Not all cows are epidemiologically equal: quantifying the risks of bovine viral diarrhoea virus (BVDV) transmission through cattle movements

Biosensor Technology: Advances and Applications in Livestock Infectious Disease Diagnosis

Biosensors have revolutionized the diagnosis of infectious diseases in livestock by offering sensitive and rapid detection methods for important pathogens. These devices, particularly luciferase-based biosensors, convert biological responses into quantifiable signals, enabling the real-time, non-invasive monitoring of critical biomarkers. This review explores the development and advantages of biosensors, focusing on their applications in detecting important livestock pathogens, including bacteria, parasites, and viruses. By comparing biosensors with traditional diagnostic methods, the review highlights their superior sensitivity and specificity in diagnosing obstetric infections. Furthermore, it discusses the broader utility of biosensors in monitoring gene expression, protein localization, and cellular events. Together, biosensors provide new tools for the timely diagnosis of infectious diseases in livestock and are critical to improving livestock health.

In vitro gene editing using primary cells derived from Cas9-expressing pigs

Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9 (CRISPR/Cas9) technology has significantly facilitated the generation of gene-edited (GE) pigs. Although GE pigs are promising for agricultural and biomedical applications, the entire process of generating useful GE pigs is time- and labor-intensive. To overcome this, in vivo gene-editing techniques have been developed, where Cas9 nuclease and single guide RNA (sgRNA) are directly injected into animals; however, their efficiency remains low owing to the large size of the nuclease. In this study, we generated a Cas9-expressing pig by inserting the Cas9 gene into the ROSA26 locus, resulting in its constitutive expression in various tissues. We also confirmed the pig's fertility. In vitro experiments with primary cells from the pig confirmed effective gene deletion by adding only sgRNAs. These results suggest that the Cas9-expressing pig generated in this study could serve as an effective platform for in vivo and in vitro gene editing in agricultural and biomedical research.

Development of a nucleic acid detection method based on the CRISPR-Cas13 for point-of-care testing of bovine viral diarrhea virus-1b

Bovine viral diarrhea (BVD) is a single-stranded, positive-sense ribonucleic acid (RNA) virus belonging to the genus Pestivirus of the Flaviviridae family. BVD frequently causes economic losses to farmers. Among bovine viral diarrhea virus (BVDV) strains, BVDV-1b is predominant and widespread in Hanwoo calves. Reverse-transcription polymerase chain reaction (RT-PCR) is an essential method for diagnosing BVDV-1b and has become the gold standard for diagnosis in the Republic of Korea. However, this diagnostic method is time-consuming and requires expensive equipment. Therefore, Clustered regularly interspaced short palindromic repeats-Cas (CRISPR-Cas) systems have been used for point-of-care (POC) testing of viruses. Developing a sensitive and specific method for POC testing of BVDV-1b would be advantageous for controlling the spread of infection. Thus, this study aimed to develop a novel nucleic acid detection method using the CRISPR-Cas13 system for POC testing of BVDV-1b. The sequence of the BVD virus was extracted from National Center for Biotechnology Information (NC_001461.1), and the 5' untranslated region, commonly used for detection, was selected. CRISPR RNA (crRNA) was designed using the Cas13 design program and optimized for the expression and purification of the LwCas13a protein. Madin Darby bovine kidney (MDBK) cells were infected with BVDV-1b, incubated, and the viral RNA was extracted. To enable POC viral detection, the compatibility of the CRISPR-Cas13 system was verified with a paper-based strip through collateral cleavage activity. Finally, a colorimetric assay was used to evaluate the detection of BVDV-1b by combining the previously obtained crRNA and Cas13a protein on a paper strip. In conclusion, the CRISPR-Cas13 system is highly sensitive, specific, and capable of nucleic acid detection, making it an optimal system for the early point-of-care testing of BVDV-1b.

The Epidemiology of Bovine Viral Diarrhea Virus in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis

Introduction

Bovine viral diarrhea virus (BVDV) causes reproductive inefficiencies and negatively impacts the economy of low- and middle-income countries (LMICs). It is characterized by a combination of syndromes that result in poor production performance and calf morbidity and mortality. BVDV control is possible by introduction of biosecurity measures, test-and-cull, and vaccination programs as accomplished in high-income countries. Knowledge of BVDV epidemiology is limited in many LMICs, which hinders implementation of effective control programs. We carried out a systematic review and meta-analysis to estimate the burden of BVDV, identify risk factors related to its occurrence, and health and economic impacts on production systems.

Materials and Methods

Relevant BVD articles were collated from library databases; 690 abstracts and full texts were found in an initial search followed by filtering of 59 manuscripts. We accounted for quality and risk of bias in the meta-analysis. Prevalence, exposure, and current infection at regional, production, and farming system levels were estimated using logistic random-effects meta-regression models. Finally, we calculated the proportion of studies that addressed risk factors and health and economic impacts across different production systems to inform future preventative strategies in LMICs.

Results

Seroprevalence was high and varied between regions. Mean weighted prevalence was 39.5% (95% CI 25-56.1), 45.2% (95% CI 35.9-54.8), 49.9% (95% CI 25.5-74.3), and 21.6% (95% CI 0.5-56) for sub-Saharan Africa, South America, Middle East, and Asia, respectively. Seroprevalence varied across farming systems, with smallholder farming showing the highest values. Herdsize was the most frequently reported risk factor, and the percentage of articles that reported herdsize as a risk factor were 20.6%, 33.3%, and 38.4% for dairy, beef and mixed systems respectively. Abortion (13.7% of articles) was the main reported health impact in dairy systems. Some articles reported milk drop (4.6% of articles), but no article investigated the economic cost of BVDV in farming systems.

Conclusion

Animal-level seroprevalence varied across all regions. Most of the studies focused on BVDV seroprevalence. There were some articles that investigated risk factors and health impacts, and there were even less that investigated economic impacts. Future studies should focus on identifying risk factors and quantifying health and economic impacts across systems. Understanding these aspects is crucial to develop management strategies to apply across diverse production systems in LMICs.

Modeling the Effect of Bovine Viral Diarrhea Virus in Australian Beef Herds

Bovine viral diarrhea virus (BVDV) is an economically important disease in Australian beef farming. The disease typically results in low-level production losses that can be difficult to detect for several years. Simulation modeling can be used to support the decision to control BVDV; however, current BVDV simulation models do not adequately reflect the extensive farming environment of Australian beef production. Therefore, the objective of this study was to develop a disease simulation model to explore the impact of BVDV on beef cattle production in south-east Australia. A dynamic, individual-based, stochastic, discrete-time simulation model was created to simulate within-herd transmission of BVDV in a seasonal, self-replacing beef herd. We used the model to simulate the effect of herd size and BVDV introduction time on disease transmission and assessed the short- and long-term impact of BVDV on production outputs that influence the economic performance of beef farms. We found that BVDV can become established in a herd after a single PI introduction in 60% of cases, most frequently associated with the breeding period. The initial impact of BVDV will be more severe in smaller herds, although self-elimination is more likely in small herds than in larger herds, in which there is a 23% chance that the virus can persist for >15 years following a single incursion in a herd with 800 breeders. The number and weight of steers sold was reduced in the presence of BVDV and the results demonstrated that repeat incursions exacerbate long-term production losses, even when annual losses appear marginal. This model reflects the short- and long-term production losses attributed to BVDV in beef herds in southeast Australia and provides a foundation from which the influence and economic utility of BVDV prevention in Australian beef herds can be assessed.

Quantifying changes in the British cattle movement network

The modelling of disease spread is crucial to the farming industry and policy makers. In some of these industries, excellent data exist on animal movements, along with the networks that these movements create, and allow researchers to model spread of disease (both epidemic and endemic). The Cattle Tracing System is an online recording system for cattle births, deaths and between-herd movements in the United Kingdom and is an excellent resource for any researchers interested in networks or modelling infectious disease spread through the UK cattle system. Data exist that cover many years, and it can be useful to know how much change is occurring in a network, to help judge the merit of using historical data within a modelling context. This article uses the data to construct weighted directed monthly movement networks for two distinct periods of time, 2004-2006 and 2015-2017, to quantify by how much the underlying structure of the network has changed. Substantial changes in network structure may influence policy-makers directly or may influence models built upon the network data, and these in turn could impact policy-makers and their assessment of risk. We examined 13 network metrics, ranging from general descriptive metrics such as total number of nodes with movements and total movements, through to metrics to describe the network (e.g., Giant weakly and strongly connected components) and metrics calculated per node (betweenness, degree and strength). Mixed effect models show that there is a statistically significant effect of the period (2004-2006 vs 2015-2017) in the values of nine of the 13 network metrics. For example median total degree decreased by 19%. In addition to examining networks for two time periods, two updates of the data were examined to determine by how much the movement data stored for 2004-2006 had been cleansed between updates. Examination of these updates shows that there are small decreases in problem movements (such as animals leaving slaughterhouses) and therefore evidence of historical data being improved between updates. In combination with the significant effect of period on many of the network metrics, the modification of data between updates provides further evidence that the most recent available data should be used for network modelling. This will ensure that the most representative descriptions of the network are available to provide accurate modelling results to best inform policy makers.

Seroprevalence of bovine viral diarrhea virus (BVDV) infection in cattle population in Iran: a systematic review and meta-analysis

Bovine viral diarrhea virus (BVDV) is an important pathogen correlated with reproductive, respiratory, and gastrointestinal disorders in cattle. Furthermore, it causes endemic infections and significant economic losses in cattle herds worldwide. This review was performed to determine the pooled seroprevalence of BVDV infection and related risk factors among cattle in Iran. Data were systematically gathered without time limitation until 1 December 2020 in the Islamic Republic of Iran from the following electronic databases: PubMed, Google Scholar, Science Direct, Scopus, Web of Science, Elmnet, Magiran, Irandoc, Scientific Information Database (SID), and Civilica. According to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) and inclusion criteria, 28 eligible studies were obtained from various Iran areas. In total, the pooled seroprevalence of BVDV infection, using random-effect model, was estimated 52% (95% CI, 40.1-63.9) in cattle. According to serological detection methods, pooled seroprevalence was as follows: based on ELISA 53.9% and SVN 25.1%. The highest pooled seroprevalence of BVDV infection was in the southeast provinces of Iran (78.4%) and lowest pooled seroprevalence was in Southwest provinces of the country (28.5%). The pooled seroprevalence of BVDV infection in cattle ≤ 2 years was significantly lower than cattle > 2 years (OR = 0.606; 95% CI, 0.397-0.925), whereas the pooled seroprevalence had no significant difference according to other factors such as gender, herd size, and herd types. In conclusion, the pooled seroprevalence of BVDV infection among cattle in Iran is relatively high. The seroprevalence was different among geographical regions of the country. These results are desirable for managing the control programs of this infection in Iran.

Why Test Purchased Cattle in BVDV Control Programs?

Bovine viral diarrhea (BVD) is controlled in many countries by detection and culling of persistently infected (PI) animals. The most important risk factor for BVDV introduction is purchase. An introduced cow can be PI and transmit the virus to other cattle in the herd. If she is not PI but is pregnant, there is still a risk because the subsequently born calf may be PI, when she encountered the virus in early pregnancy. To control this risk, all cows > 1 year from non-BVDV-free herds that are introduced in herds that participate in the Dutch BVDV control program are tested for virus and antibodies. Depending on the results, subsequent measures such as suspension of the BVDV-free status, removing the animals from the herd, or testing the off-spring of the cow for virus, are undertaken. The aim of this study was to evaluate the results of this risk mitigating measure. Data on cattle movements, calving's, herd-level BVDV status, and animal-level test data were available from all dairy herds that participated in the national BVDV control program (>14,000 dairy herds) for the year 2019. The data were combined and parameters of interest were calculated, i.e., (i) the number of purchased BVD virus positive cattle and (ii) the number of BVD virus positive calves born from purchased cows within 9 months after introduction. In 2019, 217,301 cattle were introduced in Dutch dairy herds that participated in the BVDV control program. Of these, 49,820 were tested for presence of BVD virus and 27 (0.05%) cows introduced in 21 different herds tested BVD virus positive. Out of 46,727 cattle that were tested for antibodies, 20.5% tested positive. The seropositive cows produced 4,341 viable calves, of which 3,062 were tested for virus and subsequently, 40 (1.3%) were found BVD virus positive. These 40 BVD virus positive calves were born in 23 herds. The risk mitigating measure led to detection of 67 BVD virus positive animals in 44 unique herds in 2019. This study makes plausible that the probability and impact of re-introduction of BVDV can be minimized by testing introduced cattle and their subsequently born calves.

Generative models of network dynamics provide insight into the effects of trade on endemic livestock disease

We develop and apply analytically tractable generative models of livestock movements at national scale. These go beyond current models through mechanistic modelling of heterogeneous trade partnership network dynamics and the trade events that occur on them. Linking resulting animal movements to disease transmission between farms yields analytical expressions for the basic reproduction number R ₀. We show how these novel modelling tools enable systems approaches to disease control, using R ₀ to explore impacts of changes in trading practices on between-farm prevalence levels. Using the Scottish cattle trade network as a case study, we show our approach captures critical complexities of real-world trade networks at the national scale for a broad range of endemic diseases. Changes in trading patterns that minimize disruption to business by maintaining in-flow of animals for each individual farm reduce R ₀, with the largest reductions for diseases that are most challenging to eradicate. Incentivizing high-risk farms to adopt such changes exploits 'scale-free' properties of the system and is likely to be particularly effective in reducing national livestock disease burden and incursion risk. Encouragingly, gains made by such targeted modification of trade practices scale much more favourably than comparably targeted improvements to more commonly adopted farm-level biosecurity.

Quantifying intraherd cattle movement metrics: Implications for disease transmission risk

There are a paucity of data quantifying on-farm management practices such as the frequency of intraherd cattle movements, use of consolidated or spatially fragmented grazing pastures, and duration of time cattle spend at grass with respect to biosecurity and disease transmission. Such movement dynamics are important when attempting to understand the maintenance of chronic infectious disease, such as bovine tuberculosis (bTB). We captured empirical data on daily cattle movements for a sample of eighteen farms throughout one complete grazing season (n = 18,988 grazing days) and assessed these attributes in relation to herd bTB risk. Dairy herds were stocked at significantly higher densities compared to beef production systems (6.6 animals/ha, 95 % confidence intervals (CI) 6.5-6.7 and 4.1 animals/ha, 95 %CI 4.1 - 4.1 respectively, p < 0.001). Most notably milking cows, were grazed at higher densities than other life stages (e.g. calves, heifers and bullocks) (p < 0.001) and experienced four times the number of movements between pastures. Beef cattle were more likely to be grazed across multiple (rather than single) fields (p < 0.001), with greater time spent on fragmented land away from the main/home farm (p < 0.001). None of the farm or herd attributes analysed (e.g. stocking density, frequency of movement, movement distances or land fragmentation) were associated with herd bovine tuberculosis (bTB) breakdowns during this study. However, there was a weak positive association between bTB breakdowns during the 3 years prior to the study and cattle movement distances (p = 0.05) and time spent on fragmented land (p = 0.08). After a bTB breakdown occurs, restrictions on animals moving out of these herds are implemented to control disease spread, yet we argue that more attention is needed on the role of intraherd grazing patterns in modelling disease transmission risk between herds.

Characterization of potential superspreader farms for bovine tuberculosis: A review

Background

Variation in host attributes that influence their contact rates and infectiousness can lead some individuals to make disproportionate contributions to the spread of infections. Understanding the roles of such ‘superspreaders’ can be crucial in deciding where to direct disease surveillance and controls to greatest effect. In the epidemiology of bovine tuberculosis (bTB) in Great Britain, it has been suggested that a minority of cattle farms or herds might make disproportionate contributions to the spread of Mycobacterium bovis, and hence might be considered ‘superspreader farms’.

Objectives and Methods

We review the literature to identify the characteristics of farms that have the potential to contribute to exceptional values in the three main components of the farm reproductive number ‐ R_f: contact rate, infectiousness and duration of infectiousness, and therefore might characterize potential superspreader farms for bovine tuberculosis in Great Britain.

Results

Farms exhibit marked heterogeneity in contact rates arising from between‐farm trading of cattle. A minority of farms act as trading hubs that greatly augment connections within cattle trading networks. Herd infectiousness might be increased by high within‐herd transmission or the presence of supershedding individuals, or infectiousness might be prolonged due to undetected infections or by repeated local transmission, via wildlife or fomites.

Conclusions

Targeting control methods on putative superspreader farms might yield disproportionate benefits in controlling endemic bovine tuberculosis in Great Britain. However, real‐time identification of any such farms, and integration of controls with industry practices, present analytical, operational and policy challenges.

Quantification of risk factors for bovine viral diarrhea virus in cattle herds: A systematic search and meta-analysis of observational studies

Bovine viral diarrhea virus (BVDV) is endemic in many parts of the world, and multiple countries have implemented surveillance activities for disease control or eradication. In such control programs, the disease-free status can be compromised by factors that pose risks for introduction or persistence of the virus. The aim of the present study was to gain a comprehensive overview of possible risk factors for BVDV infection in cattle herds in Europe and to assess their importance. Papers that considered risk factors for BVDV infection in cattle were identified through a systematic search. Further selection of papers eligible for quantitative analysis was performed using a predefined checklist, including (1) appropriate region (i.e., studies performed in Europe), (2) representativeness of the study population, (3) quality of statistical analysis, and (4) availability of sufficient quantitative data. In total, 18 observational studies were selected. Data were analyzed by a random-effects meta-analysis to obtain pooled estimates of the odds of BVDV infection. Meta-analyses were performed on 6 risk factors: herd type, herd size, participation in shows or markets, introduction of cattle, grazing, and contact with other cattle herds on pasture. Significant higher odds were found for dairy herds (odds ratio, OR = 1.63, 95% confidence interval, CI: 1.06-2.50) compared with beef herds, for larger herds (OR = 1.04 for every 10 extra animals in the herd, 95% CI: 1.02-1.06), for herds that participate in shows or markets (OR = 1.45, 95% CI: 1.10-1.91), for herds that introduced cattle into the herd (OR = 1.41, 95% CI: 1.18-1.69), and for herds that share pasture or have direct contact with cattle of other herds at pasture (OR = 1.32, 95% CI: 1.07-1.63). These pooled values must be interpreted with care, as there was a high level of heterogeneity between studies. However, they do give an indication of the importance of the most frequently studied risk factors and can therefore assist in the development, evaluation, and optimization of BVDV control programs.

Genetic Diversity of Bovine Pestiviruses Detected in Backyard Cattle Farms Between 2014 and 2019 in Henan Province, China

Bovine pestiviruses include Pestivirus A (BVDV-1), Pestivirus B (BVDV-2), and Pestivirus H, which was originally called HoBi-like pestivirus. We conducted an epidemiological investigation for pestiviruses circulating in backyard cattle farms in central China. RT-PCR assays and sequences analysis were conducted on 54 nasal swabs, 26 serum samples, and three lung samples from cattle with respiratory infections and identified 29 pestivirus strains, including 24 Pestivirus A and five Pestivirus H strains. Phylogenetic analysis based on partial 5'-UTR and Npro sequences showed that the genotypes of 24 Pestivirus A strains included Pestivirus A 1b (six isolates), Pestivirus A 1m (six isolates), Pestivirus A 1q (two isolates), Pestivirus A 1u (one isolates), and Pestivirus A 1o (nine isolates, a putative new sub-genotype). In addition, a single Pestivirus H agenotype included all five Pestivirus H strains. This study revealed extensive genetic variations within bovine pestivirus isolates derived from cattle in backyard farms in Central China, and this epidemiological information improves our understanding of the epidemics of bovine Pestiviruses, as well as will be useful in designing and evaluating diagnostic methods and developing more effective vaccines.

Estimation of the within-herd transmission rates of bovine viral diarrhoea virus in extensively grazed beef cattle herds

Many research groups have developed mathematical models to simulate the dynamics of BVDV infections in cattle herds. However, most models use estimates for within-herd BVDV transmission rates that are either based on expert opinion or adapted from other dairy herd simulation models presented in the literature. There is currently little information on the transmission rates for BVDV in extensively grazed beef herds partly due to the logistical challenges in obtaining longitudinal data of individual animal’s seroconversion, and it may not be appropriate to apply the same transmission rates from intensive dairy herds given the significant differences in herd demographics and management. To address this knowledge gap, we measured BVDV antibody levels in 15 replacement heifers in each of 75 New Zealand beef breeding farms after their first calving and again at pregnancy scanning or weaning to check for seroconversion. Among these, data from 9 farms were used to infer the within-herd BVDV transmission rate with an approximate Bayesian computation method. The most probable within-herd BVDV transmission rate was estimated as 0.11 per persistently infected (PI) animal per day with a 95% highest posterior density interval between 0.03 and 0.34. This suggests that BVDV transmission in extensively grazed beef herds is generally slower than in dairy herds where the transmission rate has been estimated at 0.50 per PI animal per day and therefore may not be sufficient to ensure that all susceptible breeding females gain adequate immunity to the virus before the risk period of early pregnancy for generating new PI calves.

Network structure and risk-based surveillance algorithms for live shrimp movements in Thailand

Live shrimp movements pose a potential route for site-to-site transmission of acute hepatopancreatic necrosis disease (AHPND) and other shrimp diseases. We present the first application of network theory to study shrimp epizootiology, providing quantitative information about the live shrimp movement network of Thailand (LSMN), and supporting practical and policy implementations of disease surveillance and control measures. We examined the LSMN over a 13-month period from March 2013 to March 2014, with data obtained from the Thailand Department of Fisheries. The LSMN had a mixture of characteristics both limiting and facilitating disease spread. Importantly, the LSMN exhibited power-law distributions of in and out degrees with exponents of 2.87 and 2.17, respectively. This characteristic indicates that the LSMN behaves like a scale-free network and suggests that an effective strategy to control disease spread in the Thai shrimp farming sector can be achieved by removing a small number of targeted inter-site connections (arcs between nodes). Specifically, a disease-control algorithm based on betweenness centrality (defined as the number of shortest paths between node pairs that traverse a given arc) is proposed here to prioritize targets for disease surveillance and control measures.

Neighbourhood contacts and trade movements drive the regional spread of bovine viral diarrhoea virus (BVDV)

To explore the regional spread of endemic pathogens, investigations are required both at within and between population levels. The bovine viral diarrhoea virus (BVDV) is such a pathogen, spreading among cattle herds mainly due to trade movements and neighbourhood contacts, and causing an endemic disease with economic consequences. To assess the contribution of both transmission routes on BVDV regional and local spread, we developed an original epidemiological model combining data-driven and mechanistic approaches, accounting for heterogeneous within-herd dynamics, animal movements and neighbourhood contacts. Extensive simulations were performed over 9 years in an endemic context in a French region with high cattle density. The most uncertain model parameters were calibrated on summary statistics of epidemiological data, highlighting that neighbourhood contacts and within-herd transmission should be high. We showed that neighbourhood contacts and trade movements complementarily contribute to BVDV spread on a regional scale in endemically infected and densely populated areas, leading to intense fade-out/colonization events: neighbourhood contacts generate the vast majority of outbreaks (72%) but mostly in low immunity herds and correlated to a rather short presence of persistently infected animals (P); trade movements generate fewer infections but could affect herds with higher immunity and generate a prolonged presence of P. Both movements and neighbourhood contacts should be considered when designing control or eradication strategies for densely populated region.

Assessment of the cost effectiveness of compulsory testing of introduced animals and bulk tank milk testing for bovine viral diarrhea in Japan

Bovine viral diarrhea (BVD) is a chronic disease of cattle caused by infection with BVD virus (BVDV) and can result in economic losses within the livestock industry. In Japan, the test and culling policy is a basic control measure, and implementation of an adequate vaccination program is recommended as a national policy. In addition, optional control measures, including compulsory testing of introduced animals and bulk tank milk (BTM) testing as a mass screening method, are used in several provinces, but their efficacy has not been completely assessed. We evaluated these control measures using the scenario tree model of BVD in Japan, developed in the previous study. The model outputs indicated that compulsory testing of all introduced cattle, rather than only heifers and/or non-vaccinated cattle, was cost effective and reduced the risk of BVDV introduction due to animal movement and that BTM testing could effectively monitor most part of the cattle population. Vaccination coverage and BVDV prevalence among introduced cattle could also affect the cost effectiveness of compulsory testing of targeted cattle, particularly under low vaccination coverage or high BVDV prevalence. However, even with the implementation of a highly effective monitoring scheme for many years, BVD risk could not be eliminated; it instead converged at a very low level (0.02%). Disease models with a cost-effective output could be a powerful tool in developing a control scheme for chronic animal diseases, including BVD, with the consent of relevant stakeholders.

Farm productive contexts and the dynamics of bovine viral diarrhea (BVD) transmission

Bovine viral diarrhea (BVD) is a viral disease that affects cattle and that is endemic to many European countries. It has a markedly negative impact on the economy, through reduced milk production, abortions, and a shorter lifespan of the infected animals. Cows becoming infected during gestation may give birth to Persistently Infected (PI) calves, which remain highly infective throughout their life, due to the lack of immune response to the virus. As a result, they are the key driver of the persistence of the disease both at herd scale, and at the national level. In the latter case, the trade-driven movements of PIs, or gestating cows carrying PIs, are responsible for the spatial dispersion of BVD. Past modeling approaches to BVD transmission have either focused on within-herd or between-herd transmission. A comprehensive portrayal, however, targeting both the generation of PIs within a herd, and their displacement throughout the country due to trade transactions, is still missing. We overcome this by designing a multiscale metapopulation model of the spatial transmission of BVD, accounting for both within-herd infection dynamics, and its spatial dispersion. We focus on Italy, a country where BVD is endemic and seroprevalence is very high. By integrating simple within-herd dynamics of PI generation, and the highly-resolved cattle movement dataset available, our model requires minimal arbitrary assumptions on its parameterization. We use our model to study the role of the different productive contexts of the Italian market, and test possible intervention strategies aimed at prevalence reduction. We find that dairy farms are the main drivers of BVD persistence in Italy, and any control strategy targeting these farms would lead to significantly higher prevalence reduction, with respect to targeting other production compartments. Our multiscale metapopulation model is a simple yet effective tool for studying BVD dispersion and persistence at country level, and is a good instrument for testing targeted strategies aimed at the containment or elimination of this disease. Furthermore, it can readily be applied to any national market for which cattle movement data is available.

Contact chains of cattle farms in Great Britain

Network analyses can assist in predicting the course of epidemics. Time-directed paths or 'contact chains' provide a measure of host-connectedness across specified timeframes, and so represent potential pathways for spread of infections with different epidemiological characteristics. We analysed networks and contact chains of cattle farms in Great Britain using Cattle Tracing System data from 2001 to 2015. We focused on the potential for between-farm transmission of bovine tuberculosis, a chronic infection with potential for hidden spread through the network. Networks were characterized by scale-free type properties, where individual farms were found to be influential 'hubs' in the network. We found a markedly bimodal distribution of farms with either small or very large ingoing and outgoing contact chains (ICCs and OCCs). As a result of their cattle purchases within 12-month periods, 47% of British farms were connected by ICCs to more than 1000 other farms and 16% were connected to more than 10 000 other farms. As a result of their cattle sales within 12-month periods, 66% of farms had OCCs that reached more than 1000 other farms and 15% reached more than 10 000 other farms. Over 19 000 farms had both ICCs and OCCs reaching more than 10 000 farms for two or more years. While farms with more contacts in their ICCs or OCCs might play an important role in disease spread, farms with extensive ICCs and OCCs might be particularly important by being at higher risk of both acquiring and disseminating infections.

Seroprevalence and risk factors associated with bovine viral diarrhea virus and bovine herpes virus-1 in Zanjan Province, Iran

Bovine viral diarrhea virus (BVDV) and bovine herpes virus-1 (BHV-1) remain as the major pathogens with heavy economic consequences in Iran. The prevalence of antibodies against BVDV and BHV-1, the rate of BVDV persistently infected (PI) animals, and associated risk factors were evaluated in a cross-sectional study carried out in Zanjan Province, Northwest Iran, in December 2011. A total number of 562 cattle in 10 herds and five cities were randomly selected, and their serum samples were tested to detect antibodies to these viruses and also BVDV antigen-positive (PI) animals. The data were analyzed with Pearson's correlation coefficient, chi-square, and logistic regression test. In total, nine and eight of the selected herds were seropositive to BVDV and BHV-1, respectively. The overall seroprevalence of these infections were estimated at 28.6 and 10.7% for BVDV and BHV-1, respectively, and 0.53% of the samples were detected as persistently infected. Statistical analysis revealed that sex, age, and farming system are risk factors for both infections (P < 0.05), while breed was determined as a strong risk factor only for BVDV (P < 0.001). In addition, the present study certainly identifies that infection with BVDV is associated with infection to BHV-1 (OR = 4.52, 95% CI: 2.60-7.80; P ˂ 0.001). The results add our knowledge about the prevalence and associated risk factors of BVDV and BHV-1 in Iran and imply that the prophylactic and surveillance strategies need to be implemented to reduce the risk of spread of these viruses.

Identification of a new bovine viral diarrhea virus subtype in the Republic of Korea

Background

Bovine viral diarrhea virus (BVDV) is prevalent in Korean indigenous cattle, leading to substantial economic losses. This study was conducted to investigate the occurrence of BVDV. In 2016, a total of 143 blood samples were collected from asymptomatic Korean indigenous calves younger than 3-months of age from six different farms in the Republic of Korea (ROK).

Results

Eighty-seven calves (60.8%, 87/143) were tested positive for BVDV as evaluated by RT-PCR analysis. Phylogenetic analysis based on the 5′-untranslated region was used to classify these cases into three subtypes: BVDV-1b, BVDV-1o, and BVDV-2a. These results showed that BVDV-1b was the predominant subtype, while 2 samples clustered with BVDV-2a. Interestingly, one sample formed a separate group as a potentially new subtype, BVDV-1o. To our knowledge, this is the first report of BVDV-1o infection in Korean native calves. The BVDV-1o subtype identified in this study was closely related to cattle isolates obtained from Japan, indicating that this subtype is a new introduction to the ROK.

Conclusions

This study provides useful information for carrying out epidemiological surveys of BVDV in the ROK and developing a vaccine for future use in the ROK, particularly for the first detection of BVDV-1o in Korean indigenous calves. Further studies are required to investigate the prevalence and pathogenicity of this BVDV-1o subtype.

Livestock Disease Management for Trading Across Different Regulatory Regimes

The maintenance of livestock health depends on the combined actions of many different actors, both within and across different regulatory frameworks. Prior work recognised that private risk management choices have the ability to reduce the spread of infection to trading partners. We evaluate the efficiency of farmers' alternative biosecurity choices in terms of their own-benefits from unilateral strategies and quantify the impact they may have in filtering the disease externality of trade. We use bovine viral diarrhoea (BVD) in England and Scotland as a case study, since this provides an example of a situation where contrasting strategies for BVD management occur between selling and purchasing farms. We use an agent-based bioeconomic model to assess the payoff dependence of farmers connected by trade but using different BVD management strategies. We compare three disease management actions: test-cull, test-cull with vaccination and vaccination alone. For a two-farm trading situation, all actions carried out by the selling farm provide substantial benefits to the purchasing farm in terms of disease avoided, with the greatest benefit resulting from test-culling with vaccination on the selling farm. Likewise, unilateral disease strategies by purchasers can be effective in reducing disease risks created through trade. We conclude that regulation needs to balance the trade-off between private gains from those bearing the disease management costs and the positive spillover effects on others.

Spatial analysis for bovine viral diarrhea virus and bovine herpesvirus type 1 infections in the state of Paraíba, northeastern Brazil

BACKGROUND

Bovine Viral Diarrhea Virus (BVDV) and Bovine Herpesvirus type 1 (BoHV-1) cause reproductive problems in cattle and restrictions on international trade in animals worldwide. Both infections were detected in cattle herds in the Paraíba state, Northeastern Brazil, however, the spatial distribution and geographic identification of positive herds for these viruses has never been examined. Therefore, the aim of this study was to describe the spatial pattern of apparent prevalence estimate and to identify spatial clustering of positive herds of BVDV and BoHV-1 infections in cattle herds from the state of Paraíba, Northeastern Brazil.

RESULTS

The herd-level prevalence for BVDV and BoHV-1 infections in Paraíba were, respectively, 65.5% (95% CI: 61.1-69.7) and 87.8% (95% CI: 84.5-90.5). The average apparent within-herd prevalence of BVDV was 31.8% and of BoHV-1 was 62.4%. The predicted prevalence was highest (0.42-0.75) for BVDV in the west, north and eastern part of Sertão and in the central and eastern part of Agreste/Zona da Mata. For BoHV-1, the highest predicted prevalence (0.74-0.97) was in some local areas across Sertão and throughout the eastern part of Agreste/Zona da Mata. Six significant clusters were detected for BVDV, a primary cluster covering the eastern Sertão region, with 11 herds, radius of 24.10 km and risk relative (RR) of 2.21 (P <  0.001) and five smaller significant clusters, involving one or two herds in Agreste/Zona da Mata region with a high RR. A significant clustering of BoHV-1 positive herds (P <  0.001) was detected in Agreste/Zona da Mata region with a radius of 77.17 km and a RR of 1.27, with 103 cases. Consistency was found between kriging and SatScan results for identification of risk areas for BVDV and BoHV-1 infections.

CONCLUSIONS

The clusters detected contemplated different areas of the state, with BVDV cluster located in the Sertão and BoHV-1 in Agreste/Zona da Mata stratum. Through the risk mapping, it was possible to identify the areas in which the risk is significantly elevated, coincided with areas where there are borders with other states and in which there is a high movement of animals.

A quantitative risk-analysis for introduction of Bovine Viral Diarrhoea Virus in the Netherlands through cattle imports

Many countries have implemented control programmes aiming to eradicate Bovine Viral Diarrhoea Virus (BVDV). After obtaining the free status, a risk of re-introduction of the virus through import may remain. Therefore the risk of introduction of BVDV through cattle imports in the Netherlands was quantified and the effectiveness of subsequent intervention measures was assessed. Data, literature and expert opinion were used to estimate values for input parameters to feed a stochastic simulation model. The probability that BVDV was imported was differentiated into persistently infected (PI) cattle, trojan cows that transmitted the virus vertically resulting in a PI foetus (TR) and transient infected cattle (TI). The import risk was stratified to beef, dairy, small scale, suckler, trade, veal and young stock herds. The intervention scenarios that were evaluated consisted of virus testing, a combination of virus testing and antibody testing in pregnant cows, abolishment of imports from high risk countries (i.e. countries with a BVDV prevalence >15%) and a combination of import restrictions and testing prior to import. Each year, 334 (5th and 95th percentile: 65-902) Dutch cattle herds were estimated to be infected with BVDV through import. Veal herds account for most infections associated with import (87%), whereas in the other herd types, only 9 beef, 6 dairy, 2 small scale, 16 suckler, 10 trade and 2 young stock herds are infected through imports per year. Import of PI cattle is the most important risk for introduction in veal herds, while import of TR cows is the main source of BVDV introduction in dairy, small scale and suckler herds. With the intervention scenarios, the number of BVDV infected herds in the Netherlands could be reduced to 81 and 58 herds per year when respectively virus testing or a combination of virus and antibody testing was applied or to 108 herds when import from high risk countries was abolished. With the scenario in which both import from high risk countries was abolished combined with virus and antibody testing, the number of BVDV infected herds could be reduced to 17 herds per year. The risk assessment showed that BVDV is regularly imported in the Netherlands. The import risk can effectively be reduced by implementing diagnostic testing prior to import and only import cattle with a favourable result, eventually combined with certain trade restrictions.

Assessment of concurrent infection with bovine viral diarrhoea virus (BVDV) and Mycobacterium bovis: A herd-level risk factor analysis from Northern Ireland

Bovine viral diarrhoea virus (BVDV) is a significant pathogen of cattle, leading to severe economic and animal-welfare impacts. Furthermore, the pathogen has been associated with impacting the progression or spread of other pathogens (e.g. Mycobacterium bovis, the causative agent of bovine tuberculosis (bTB)). During this study we investigated (i) risk factors for BVDV at a herd-level and (ii) whether there was any association between BVDV and herd-level bTB risk. The data for this study were gathered from a voluntary BVDV control programme in Northern Ireland (2013-2015) based on the identification of virus positive animals through tissue tag testing of calves. We assigned a herd-level BVDV status to 2827 participating herds, where a herd was assumed "infected" if one or more animals tested positive for BVDV. Two model suites were developed. Firstly, we assessed risk factors for BVDV herd status using multivariable logit random-effects modelling, aggregating to the calendar year level (2013-2015; n=4828; model 1). Secondly, we aggregated data across the three years of the study to give an overall status for the whole study period (n=2827; logistic model 2). Risk factors included year, herd-type, herd size, number of births, inward trade moves, calf mortality, and region. Furthermore, the herd-level bovine tuberculosis status (based on the single intradermal comparative cervical tuberculin (SICCT) test outcomes, or confirmation at post-mortem), or the size of bTB breakdowns (number of SICCT test positive animals), of herds was also investigated to assess whether there was an association (co-infection) with herd BVDV status. The final models suggested that BVDV herd status was positively associated with increased levels of calf mortality, herd size, number of births, the number of BVDV tests undertaken and the number of animals introduced to the herd. There was a significant univariable positive association between BVDV status, and SICCT breakdown risk, breakdown size and confirmed bTB status in model 2. However, there was no evidence of significant associations between bTB status (using SICTT status, confirmed status or herd breakdown size) and BVDV status in final multivariable models when controlling for other significant confounders. These results provide information for action for the future control and eradication of BVDV in Northern Ireland, though these data provide little support for the hypothesised association between BVDV and bTB status at herd-level. Further animal-level analyses are necessary to investigate whether there is support for a BVD-bTB co-infection association, including the impact of co-infection on the severity of infection.

Data-driven network modelling of disease transmission using complete population movement data: spread of VTEC O157 in Swedish cattle

European Union legislation requires member states to keep national databases of all bovine animals. This allows for disease spread models that includes the time-varying contact network and population demographic. However, performing data-driven simulations with a high degree of detail are computationally challenging. We have developed an efficient and flexible discrete-event simulator SimInf for stochastic disease spread modelling that divides work among multiple processors to accelerate the computations. The model integrates disease dynamics as continuous-time Markov chains and livestock data as events. In this study, all Swedish livestock data (births, movements and slaughter) from July 1st 2005 to December 31st 2013 were included in the simulations. Verotoxigenic Escherichia coli O157:H7 (VTEC O157) are capable of causing serious illness in humans. Cattle are considered to be the main reservoir of the bacteria. A better understanding of the epidemiology in the cattle population is necessary to be able to design and deploy targeted measures to reduce the VTEC O157 prevalence and, subsequently, human exposure. To explore the spread of VTEC O157 in the entire Swedish cattle population during the period under study, a within- and between-herd disease spread model was used. Real livestock data was incorporated to model demographics of the population. Cattle were moved between herds according to real movement data. The results showed that the spatial pattern in prevalence may be due to regional differences in livestock movements. However, the movements, births and slaughter of cattle could not explain the temporal pattern of VTEC O157 prevalence in cattle, despite their inherently distinct seasonality.

Evaluation of farm-level parameters derived from animal movements for use in risk-based surveillance programmes of cattle in Switzerland

Background

This study focused on the descriptive analysis of cattle movements and farm-level parameters derived from cattle movements, which are considered to be generically suitable for risk-based surveillance systems in Switzerland for diseases where animal movements constitute an important risk pathway.

Methods

A framework was developed to select farms for surveillance based on a risk score summarizing 5 parameters. The proposed framework was validated using data from the bovine viral diarrhoea (BVD) surveillance programme in 2013.

Results

A cumulative score was calculated per farm, including the following parameters; the maximum monthly ingoing contact chain (in 2012), the average number of animals per incoming movement, use of mixed alpine pastures and the number of weeks in 2012 a farm had movements registered. The final score for the farm depended on the distribution of the parameters. Different cut offs; 50, 90, 95 and 99 %, were explored. The final scores ranged between 0 and 5. Validation of the scores against results from the BVD surveillance programme 2013 gave promising results for setting the cut off for each of the five selected farm level criteria at the 50th percentile. Restricting testing to farms with a score ≥ 2 would have resulted in the same number of detected BVD positive farms as testing all farms, i.e., the outcome of the 2013 surveillance programme could have been reached with a smaller survey.

Conclusions

The seasonality and time dependency of the activity of single farms in the networks requires a careful assessment of the actual time period included to determine farm level criteria. However, selecting farms in the sample for risk-based surveillance can be optimized with the proposed scoring system. The system was validated using data from the BVD eradication program. The proposed method is a promising framework for the selection of farms according to the risk of infection based on animal movements.