Preventive veterinary medicine最新文献

Equine Infectious Anemia (EIA) is a vector-borne persistent viral infection in equine animals. The EIA is characterized by recurrent fever, thrombocytopenia, depression, anemia, rapid weight loss, and lower body edema. Control of EIA is achieved through the elimination or isolation of infected animals, resulting in significant economic losses. In recent years, many countries in Europe have experienced outbreaks of EIA, which could potentially develop into a new wave of epidemic and pose a significant threat to the healthy development of the equine industry. This study utilized spatiotemporal analysis techniques and ecological niche modeling to investigate the spatiotemporal distribution characteristics of historical EIA outbreaks and predict risk areas for EIA occurrence in Europe. Spatiotemporal analysis results indicate that from 2005 to 2023, the EIA outbreaks in Europe exhibit five significant spatiotemporal clusters, with hotspots concentrated in southeastern France and northwestern Italy. Ecological niche modeling reveals that western, central, and southern Europe are high-risk areas for EIA outbreaks. Annual mean temperature, annual precipitation, and horse density are important variables that influence the occurrence of EIA. The results of this study can provide decision-makers with valuable insights, helping with EIA monitoring and resource allocation.

Identifying and restricting animal movements is a common approach used to mitigate the spread of diseases between premises in livestock systems. Therefore, it is essential to uncover between-premises movement dynamics, including shipment distances and network-based control strategies. Here, we analyzed three years of between-premises pig movements, which include 197,022 unique animal shipments, 3973 premises, and 391,625,374 pigs shipped across 20 U.S. states. We constructed unweighted, directed, temporal networks at 180-day intervals to calculate premises-to-premises movement distances, the size of connected components, network loyalty, and degree distributions, and, based on the out-going contact chains, identified network-based control actions. Our results show that the median distance between premises pig movements was 74.37 km, with median intrastate and interstate movements of 52.71 km and 328.76 km, respectively. On average, 2842 premises were connected via 6705 edges, resulting in a weak giant connected component that included 91 % of the premises. The premises-level network exhibited loyalty, with a median of 0.65 (IQR: 0.45 – 0.77). Results highlight the effectiveness of node targeting to reduce the risk of disease spread; we demonstrated that targeting 25 % of farms with the highest degree or betweenness limited spread to 1.23 % and 1.7 % of premises, respectively. While there is no complete shipment data for the entire U.S., our multi-state movement analysis demonstrated the value and the needs of such data for enhancing the design and implementation of proactive­ disease control tactics.

A large-scale study was carried out in the Polish goat population in 2014–2021 to determine the herd-level true seroprevalence (HTP) of caseous lymphadenitis (CLA) caused by Corynebacterium pseudotuberculosis (Cp) and paratuberculosis (PTB) caused by Mycobacterium avium ssp. paratuberculosis (Map). Two-stage cluster sampling was applied to herds counting at least 20 adult goats (aged >1 year) and in each herd all males and 10–13 females were tested. At least one seropositive goat regardless of its sex was necessary to consider the herd as infected. HTP was estimated using the Bayesian approach with the Gibbs sampler in the EpiTools and reported as the median and 95 % credibility interval (95 % CrI). A total of 1282 adult goats from 86 herds were serologically tested using two commercial ELISAs (Cp-ELISA and Map-ELISA). At least 1 seropositive result of Cp-ELISA and Map-ELISA was obtained in 73/86 herds (84.9 %) and 40/86 herds (46.5 %), respectively. HTP of CLA was estimated at 73.3 % (95 % CrI: 65.0 %, 80.4 %) and HTP of PTB was estimated at 42.9 % (95 % CrI: 25.8 %, 58.0 %). There was a significant positive association between the occurrence of CLA and PTB in the herds (odds ratio 6.0, 95 % confidence interval: 1.2, 28.8; p = 0.010). Probability of the seropositive result for PTB was also significantly higher in Cp-seropositive goats than in Cp-seronegative goats (odds ratio 3.9, 95 % confidence interval: 2.4, 6.3; p < 0.001) which could indicate either a higher risk of co-infection or a higher rate of false positive results for PTB in Cp-positive goats. To investigate this issue, optical densities obtained in Map-ELISA were compared between Cp-positive and Cp-negative goats and results of Map-ELISA were adjusted accordingly. Map-negative sera from Cp-positive goats turned out to have significantly higher optical densities than Map-negative sera from Cp-negative goats (p < 0.001). After the adjustment, the herd-level apparent seroprevalence of PTB was 41.9 % (36/86 herds) so it still fell within the 95 % CrI of HTP of PTB calculated before the adjustment. Concluding, CLA appears to be widespread in the Polish goat population. In many of them it may be subclinical at the moment, however will likely emerge in the future as the disease follows cyclic pattern in Poland. On the other hand, given the total lack of clinical PTB in Polish goats, an explanation for a high HTP of PTB remains unclear and warrants further studies using tests of higher analytical specificity than ELISA.

This study investigates the economic burden of calf mortality in Turkish dairy farms and its impact on the national economy. We gathered research data by directly surveying dairy farms in seven provinces, each representing a distinct region of Turkiye. By conducting these surveys, we captured data on various aspects of calf mortality, including losses among non-pregnant cows aged two and older, pregnant cows, and those experiencing complications during birth, as well as losses within the 0–6 month age bracket. These figures were then amalgamated to establish the overall calf loss rate. Using a fractional probit model, we examined the empirical relationship between total calf loss rates and the socio-demographic characteristics of farm operators and their establishments. Our findings revealed that approximately 82 % of farms experienced some degree of calf loss, with the calf loss rate among dairy cattle farming accounting for nearly 20 %. Notably, regional disparities emerged as a key observation, alongside the identification of certain socio-demographic farm characteristics that proved statistically significant. Specifically, factors such as the prevalence of local cattle breeds, the proportion of crossbred bulls, as well as the numbers of heifers and calves, stood out as influential. Further scrutiny, fortified by ANOVA tests and relationships between the number of cows and total calf loss rate, underscored pronounced geographical disparities in post-estimation calf loss rates. Meanwhile, correlation heatmaps illuminated noteworthy relationships between specific cattle traits and the extent of calf losses. These findings not only underscore the severity of the issue but also highlight the urgency of preventive measures. In light of these insights, we offer pertinent policy recommendations to stakeholders and policymakers aimed at mitigating this considerable economic burden effectively.

Ethiopia’s cattle population is among the largest in Africa and is burdened by frequent foot-and-mouth disease (FMD) outbreaks. FMD is caused by several distinct and highly contagious viral strains that can result in acute disease in cattle, causing losses in productivity and impeding international trade. This economic simulation study considered four main sources of losses due to FMD in cattle: reduced milk yield, draft power yield, fertility, and increased mortality. Economic losses were estimated per case across age-sex strata in 89 Ethiopian administrative zones for the years 2010–2021 using a wide range of data to estimate distributions for 30 input variables in a series of Monte Carlo simulations. It was estimated that an average case of FMD in Ethiopian cattle results in losses (mean values reported followed 95 % confidence intervals in brackets) of US dollars (USD) 11 (USD 7–USD 16) per case. Losses resulting from an average outbreak were estimated to be USD 2300 (USD 1400–USD 3300), while national annual losses were estimated to be USD 0.9 Mil. (USD 0.2 Mil.–USD 2.3 Mil.). Per cow-year, based on a national cow population of approximately 39 Mil. head, these estimated annual losses are equivalent to losses of only USD 0.02 (USD 0.01–USD 0.06). Nationally, these losses were significantly less than previously estimated in the literature, with currently estimated losses more accurately reflecting the economic burden of FMD in Ethiopian cattle over the past decade. The relatively small estimated losses suggest that control efforts based on widespread vaccination in countries with primarily extensive cattle production systems, such as Ethiopia, are unlikely to be economically sound. Sensitivity analyses suggested losses would be far greater in intensive systems, and that certainty surrounding incidence rates is paramount to the formulation of economically sound animal healthpolicy in regions with endemic FMD.

Due to its increasing occurrence in cattle farms in various countries, leading to significant economic losses in affected livestock, Salmonella enterica subspecies enterica serovar Dublin (S. Dublin) has become a highly investigated pathogen in cattle production. In Austria, there have been occasional human cases of S. Dublin as well as an increase in laboratory-confirmed cases in cattle, indicating the need for a screening programme to determine the current status in Austria. The aims of this study were, firstly, to determine the seroprevalence of S. Dublin in dairy herds through bulk milk screenings in two federal states (Salzburg, Tyrol) of Austria. Secondly, the study aimed to identify the infection status of the herds through individual animal and herd level detection, comparing microbiological, molecular and serological detection methods. The results of the study will allow the development of a sampling strategy for a surveillance programme in Austria.

A total of 6973 dairy farms were tested through serological bulk milk screening. The seroprevalence for the federal state of Tyrol was 14.8 % and for Salzburg it was 18.2 %, resulting in an average seroprevalence of 16.5 %. At an individual animal level, 205 (11.3 %) animals tested positive for shedding of S. Dublin in the faeces through microbiological detection, and 268 (17.0 %) animals had positive values (ct value ≤ 38) by qPCR. The association between microbiological and molecular detection was statistically significant (p < 0.001), with a calculated kappa value of 0.65 ± 0.27 (p ≤ 0.001), assuming a substantial level of agreement. In 17 herds, where an individual animal tested positive for shedding of S. Dublin, environmental sampling and testing were carried out. At a herd level 16 (94.1 %) out of the 17 participating herds, tested positive for S. Dublin either microbiologically or by molecular assay in boot swab samples. Bulk milk samples from 14 out of the 17 participating herds were analysed for antibodies to S. Dublin and 12 samples (85.7 %) were positive. In total 111 (18.9 %) out of 587 blood samples tested positive for S. Dublin antibodies, demonstrating a statistically significant correlation (p < 0.001) both with microbiological (κ = 0.32 ± 0.49; p ≤ 0.001) and molecular (κ=0.23 ± 0.06; p ≤ 0.001) findings.

It was possible to identify S. Dublin by culture from boot swabs in 14 (82.4 %) out of 17 herds and by molecular assay using qPCR in 15 (88.2 %) out of 17 herds, indicating a suitable sample type for screening on a herd level-basis for acute infections, but not for identifying chronic infections or asymptomatic carriers. Other environmental samples, such as sponge-sticks, are only suitable to a limited extent for the detection of S. Dublin. The results of this study demonstrate a moderate S. Dublin prevalence in dairy herds in the se