Preventive veterinary medicine最新文献

Monitoring antimicrobial use (AMU) is crucial, as it plays a key role in driving antimicrobial resistance (AMR). Animals account for a significant share of AMU, making it essential to accurately quantify AMU exposure at the species, farm, and country levels. In Pakistan, prophylactic use of antimicrobials remains common alongside therapeutic use. This study aimed to establish defined daily and course doses for both therapeutic and prophylactic use of antimicrobials in commercial broiler production in Pakistan. A list of antimicrobial products was compiled from the daily treatment records from 100 commercial broiler farms in Punjab, Pakistan. For each active substance (AS), a defined daily dose (DDD_vetPK) was assigned for treatment, prevention or both, by averaging the recommended doses of all similar AS with the same administration route. A defined course dose (DCD_vetPK) was calculated by multiplying the average recommended dose by the average treatment duration for each AS, based on the Summary of Product Characteristics (SmPC). A total of 41 AS, categorized into 17 antimicrobial classes, were identified from 139 antimicrobial products. The most frequently reported AS were colistin (polymyxins) at 15.9 %, amoxicillin (aminopenicillins) at 7.5 %, neomycin (aminoglycosides) at 7.3 %, enrofloxacin (fluoroquinolones) at 6.7 %, and tylosin (macrolides) at 6.4 % of the total treatments (n = 358) reported at farms. Notably, 51 % of AS were classified as critically important for human medicine by WHO. Among AS indicated for treatment in SmPC, the defined daily doses for Pakistan (DDD_vetPK) varied substantially from the European Medicines Agency (EMA) values (DDD_vet), with the top deviations being Tiamulin (+147.8 %), Sulfadimidine_TMP (+111.2 %), Flumequine (+88.6 %), Spiramycin (-87.8 %), and Tylosin (-84.3 %). This study presents a list of defined daily doses and defined course doses for AMU quantification in Pakistani broilers using dose-based indicators. The observed differences between Pakistani and EMA doses, and lack of EMA doses for preventive antimicrobials, suggest using Pakistani DDD_vetPK values to quantify antimicrobial usage in Pakistan. A huge variation in recommended doses was reported in SmPC. There is an urgent need to establish a list of approved veterinary antimicrobials used in Pakistan, along with harmonization in recommended doses and maintenance of standardized SmPC by the drug regulatory authorities. Setting up a national-level list of defined daily doses is crucial to accurately monitor and quantify AMU.

Passive surveillance can be most effective in the early detection of disease outbreaks given that farmers observe their animals daily. The European Animal Health Law states that unexplained excess mortality should be reported to the veterinary authorities. In the Netherlands, in addition to notifications to the competent authority, Royal GD is commissioned a passive surveillance component that consists of a veterinary helpdesk and postmortem examination for early detection of emerging diseases. The aim of this study was to evaluate this voluntary passive surveillance component through excess mortality in cattle.

Weekly on-farm mortality was calculated using the cattle Identification and Registration records. Mortality was assessed on regional level for dairy, veal and other beef cattle using a Generalized Linear Model (GLM) (log-link, negative binomial). We used a cumulative sum of the model residuals to identify periods of excess mortality. The mortality was defined as excessive when above five times the standard error. The analysis was also conducted on herd level, but these models did not converge.

We checked for an association between the two passive surveillance components elements and excess mortality. A GLM (log-link, negative binomial) with the number of contacts or submissions per region as the dependent variables and excess mortality per region and year as independent variables was carried out.

Overall, the models showed significantly higher use of passive surveillance components in periods of excess mortality compared to non-excess periods. In dairy cattle the odds for contact or submission were between 1.72 (1.59–1.86) and 2.02 (1.82–2.25). For veal calves we found the odds of 2.19 (1.18–4.04) and 2.24 (1.78–2.83) relative to periods without excess mortality. Beef cattle operations, other than veal, showed only an increased odds for postmortem submissions in calves of 3.71 (2.74–5.01), submissions for cattle and contact in general was not increased for this farm type.

In conclusion, the voluntary passive surveillance component in the Netherlands is used more often in periods of excess mortality in cattle. The chance of getting a timely response is highest for dairy farms. For veal calf operations the chance of receiving a timely response is more likely for postmortem submissions. A comparison with passive surveillance for excess mortality in other countries was not possible because no literature could be found. However, the method of this study can be used by other countries to evaluate their passive surveillance. This would make comparison of the performance of passive surveillance in different countries possible.

A follow up to an online questionnaire survey (in a kind of a sequential study design), qualitative assessment was made on the views of selected animal health experts on disease prioritization methods, resource allocation and use of decision-support tools. This was done through in-depth interviews with experts working for national or international organizations and sectors. A semi-structured question guide was formulated based on the information generated in the online questionnaire and a systematic content analysis of animal and human health manuals for disease prioritization and resource allocation. In-depth, one-on-one, online interviews on the process of disease prioritization, animal health decision-making, types of prioritization tools and aspects of improvements in the tools were conducted during March and April 2022 with 20 expert informants. Prioritization approaches reported by experts were either single criterion-based or multiple criteria-based. Experts appreciated the single-criterion-based approach (quantitative) for its objectivity in contrast to multicriteria prioritization approaches which were criticized for their subjectivity. Interviews with the experts revealed a perceived lack of quality and reliable data to inform disease prioritization, especially in smallholder livestock production systems. It was found that outputs of disease prioritization exercises do not generally directly influence resource allocation in animal health and highlighted the paucity of funding for animal health compared to other agricultural sectors. The experts considered that the available decision-support tools in animal health need improvement in terms of data visualization for interpretation, management decision making and advocacy. Further recommendations include minimizing subjective biases by increasing the availability and quality of data and improving the translation of disease prioritization outputs into actions and the resources to deliver those actions.

Data Availability Statement

The data can be obtained from the corresponding author upon request.

Sheep scab causes economic losses and animal welfare problems and has proven difficult to control in the UK. Research has highlighted the importance of developing place-based approaches to understanding and controlling sheep scab. This paper builds on this literature through introducing the concept of marginality in the case study of managing sheep scab on the island of Lewis and Harris in the Scottish Western Isles. The paper also proposes steps for developing a place-based understanding of biosecurity.

The research draws on interviews and workshops with crofters analysed using thematic analysis. Crofting is a unique system of land management particular to Scotland. Crofters have the right to manage a small area of private land and access to a larger area of common grazing. The research found that there was a tension between the cultural heritage and social benefits of traditional crofting practices of common grazing and communal husbandry of sheep and the biosecurity imperative to reduce the mixing of sheep to prevent the spread of disease. Dynamics of marginalisation were also disrupting established husbandry practices through a lack of people and loss of sheep from the land.

The crofters also identified collective actions they could take to tackle sheep scab, including collective dipping and controlling the movement of animals onto the island. Previous research has shown that in marginalised areas, social capital: networks between people, are not a panacea for bringing about positive change and additional resources from outside may be needed.

Based on the findings of this research we suggest three phases for developing a place-based conception of biosecurity for livestock keepers. The first phase is to understand both the biosecurity challenges facing communities and cultural and social aspects of farming systems that are important to a region. The second is to facilitate livestock keepers to co-produce their own priorities for biosecurity that allow them to address disease management challenges in their own constraints. The third phase is to enable communities to implement measures in their context. This can involve facilitating access to potential financial resources, equipment, expertise and links with other community groups. These phases will facilitate them in developing their definition of place-based biosecurity. This paper addresses the first and preliminary research on the second stages of this process. Further research will lead to actions on the third phase to help crofters in Lewis and Harris to put a place based communal understanding of biosecurity into practice.

The adoption of standardized metrics and indicators of antimicrobial use (AMU) in the food animal industry is essential for the success of programs aimed at promoting the responsible and judicious use of antimicrobials in this activity. The objective of this study was to introduce the use of standardized AMU metrics and indicators to quantify the use of florfenicol and oxytetracycline in the Chilean salmon industry, and in this way evaluate the feasibility of their use given the type of health and production information currently managed by the National Fisheries and Aquaculture Service (SERNAPESCA), the Chilean agency responsible for regulating aquaculture in Chile. The data available from SERNAPESCA allowed the construction and evaluation of the most data-demanding AMU metrics and indicators. Consequently, the use of florfenicol and oxytetracycline administered by oral and parenteral routes was quantified using the treatment incidence based on both animal defined daily dose (TI_DDDvet) and animal used daily dose (TI_UDDA). To that end, the study included information from 1320 closed production cycles from farms rearing Atlantic salmon, coho salmon and rainbow trout that were active between January 2017 and December 2021. By applying standardized AMU metrics and indicators, we were able to determine that the median of TI_DDDvet for florfenicol was 75.1 (80 % range, 20.0–158.0) DDDvet per ton-year at risk for oral procedures and 0.36 (80 % range, 0.07–1.19) DDDvet per ton-year at risk for parenteral procedures. For oxytetracycline, the median TI_DDDvet was 3.09 (80 % range, 0.74–42.8) and 0.47 (80 % range, 0.09–1.68) DDDvet per ton-year at risk for oral and parenteral procedures, respectively. The median TI_UDDA for treatments with florfenicol was 45.6 (80 % range, 10.9–96.5) UDDA per ton-year at risk for oral treatments and 0.28 (80 % range, 0.05–0.80) UDDA per ton-year at risk for parenteral treatments. For oxytetracycline, the median TI_UDDA was 2.63 (80 % range, 0.61–28.2) UDDA per ton-year at risk for oral treatments and 0.41 (80 % range, 0.08–1.29) UDDA per ton-year at risk for parenteral treatments. This study demonstrates that it is feasible to move from traditional AMU metrics and indicators to standardized ones in the Chilean salmon industry. This is possible because the competent authority requires salmon farms to report detailed health and production information at a high frequency. The use of standardized AMU metrics and indicators can help the authority to have a more comprehensive view of the antimicrobial use in the Chilean salmon industry.

Coxiella burnetii is a multi-host bacterium of major public and animal health concern. This pathogen circulates among several wild species in the Iberian Peninsula, however, the role of the Iberian lynx (Lynx pardinus) in the epidemiology of this emerging pathogen is still unknown. The objective of this work was to assess the circulation of C. burnetii in Iberian lynx populations from the Iberian Peninsula and to study the molecular characterisation of this pathogen in lynxes and their feeding ticks. A total of 922 lynxes, including free-ranging and captive individuals, were sampled between 2010 and 2022 for the collection of sera (n = 543), spleen samples (n = 390) and ticks (n = 357 from 61 lynxes). The overall seroprevalence was 7.7 % (42/543; 95 %CI: 5.5–10.0 %), with age being significantly associated with the C. burnetii exposure in free-ranging lynxes. A longitudinal study was also carried out to assess the dynamics of the circulation of C. burnetii in this wild host, revealing that 7 of the 37 longitudinally surveyed individuals seroconverted during the study period. The PCR prevalence was 4.4 % (17/390, 95 %CI: 2.3–6.4 %) for spleen samples and 1.1 % (4/357; 95 % CI: 0.0–2.2) in ticks. This is the first study to evaluate the circulation of C. burnetii in the Iberian lynx and to confirm the infection in this felid. The results obtained show a moderate, wide, homogeneous, and endemic circulation of this bacterium in the Iberian lynx populations.

Mortality during the post-weaning phase is a critical indicator of swine production system performance, influenced by a complex interaction of multiple factors of the epidemiological triad. This study leveraged retrospective data from 1723 groups of pigs marketed within a US swine production system to develop a Wean-Quality Score (WQS) using machine learning techniques. The study evaluated three machine learning models, Random Forest, Support Vector Machine, and Gradient Boosting Machine, to classify groups having high or low 60-day mortality, where high mortality groups represented 25 % of the groups among the study population with the highest mortality values (n=431; 60-day mortality=9.98 %), and the remaining 75 % of the groups were of low mortality (n=1292; 60-day mortality=2.75 %). The best-performing model, Random Forest (RF), outperformed the other ML models in terms of accuracy (0.90), sensitivity (0.84), and specificity (0.92) metrics, and was then selected for further analysis, which consisted of creating the WQS and ranking the most important factors for classifying groups as high or low mortality. The most important factors ranked through the RF model to classify groups with high mortality were pre-weaning mortality, weaning age, average parity of litters in sow farms, and PRRS status. Additionally, stocking conditions such as stocking density and time to fill the barn were important predictors of high mortality. The WQS was developed and correlated (r = 0.74) with the actual 60-day mortality of the groups, offering a valuable tool for assessing post-weaning survivability in swine production systems before weaning. This study highlights the potential of machine learning and comprehensive data utilization to improve the assessment and management of weaned pig quality in commercial swine production, which producers can utilize to identify and intervene in groups, according to the WQS.

Infectious diseases in livestock not only cause significant economic losses but also affect food security. Although wildlife may be involved in these infectious diseases by serving as reservoirs, research has primarily focused on livestock and related species. Moreover, while these species represent a potential threat in wildlife-borne infectious diseases, comprehensive surveys of the presence of various species are limited. In this study, we aimed to quantitatively investigate the occurrence of various mammals and birds at three pig farms in Japan. We conducted camera trap surveys from October 15, 2020, to March 24, 2022, and determined the relative abundance index inside and outside the sanitary control zone. Wild boar (Sus scrofa), sika deer (Cervus nippon), and Japanese serow (Capricornis crispus) were photographed only outside the sanitary control zone. In contrast, small and medium-sized mammals, such as feral cats (Felis catus), raccoons (Procyon lotor), and rodent species (Muridae), and birds, such as the rufous oriental turtle dove (Streptopelia orientalis) and crows of the genus Corvus, were photographed both inside and outside the sanitary control zone. This comprehensive quantitative evidence suggests that various mammals and birds may be in indirect contact with livestock, highlighting the need to improve biosecurity at livestock farms. Moreover, while fences are effective against large mammals, they are inefficient against small to medium-sized mammals and birds. Therefore, the results of this study provide important insights into enhancing biosecurity on livestock farms by strengthening physical fencing, disinfecting clothing and equipment, and complying with standards of hygiene management.

Bluetongue virus (BT) is a vector-borne virus that causes a disease, called bluetongue, which results in significant economic loss and morbidity in sheep, cattle, goats and wild ungulates across all continents of the world except Antarctica. Despite the geographical breadth of its impact, most BT epidemiological models are informed by parameters derived from the 2006–2009 BTV-8 European outbreak. The aim of this study was to develop a highly adaptable model for BT which could be used elsewhere in the world, as well as to identify the parameters which most influence outbreak dynamics, so that policy makers can be properly informed with the most current information to aid in disease planning.

To provide a framework for future outbreak modelling and an updated parameterisation that reflects natural variation in infections, a newly developed and parameterised two-host, two-vector species ordinary differential equation model was formulated and analysed. The model was designed to be adaptable to be implemented in any region of the world and able to model both epidemic and endemic scenarios. It was parameterised using a systematic literature review of host-to-vector and vector-to-host transmission rates, host latent periods, host infectious periods, and vaccine protection factors. The model was demonstrated using the updated parameters, with South Africa as a setting based on the Western Cape’s known cattle and sheep populations, local environmental parameters, and Culicoides spp. presence data.

The sensitivity analysis identified that the duration of the infectious period for sheep and cows had the greatest impact on the outbreak length and number of animals infected at the peak of the outbreak. Transmission rates from cows and sheep to C. imicola midges greatly influenced the day on which the peak of the outbreak occurred, along with the duration of incubation period, and infectious period for cows. Finally, the protection factor of the vaccine had the greatest influence on the total number of animals infected. This knowledge could aid in the development of control measures.

Due to gradual climate and anthropological change resulting in alterations in vector habitat suitability, BT outbreaks are likely to continue to increase in range and frequency. Therefore, this research provides an updated BT modelling framework for future outbreaks around the world to explore transmission, outbreak dynamics and control measures.

Effective management of cattle infected with Johne’s Disease (JD) is crucial to minimizing transmission and within-herd prevalence. Within Great Britain (GB), the voluntary National Johne’s Management Plan (NJMP) requires farmers and a certified vet to conduct a risk assessment to determine the herd risk, examine the herd JD status and formulate a management plan. Individual milk ELISA tests for JD antibodies are widely used to monitor infection. The JD Tracker application, available within the dairy data management software InterHerd+ and other web-based environments, is being used by farmers and veterinarians to facilitate the practical use of milk ELISA data to aid JD-related management decisions. The JD Tracker application uses a herd’s milk ELISA data to calculate a collection of ‘JD parameters’ that are indicative of the current JD status of the herd alongside contemporary and retrospective drivers linked to transmission and maintenance of infection. Herein, we use milk ELISA data from 154 regularly testing herds to review the temporal trends in JD parameters from 2013 to 2022. Since 2015, JD Tracker parameters have improved in these herds, most notably average test value (ATV) and within-herd prevalence (%Pos30). Trends in driver parameters suggest that farmers are progressively less likely to serve repeat test-positive (J5) cows and are more readily removing them. The data also reveal that the burden of JD is disproportionately greater in herds with higher ATV. In 2022, the 25 % of herds with the highest ATVs accounted for 42 % of positive tests and 42 % of repeat ELISA positive (J5) cows. Retrospectively, it is not possible to identify with certainty factors that directly contributed to the trends in JD parameters, but it is notable that the introduction of the NJMP was coincided with the improving JD situation. In 2019, participation in the NJMP or an equivalent scheme became mandatory for dairy farms to be compliant with the food and farms standards assurance scheme Red Tractor, with the result that JD management plans are now completed by 95 % of UK dairy farms. As far as we know, the UK is unique in its development of a tool (the JD Tracker) which adds utility to milk ELISA data using specifically designed JD parameters. Anticipated further work includes the development of a national database of JD testing herds and application of the JD Tracker at national scale to enable more comprehensive industry-level monitoring of JD within GB dairy farms.