Research in big data, informatics, and bioinformatics has grown dramatically (Andreu-Perez J, et al., 2015, IEEE Journal of Biomedical and Health Informatics 19, 1193–1208). Advances in gene sequencing technologies, surveillance systems, and electronic medical records have increased the amount of health data available. Unconventional data sources such as social media, wearable sensors, and internet search engine activity have also contributed to the influx of health data. The purpose of this study was to describe how ‘big data’, ‘informatics’, and ‘bioinformatics’ have been used in the animal health and veterinary medical literature and to map and chart publications using these terms through time. A scoping review methodology was used. A literature search of the terms ‘big data’, ‘informatics’, and ‘bioinformatics’ was conducted in the context of animal health and veterinary medicine. Relevance screening on abstract and full-text was conducted sequentially. In order for articles to be relevant, they must have used the words ‘big data’, ‘informatics’, or ‘bioinformatics’ in the title or abstract and full-text and have dealt with one of the major animal species encountered in veterinary medicine. Data items collected for all relevant articles included species, geographic region, first author affiliation, and journal of publication. The study level, study type, and data sources were collected for primary studies. After relevance screening, 1093 were classified. While there was a steady increase in ‘bioinformatics’ articles between 1995 and the end of the study period, ‘informatics’ articles reached their peak in 2012, then declined. The first ‘big data’ publication in animal health and veterinary medicine was in 2012. While few articles used the term ‘big data’ (n = 14), recent growth in ‘big data’ articles was observed. All geographic regions produced publications in ‘informatics’ and ‘bioinformatics’ while only North America, Europe, Asia, and Australia/Oceania produced publications about ‘big data’. ‘Bioinformatics’ primary studies tended to use genetic data and tended to be conducted at the genetic level. In contrast, ‘informatics’ primary studies tended to use non-genetic data sources and conducted at an organismal level. The rapidly evolving definition of ‘big data’ may lead to avoidance of the term.

This editorial summarizes the key observations from a special issue of Animal Health Research Reviews comprising 14 articles related to the efficacy of antimicrobial and non-antimicrobial approaches to reduce disease in beef, dairy cattle, swine, and broiler chickens. The articles used evidence-based methods, including scoping reviews, systematic reviews, meta-analyses, and network meta-analyses. Despite finding evidence of efficacy for some of the interventions examined, across the body of research, there was a lack of replication and inconsistency in outcomes among the included trials, and concerns related to completeness of reporting and trial design and execution. There is an urgent need for more and better data to inform antimicrobial stewardship practices in animal agriculture.

Transition cow diseases can negatively impact animal welfare and reduce dairy herd profitability. Transition cow disease incidence has remained relatively stable over time despite monitoring and management efforts aimed to reduce the risk of developing diseases. Dairy cattle disease risk is monitored by assessing multiple factors, including certain biomarker test results, health records, feed intake, body condition score, and milk production. However, these factors, which are used to make herd management decisions, are often reviewed separately without considering the correlation between them. In addition, the biomarkers that are currently used for monitoring may not be representative of the complex physiological changes that occur during the transition period. Predictive modeling, which uses data to predict future or current outcomes, is a method that can be used to combine the most predictive variables and their interactions efficiently. The use of an effective predictive model with relevant predictors for transition cow diseases will result in better targeted interventions, and therefore lower disease incidence. This review will discuss predictive modeling methods and candidate variables in the context of transition cow diseases. The next step is to investigate novel biomarkers and statistical methods that are best suited for the prediction of transition cow diseases.

In this manuscript we use realistic data to conduct a network meta-analysis using a Bayesian approach to analysis. The purpose of this manuscript is to explain, in lay terms, how to interpret the output of such an analysis. Many readers are familiar with the forest plot as an approach to presenting the results of a pairwise meta-analysis. However when presented with the results of network meta-analysis, which often does not include the forest plot, the output and results can be difficult to understand. Further, one of the advantages of Bayesian network meta-analyses is in the novel outputs such as treatment rankings and the probability distributions are more commonly presented for network meta-analysis. Our goal here is to provide a tutorial for how to read the outcome of network meta-analysis rather than how to conduct or assess the risk of bias in a network meta-analysis.

The current livestock management landscape is transitioning to a high-throughput digital era where large amounts of information captured by systems of electro-optical, acoustical, mechanical, and biosensors is stored and analyzed on a daily and hourly basis, and actionable decisions are made based on quantitative and qualitative analytic results. While traditional animal breeding prediction methods have been used with great success until recently, the deluge of information starts to create a computational and storage bottleneck that could lead to negative long-term impacts on herd management strategies if not handled properly. A plethora of machine learning approaches, successfully used in various industrial and scientific applications, made their way in the mainstream approaches for livestock breeding techniques, and current results show that such methods have the potential to match or surpass the traditional approaches, while most of the time they are more scalable from a computational and storage perspective. This article provides a succinct view on what traditional and novel prediction methods are currently used in the livestock breeding field, how successful they are, and how the future of the field looks in the new digital agriculture era.

Systematic reviews and meta-analyses are used to summarize and interpret evidence for clinical decision-making in human health. The extent of the application of these methods in veterinary medicine and animal agriculture is unknown. The goal of this scoping study was to ascertain trends in the publication of systematic reviews and meta-analyses examining animal health, animal performance, and on-farm food safety. Online databases were searched for reviews published between 1993 and 2018 that focused on relevant outcomes in domestic livestock, companion animals, or wildlife species. In total 1787 titles and abstracts underwent data characterization. Dairy cattle, fish, and pigs were the most common target commodity groups. Few articles investigated both health and performance outcomes (only health: n = 418; only performance: n = 701; both health and performance: n = 103). Most of the reviews (67.6%, n = 1208/1787) described a meta-analysis but did not state in the title or abstract that a systematic review was also conducted, which is potentially problematic. Adherence to reporting guidelines is recommended for all systematic reviews and meta-analyses. For research areas with many reviews, an evidence repository is recommended. For less well-reviewed areas, additional investigation may be necessary to identify the reasons for the lack of synthesis research.

Diagnosis, treatment, and prevention of vector-borne disease (VBD) in pets is one cornerstone of companion animal practices. Veterinarians are facing new challenges associated with the emergence, reemergence, and rising incidence of VBD, including heartworm disease, Lyme disease, anaplasmosis, and ehrlichiosis. Increases in the observed prevalence of these diseases have been attributed to a multitude of factors, including diagnostic tests with improved sensitivity, expanded annual testing practices, climatologic and ecological changes enhancing vector survival and expansion, emergence or recognition of novel pathogens, and increased movement of pets as travel companions. Veterinarians have the additional responsibility of providing information about zoonotic pathogen transmission from pets, especially to vulnerable human populations: the immunocompromised, children, and the elderly. Hindering efforts to protect pets and people is the dynamic and ever-changing nature of VBD prevalence and distribution. To address this deficit in understanding, the Companion Animal Parasite Council (CAPC) began efforts to annually forecast VBD prevalence in 2011. These forecasts provide veterinarians and pet owners with expected disease prevalence in advance of potential changes. This review summarizes the fidelity of VBD forecasts and illustrates the practical use of CAPC pathogen prevalence maps and forecast data in the practice of veterinary medicine and client education.

Livestock producers are encouraged to reduce the use of antibiotics belonging to classes of medical importance to humans. We conducted a scoping review on non-antibiotic interventions in the form of products or management practices that could potentially reduce the need for antibiotics in beef and veal animals living under intensive production conditions. Our objectives were to systematically describe the research on this broad topic, identify specific topics that could feasibly support systematic reviews, and identify knowledge gaps. Multiple databases were searched. Two reviewers independently screened and charted the data. From the 13,598 articles screened, 722 relevant articles were charted. The number of relevant articles increased steadily from 1990. The Western European research was dominated by veal production studies whereas the North American research was dominated by beef production studies. The interventions and outcomes measured were diverse. The four most frequent interventions included non-antibiotic feed additives, vaccinations, breed type, and feed type. The four most frequent outcomes were indices of immunity, non-specific morbidity, respiratory disease, and mortality. There were seven topic areas evaluated in clinical trials that may share enough commonality to support systemic reviews. There was a dearth of studies in which interventions were compared to antibiotic comparison groups.

In the last several decades, avian influenza virus has caused numerous outbreaks around the world. These outbreaks pose a significant threat to the poultry industry and also to public health. When an avian influenza (AI) outbreak occurs, it is critical to make informed decisions about the potential risks, impact, and control measures. To this end, many modeling approaches have been proposed to acquire knowledge from different sources of data and perspectives to enhance decision making. Although some of these approaches have shown to be effective, they do not follow the process of knowledge discovery in databases (KDD). KDD is an iterative process, consisting of five steps, that aims at extracting unknown and useful information from the data. The present review attempts to survey AI modeling methods in the context of KDD process. We first divide the modeling techniques used in AI into two main categories: data-intensive modeling and small-data modeling. We then investigate the existing gaps in the literature and suggest several potential directions and techniques for future studies. Overall, this review provides insights into the control of AI in terms of the risk of introduction and spread of the virus.

Vaccination against putative causal organisms is a frequently used and preferred approach to controlling bovine respiratory disease complex (BRD) because it reduces the need for antibiotic use. Because approximately 90% of feedlots use and 90% of beef cattle receive vaccines in the USA, information about their comparative efficacy would be useful for selecting a vaccine. We conducted a systematic review and network meta-analysis of studies assessing the comparative efficacy of vaccines to control BRD when administered to beef cattle at or near their arrival at the feedlot. We searched MEDLINE, MEDLINE In-Process, MEDLINE Daily Epub Ahead of Print, AGRICOLA, Cambridge Agricultural and Biological Index, Science Citation Index, and Conference Proceedings Citation Index – Science and hand-searched the conference proceedings of the American Association of Bovine Practitioners and World Buiatrics Congress. We found 53 studies that reported BRD morbidity within 45 days of feedlot arrival. The largest connected network of studies, which involved 17 vaccine protocols from 14 studies, was included in the meta-analysis. Consistent with previous reviews, we found little compelling evidence that vaccines used at or near arrival at the feedlot reduce the incidence of BRD diagnosis.

Bovine viral diarrhea virus (BVDV) is an important infectious disease agent that causes significant reproductive and economic losses in the cattle industry worldwide. Although BVDV infection is known to cause poor fertility in cattle, a greater part of the underlying mechanisms particularly associated with early reproductive losses are not clearly understood. Previous studies reported viral compromise of reproductive function in infected bulls. In females, BVDV infection is thought to be capable of killing the oocyte, embryo or fetus directly, or to induce lesions that result in fetal abortion or malformation. BVDV infections may also induce immune dysfunction, and predispose cattle to other diseases that cause poor health and fertility. Other reports also suggested BVDV-induced disruption of the reproductive endocrine system, and a disruption of leukocyte and cytokine functions in the reproductive organs. More recent studies have provided evidence of viral-induced suppression of endometrial innate immunity that may predispose to uterine disease. Furthermore, there is new evidence that BVDV may potentially disrupt the maternal recognition of pregnancy or the immune protection of the conceptus. This review brings together the previous reports with the more recent findings, and attempts to explain some of the mechanisms linking this important virus to infertility in cattle.

We conducted a systematic review and network meta-analysis to determine the comparative efficacy of antibiotics used to control bovine respiratory disease (BRD) in beef cattle on feedlots. The information sources for the review were: MEDLINE®, MEDLINE In-Process and MEDLINE® Daily, AGRICOLA, Epub Ahead of Print, Cambridge Agricultural and Biological Index, Science Citation Index, Conference Proceedings Citation Index – Science, the Proceedings of the American Association of Bovine Practitioners, World Buiatrics Conference, and the United States Food and Drug Administration Freedom of Information New Animal Drug Applications summaries. The eligible population was weaned beef cattle raised in intensive systems. The interventions of interest were injectable antibiotics used at the time the cattle arrived at the feedlot. The outcome of interest was the diagnosis of BRD within 45 days of arrival at the feedlot. The network meta-analysis included data from 46 studies and 167 study arms identified in the review. The results suggest that macrolides are the most effective antibiotics for the reduction of BRD incidence. Injectable oxytetracycline effectively controlled BRD compared with no antibiotics; however, it was less effective than macrolide treatment. Because oxytetracycline is already commonly used to prevent, control, and treat BRD in groups of feedlot cattle, the use of injectable oxytetracycline for BRD control might have advantages from an antibiotic stewardship perspective.

A systematic review and network meta-analysis were conducted to assess the relative efficacy of internal or external teat sealants given at dry-off in dairy cattle. Controlled trials were eligible if they assessed the use of internal or external teat sealants, with or without concurrent antimicrobial therapy, compared to no treatment or an alternative treatment, and measured one or more of the following outcomes: incidence of intramammary infection (IMI) at calving, IMI during the first 30 days in milk (DIM), or clinical mastitis during the first 30 DIM. Risk of bias was based on the Cochrane Risk of Bias 2.0 tool with modified signaling questions. From 2280 initially identified records, 32 trials had data extracted for one or more outcomes. Network meta-analysis was conducted for IMI at calving. Use of an internal teat sealant (bismuth subnitrate) significantly reduced the risk of new IMI at calving compared to non-treated controls (RR = 0.36, 95% CI 0.25–0.72). For comparisons between antimicrobial and teat sealant groups, concerns regarding precision were seen. Synthesis of the primary research identified important challenges related to the comparability of outcomes, replication and connection of interventions, and quality of reporting of study conduct.

Use of antimicrobial approaches at drying-off for preventing new intramammary infections (IMI) during the dry period in dairy cows could be replaced by non-antimicrobial approaches. Such approaches would be of interest not only for organic but also for conventional dairy producers. The objective of the current review was to quantify the effect of non-antimicrobial internal teat sealant (ITS)-based approaches at drying-off for treating and preventing IMI, when compared with no treatment or with an antimicrobial-based approach. The protocol for this review was published before initiating the review. A total of 18 trials from 16 articles could be used to investigate the effect of an ITS-based approach. With the available results, we conclude with a high level of confidence that non-antimicrobial ITS-based dry-off approaches are efficient for preventing new IMI during the dry period when compared with no treatment, and would reduce risk of new IMI by 52%. Moreover, we are relatively confident that a bismuth subnitrate-based ITS performed better than an antimicrobial for preventing new IMI during the dry period (a risk reduction of 23%). Similarly, we are relatively confident that an ITS-based approach would only slightly or not at all reduce the prevalence of IMI at calving compared with untreated quarters.

A systematic review and network meta-analysis were conducted to assess the relative efficacy of antimicrobial therapy given to dairy cows at dry-off. Eligible studies were controlled trials assessing the use of antimicrobials compared to no treatment or an alternative treatment, and assessed one or more of the following outcomes: incidence of intramammary infection (IMI) at calving, incidence of IMI during the first 30 days in milk (DIM), or incidence of clinical mastitis during the first 30 DIM. Databases and conference proceedings were searched for relevant articles. The potential for bias was assessed using the Cochrane Risk of Bias 2.0 algorithm. From 3480 initially identified records, 45 trials had data extracted for one or more outcomes. Network meta-analysis was conducted for IMI at calving. The use of cephalosporins, cloxacillin, or penicillin with aminoglycoside significantly reduced the risk of new IMI at calving compared to non-treated controls (cephalosporins, RR = 0.37, 95% CI 0.23–0.65; cloxacillin, RR = 0.55, 95% CI 0.38–0.79; penicillin with aminoglycoside, RR = 0.42, 95% CI 0.26–0.72). Synthesis revealed challenges with a comparability of outcomes, replication of interventions, definitions of outcomes, and quality of reporting. The use of reporting guidelines, replication among interventions, and standardization of outcome definitions would increase the utility of primary research in this area.

Paratuberculosis is a worldwide infectious disease caused by Mycobacterium avium ssp. paratuberculosis (MAP). Various ruminant species can be affected by the disease, and the diagnosis of the disease is challenging in the absence of a gold standard test. The aim of this systematic review protocol is to determine the accuracy of the direct and indirect diagnostic tests for MAP infection with a special focus on sheep and goats.

A systematic review and meta-analysis were conducted to determine the efficacy of selective dry-cow antimicrobial therapy compared to blanket therapy (all quarters/all cows). Controlled trials were eligible if any of the following were assessed: incidence of clinical mastitis during the first 30 DIM, frequency of intramammary infection (IMI) at calving, or frequency of IMI during the first 30 DIM. From 3480 identified records, nine trials were data extracted for IMI at calving. There was an insufficient number of trials to conduct meta-analysis for the other outcomes. Risk of IMI at calving in selectively treated cows was higher than blanket therapy (RR = 1.34, 95% CI = 1.13, 1.16), but substantial heterogeneity was present (I2 = 58%). Subgroup analysis showed that, for trials using internal teat sealants, there was no difference in IMI risk at calving between groups, and no heterogeneity was present. For trials not using internal teat sealants, there was an increased risk in cows assigned to a selective dry-cow therapy protocol, compared to blanket treatment, with substantial heterogeneity in this subgroup. However, the small number of trials and heterogeneity in the subgroup without internal teat sealants suggests that the relative risk between treatments may differ from the determined point estimates based on other unmeasured factors.

A systematic review and network meta-analysis were conducted to assess the relative efficacy of antimicrobial therapy for clinical mastitis in lactating dairy cattle. Controlled trials in lactating dairy cattle with natural disease exposure were eligible if they compared an antimicrobial treatment to a non-treated control, placebo, or a different antimicrobial, for the treatment of clinical mastitis, and assessed clinical or bacteriologic cure. Potential for bias was assessed using a modified Cochrane Risk of Bias 2.0 tool. From 14775 initially identified records, 54 trials were assessed as eligible. Networks were established for bacteriologic cure by bacterial species group, and clinical cure. Disparate networks among bacteriologic cures precluded meta-analysis. Network meta-analysis was conducted for trials assessing clinical cure, but lack of precision of point estimates resulted in wide credibility intervals for all treatments, with no definitive conclusions regarding relative efficacy. Consideration of network geometry can inform future research to increase the utility of current and previous work. Replication of intervention arms and consideration of connection to existing networks would improve the future ability to determine relative efficacy. Challenges in the evaluation of bias in primary research stemmed from a lack of reporting. Consideration of reporting guidelines would also improve the utility of future research.

A systematic review and network meta-analysis (NMA) were conducted to address the question, ‘What is the efficacy of litter management strategies to reduce morbidity, mortality, condemnation at slaughter, or total antibiotic use in broilers?’ Eligible studies were clinical trials published in English evaluating the efficacy of litter management in broilers on morbidity, condemnations at slaughter, mortality, or total antibiotic use. Multiple databases and two conference proceedings were searched for relevant literature. After relevance screening and data extraction, there were 50 trials evaluating litter type, 22 trials evaluating litter additives, 10 trials comparing fresh to re-used litter, and six trials evaluating floor type. NMAs were conducted for mortality (61 trials) and for the presence or absence of footpad lesions (15 trials). There were no differences in mortality among the litter types, floor types, or additives. For footpad lesions, peat moss appeared beneficial compared to straw, based on a small number of comparisons. In a pairwise meta-analysis, there was no association between fresh versus used litter on the risk of mortality, although there was considerable heterogeneity among studies (I2 = 66%). There was poor reporting of key design features in many studies, and analyses rarely accounted for non-independence of observations within flocks.