scale 1–5), defining BCS < 3 as suboptimal and BCS > 3 as optimal, and a blood sample was taken from cows between 0 and 4 DIM for metabolite determination. To evaluate the association between health events (i.e., retained placenta-metritis and clinical mastitis) and risk factors (parity, BCS, high NEFA (> 0.6 mmol/L) and subclinical hypocalcemia (SCH) (< 2.10 mM)) data were analysed using multivariable logistic regression models. To evaluate the association of health events and risk factors with reproductive performance and culling, data were analysed using Cox proportional hazard regression models. A risk factor and an outcome of interest were assumed to be associated at P < 0.05 and a tendency to be associated was defined at P < 0.10. Overall, 47 % (n = 303) of the cows showed elevated NEFA concentration and 77 % (n = 499) had SCH. In addition, 21.5 % (n = 139) of the cows recorded at least one clinical disease. Cumulative incidence was 17 % (n = 109) for clinical mastitis, 4.2 % (n = 27) for retained placenta (RP)-metritis and 1.4 % (n = 7) for lameness. Clinical mastitis was associated with parity, with lower odds in primiparous (PP) cows (OR = 0.42, P < 0.01). Cows in an optimal BCS also tended to have lower odds (OR = 0.66, P = 0.07). Moreover, high NEFA and SCH cows had higher odds of CM (OR = 4.5, P = 0.01 and OR = 1.75, P = 0.04, respectively). Retained placenta-metritis tended to be associated with high NEFA concentration (OR = 2.2, P = 0.06). Primiparous cows with suboptimal BCS showed an increased first insemination rate (HR = 2.34; P < 0.01). The risk of culling was lower in PP cows (HR = 0.19; P < 0.01) and in cows with optimal BCS and low NEFA concentration (HR = 0.38; P = 0.03). Our data show that metabolic challenge (defined as peripartum suboptimal BCS, high NEFA or SCH) is associated with increased odds of clinical mastitis and RP-metritis, decreased probability of insemination and increased hazard of culling. Under grazing conditions, we suggest that farm management to improve the metabolic adaptation to lactation represents an opportunity to enhance cow performance in terms of health, fertility and longevity.

Antibiotic resistance is one of the major concerns in veterinary and human medicine and poses a considerable threat to both human and animal health. It has been shown that over- or misuse of antibiotics is one of the primary drivers of antibiotic resistance. To develop the surveillance of antibiotic use, Switzerland introduced the "Informationssystem Antibiotika in der Veterinärmedizin" (IS ABV) in 2019, mandating electronic registration of antibiotic prescriptions by all veterinarians in Switzerland. However, initial data analysis revealed a considerable amount of implausible data entries, potentially compromising data quality and reliability. These anomalies may be caused by input errors, inaccuracies, incorrect or aberrant master data or data transmission and make analysis impossible. To address this issue efficiently, we propose a two-stage anomaly detection framework utilizing machine learning algorithms. In this study, our primary focus was on cattle treatments with either single or group therapy, as they were the species with the highest prescription volume. However, not all outliers are necessarily incorrect; some may be legitimate but unusual antibiotic treatments. Thus, expert review plays a crucial role in distinguishing outliers, that are correct from actual errors. Initially, relevant prescription variables were extracted and pre-processed with a custom-built scaler. A set of unsupervised algorithms calculated the probability of each data point and identified the most likely outliers. In collaboration with experts, we annotated anomalies and established anomaly thresholds for each production type and active substance. These expert-annotated labels were then used to fine-tune the final supervised classification algorithms. With this methodology, we identified 22,816 anomalies from a total of 1,994,170 prescriptions in cattle (1.1 %). Cattle with no further specified production type had the most (2 %) anomalies with 7758 out of 379,995. The anomalies were consistently identified and comprised prescriptions with too high and too low dosages. Random Forest achieved a ROC-AUC score of 0.994, (95 % CI: 0.992, 0.995) and a F1-Score of 0.962 (95 % CI: 0.958, 0.966) for single treatments. The versatility of this framework allows its adaptation to other species within IS ABV and potentially to other prescription-based surveillance systems. If applied regularly to uploaded prescriptions, it should reduce input errors over time, improving the validity of the data in the long term.

In September 2023, bluetongue virus serotype 3 (BTV-3) emerged in the Netherlands, infecting over five thousand livestock farms. In sheep, high morbidity and mortality rates were reported that were unlike previously described bluetongue outbreaks. This study aimed to quantify the impact of BTV-3 in the small ruminant population in the Netherlands in 2023. Sheep and goat movement census data and BTV-3 notification data were available from 2020 until the end of 2023. Data were aggregated to farm and week level and mortality indicators were calculated for lambs (<1 year) and adult animals (≥1 year). Population averaged GEE models with a Negative-binomial distribution and a log-link function correcting for repeated measures per farm in time were used to quantify the association between BTV-3 and mortality. In 2023, 2994 sheep farmers and 89 goat farmers notified clinical signs of BTV-3 to the NVWA. During this BTV-3 outbreak period, an additional 55,000 sheep died compared to the same period in 2020–2022. At flock level a high variety in mortality was observed, with a clear increase in mortality in both flocks that were not notified but that were located in infected areas and in flocks of which the farmer notified clinical signs. During the BTV-3 outbreak period, mortality in infected areas increased 4.2 (95 % CI: 4.0–4.3) times in sheep lambs (<1 year) and 4.6 (95 % CI: 4.4–4.8) times in sheep (≥1 year) compared to BTV-3 free areas. Flocks with a confirmed BTV-3 infection that were notified in September showed a 12.8 (95 % CI: 11.4–14.3) times higher mortality in lambs and a 15.1 (95 % CI: 13.7–16.6) times higher mortality in sheep compared to flocks in BTV-3 areas. In flocks of which the farmer notified clinical signs after September, mortality was 4.6 (95 % CI: 4.2–5.0) and 5.6 (95 % CI: 5.1–6.0) times higher in lambs and sheep compared BTV-3 areas respectively. In goats, around 4000 additional deaths were recorded during the BTV-3 outbreak period. In farms that were notified, mortality of goats (≥1 year) was 1.8 (95 % CI: 1.2–2.8) times higher compared to BTV-3 free areas. Since May 2024, multiple BTV-3 vaccines are available in the Netherlands. In June 2024, the first new infections of BTV-3 were confirmed in Dutch sheep flocks. Hopes are that with the possibility to vaccinate, the spread and impact of BTV-3 in the Netherlands will rapidly decline and that losses as observed in 2023 will no longer be seen.

Limiting the use of antimicrobial agents in intensive livestock production is a challenge due to different perceptions between the short-term benefits of antimicrobial use (AMU) by livestock producers and the long-term social costs of antimicrobial resistance (AMR) and its impact on human, animal, and environmental health. Pig farmers are key stakeholders supporting Thailand’s national strategic plan on AMR which aims to reduce antimicrobial consumption in the livestock sector. Consequently, this study explored the knowledge, perceptions, attitudes, and practices of pig farmers towards AMU and AMR, expecting to provide information that would help guide policymakers in the development of a proper interventional program for antimicrobial stewardship. The qualitative approach utilized individual, face-to-face, in-depth, semi-structured interviews with the 20 owners of middle- and large-scale pig farms in eastern Thailand. The major themes identified in this finding were: (1) the use of antimicrobials on farms and the knowledge of antimicrobials; (2) AMU on pig farms (the purpose of AMU, antimicrobial prescription practices, and performing antimicrobial susceptibility testing); (3) attitudes towards prescribing practices and record keeping; (4) farm animal husbandry practices and AMU; (5) factors influencing AMU; and (6) awareness regarding AMR. Most of the pig farm owners recognized that achieving Good Agricultural Practices certification required following the legislation and regulations for AMU. Other observations were that the respondents had positive attitudes towards prescribing practices, performing antimicrobial susceptibility testing before antimicrobial therapy, and recording drug use on farms; however, there was low awareness of AMR. In addition, alternative substances, such as medicinal plants, and proper biosecurity practices were mentioned. Factors influencing AMU on pig farms were intensive enforcement of legislation and regulations, the implementation of farm management practices, the provision of information and consultancy services by veterinary professionals, farmer experience, and consumer trends.

Influenza A virus (IAV) is an important pathogen in Brazilian swine herds, and monitoring the viral circulation is essential to control and reduce the transmission. Surveillance programs for IAV are often based on individual piglets level sampling, making the evaluation of the available diagnostic tools crucial to assessing IAV circulation in herds. Thus, two sample collection methodologies were compared in pig herds in southern Brazil to detect IAV by RT-qPCR: nasal swab (NS) and nasal wipe (NW). A Bayesian latent class model (BLCM) was set for two tests and two populations. The NW and NS used are more specific (higher than 95 % for both) than sensitive. The sensitivity for NW was lower than the NS, 84.14 % (70 % – 95 %; posterior probability interval (PPI): 95 %) and 87.15 % (73 % – 97 %; PPI: 95 %), respectively, and the specificity was 95 % (90 % – 99 %; PPI: 95 %) and 99 % (96 % – 100 %; PPI: 95 %), respectively. Although the wipe sample collection loses both sensitivity and specificity compared with nasal swab, differences in test performance were very limited and PPIs largely overlapped. Therefore NW can also be considered a valuable tool. The decision about the use of both techniques should be based on the trade-off between their performance limitations and feasibility in routine monitoring.

This study aimed to describe the attitudes and personalities of farm managers (FMs) in large Estonian dairy herds and analyse the potential associations with calf mortality. The study included FMs from 114 free-stall farms with at least 100 cows. Each participant completed a questionnaire that comprised questions about the respondent and various statements to reveal their attitudes towards calves, calf mortality, and farming in general. A 7-point Likert scale was used to record the responses. The data on the number of live births and deaths and animal movement data were gathered from farm records and the Estonian Agricultural Registers and Information Board. The yearly calf mortality risk (%) during the first 21 days (YAG) and mortality rate between 22–90 days of age (OAG) adjusted for the animal time-at-risk were then calculated for each herd. Univariate negative binomial regression analysis was used to identify associations between calf mortality risk/rate, and the studied statements and variables with a p-value < 0.25 were included in a k-modes clustering analysis. The mean calf mortality risk was determined to be 5.9 % (range 0.0–26.8 %) during the first 21 days and mean calf mortality rate was 1.8 (range 0.0–9.2) deaths per 100 calf-months during 22–90 days of age. In both age group analyses, two FMs´ clusters formed based on 17 pre-selected statements. The FMs of the high-mortality cluster were found to be dissatisfied with the calf mortality levels. In the YAG analysis, FMs from high-mortality cluster gave lower priority to the issue of calf mortality, placed high importance on the influence of workers on calf mortality, and were more satisfied with the staff's performance compared to FMs of the cluster of herds with lower calf mortality. They were additionally less satisfied with their own performance and felt less recognized by the farm staff. They were also more inclined to try new products and practices on the farm and demonstrated greater empathy towards cattle. In the OAG analysis, the FMs from the higher-mortality cluster viewed reducing calf mortality more costly, had a less ambitious and target-driven management style, and rated their self-performance lower. This study determined that FMs working in herds with high calf mortality were dissatisfied and did not prioritize addressing calf mortality compared to managers working in farms with lower calf mortality. FMs' attitudes and management styles were associated with calf mortality, while the respondents' personality traits had little influence.

Toxoplasma gondii is a zoonotic pathogen that can infect farm animals, companion animals, and humans, sometimes causing public health issues. In Taiwan, the pig industry is a vital agricultural industry, with a self-sufficiency rate of 91 %, and pigs are also food-producing animal reservoirs of Toxoplasma gondii. Infected pigs are usually asymptomatic, and abortions and death may occur in severe cases. We combined an enzyme-linked immunosorbent assay (ELISA) and an indirect fluorescence assay (IFA) to investigate the seroprevalence of Toxoplasma gondii among pig populations in Taiwan. A stratified sampling approach to determine the number of sample farms proportional to the number of pig farms in each county was employed, with 15 blood samples collected at each farm between July and September 2017. With the tested results, empirical Bayesian smoothing was utilized to assess the proportion of Toxoplasma-positive farms at the county level. Bayesian mixed-effects logistic regression models, incorporating farm and county as random effects, were employed to investigate associations between Toxoplasma test results and potential risk factors. A total of 930 serum samples from 62 pig farms were collected and tested. An overall herd prevalence of 27.4 % was shown with the seroprevalence in northern Taiwan being greater than that in southern Taiwan. The sampling month and companion dog density in 2017 were significantly associated with Toxoplasma infections in pigs. With every increase in the number of companion dogs per km² at the county level, the odds of Toxoplasma infection in pigs increased by 4.7 % (95 % CI: 1.7–8.9 %). This study demonstrated that combining ELISA for screening with IFA for confirmation is a cost-effective and time-saving method for conducting a large-scale sample investigation. This was also the first nationwide, cross-sectional study in Taiwanese pig herds to investigate Toxoplasma gondii infection.