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Abstract Livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) is widespread in many European countries including Denmark, where 88% of randomly selected production herds tested positive in 2016. In the present study, we investigated herd-level risk factors for farms being classified as LA-MRSA positive (study 1), in addition to herd-level risk factors for farms changing status from LA-MRSA negative to LA-MRSA positive during a 2-year period (study 2). Risk factors previously identified in other studies were confirmed in study 1: large herd size, herd type (lower risk in herds with sows) and number of pig suppliers. Due to the effect of herd type, data from sow herds (N = 41) and herds without sows (N = 166) were analysed separately. A univariable analysis found that the variables significantly associated with LA-MRSA status for sow herds were: use of wet feed in the sow units; higher weights of piglets at weaning; availability of a delivery room on the farm; cleaning of aisles after pigs were moved; number of pigs per weaner section; number of pigs purchased in the past year, and factors related to rodent control and human traffic in the herd. In herds without sows, the univariable analysis showed that the presence of other species of animal on the farm; negative pressure ventilation; full sectioning; frequent visits from the veterinarian; peroral use of tetracyclines for weaners; number of pigs purchased in the past year, and factors related to rodent control and human traffic in the herd were significantly associated with LA-MRSA status. For herds that changed from LA-MRSA negative to positive (study 2), having a company contract for mouse control, having more than one pig supplier and using group medication in the drinking water were the variables associated with LA-MRSA status in the univariable analysis. We did not succeed in building a biologically meaningful multivariable model based on any of the datasets and, as observed in similar studies, many of the risk factors identified in the univariable analysis were related to herd size. It was therefore not possible to determine whether it was the size of the herd or related factors that were the causal risk factors for being LA-MRSA positive. [ABSTRACT FROM AUTHOR]

The movements of livestock between premises and markets can be characterised as a dynamic network where the structure of the network itself can critically impact the transmission dynamics of many infectious diseases. As evidenced by the 2001 foot-and-mouth disease (FMD) epidemic in the UK, this can involve transmission over large geographical distances and can result in major economic loss. One consequence of the FMD epidemic was the introduction of mandatory livestock movement restrictions: a 13-day standstill in Scotland for cattle and sheep after moving livestock onto a farm (allowing many exemptions) and a 6-day standstill for cattle and sheep in England and Wales (with minor exemptions, e.g. direct movements to slaughter). Such standstills are known to be effective but commercial considerations result in pressures to relax them. When contemplating legislative changes such as a change in length of movement restrictions we need to consider the consequent effect these could have on the emergent properties of the system, i.e. the network structure itself. In this study, we investigate how disease dynamics change when the local contact structure of the recorded livestock movement network in Scotland is altered through rewiring movements between premises. The network rewiring used here changes the structure of the recorded trade network through a combination of altered movement restrictions and redirection of movements between holdings and markets to avoid nonsensical activity (e.g. movements to markets on days when they are inactive) while conserving other characteristics (e.g. movement date as closely as possible and market sales of the correct animal production type). Rewiring results in networks with higher clustering coefficients and lower network density. The impact of rewiring on a hypothetical foot-and-mouth disease outbreak in Scotland was assessed by stochastic simulation, considering scenarios with and without exemptions to the standstill rules. As expected, rewiring leads to a decrease in outbreak size and - if standstill exemptions are prohibited – higher probability of smaller outbreaks. Without exemptions, a shorter movement standstill is almost as effective as a longer standstill period, indicating that a simpler biosecurity system would offer minimal additional risk for FMD. These results suggest that explicitly manipulating the contact network structure in a sensible way has the potential to significantly impact disease control. [ABSTRACT FROM AUTHOR]

Bulk tank milk (BTM) samples are used to determine the infection status and estimate dairy herd prevalence for bovine leukaemia virus (BLV) using an antibody ELISA assay. BLV ELISA variability between samples from the same herd or from different herds has not been investigated over long time periods. The main objective of this study was to determine the within-herd and between-herd variability of a BTM BLV ELISA assay over 1-month, 3-month, and 3-year sampling intervals. All of the Canadian Maritime region dairy herds (n = 523) that were active in 2013 and 2016 were included (83.9% and 86.9% of total herds in 2013 and 2016, respectively). BLV antibody levels were measured in three BTM samples collected at 1-month intervals in early 2013 as well as two BTM samples collected over a 3-month interval in early 2016. Random-effects models, with fixed effects for sample replicate and province and random effects for herd, were used to estimate the variability between BTM samples from the same herd and between herds for 1-month, 3-month, and 3-year sampling intervals. The majority of variability of BTM BLV ELISA results was seen between herds (1-month, 6.792  ±  0.533; 3-month, 7.806  ±  0.652; 3-year, 6.222  ±  0.528). Unexplained variance between samples from the same herd, on square-root scale, was greatest for the 3-year (0.976  ±  0.104), followed by the 1-month (0.611  ±  0.035) then the 3-month (0.557  ±  0.071) intervals. Variability of BTM antibody levels within the same herd was present but was much smaller than the variability between herds, and was greatest for the 3-year sampling interval. The 3-month sampling interval resulted in the least variability and is appropriate to use for estimating the baseline level of within-herd prevalence for BLV control programs. Knowledge of the baseline variability and within-herd prevalence can help to determine effectiveness of control programs when BTM sampling is repeated at longer intervals. [ABSTRACT FROM AUTHOR]

This study aimed to estimate the distributions of the within-herd true prevalence (TP) and the annual clinical incidence proportion (CIp) of Mycobacterium avium subsp. paratuberculosis (MAP) infection in dairy cattle herds in Chile. Forty two commercial herds with antecedents of MAP infection were randomly selected to participate in the study. In small herds (≤30 cows), serum samples were collected from all animals present. Whereas, in larger herds, milk or serum samples were collected from all milking cows with 2 or more parities. Samples were analysed using the Pourquier® ELISA PARATUBERCULOSIS (Insitute Pourquier, France) test. Moreover, a questionnaire gathering information on management practices and the frequency of clinical cases, compatible with paratuberculosis (in the previous 12 months), was applied on the sampling date. A Bayesian latent class analysis was used to obtain TP and clinical incidence posterior distributions. The model adjusts for uncertainty in test sensitivity (serum or milk) and specificity, and prior TP & CIp estimates. A total of 4963 animals were tested, with an average contribution of 124 samples per herd. A mean apparent prevalence of 6.3% (95% confidence interval: 4.0–8.0%) was observed. Model outputs indicated an overall TP posterior distribution, across herds, with a median of 13.1% (95% posterior probability interval (PPI); 3.2–38.1%). A high TP variability was observed between herds. CIp presented a posterior median of 1.1% (95% PPI; 0.2–4.6%). Model results complement information missing from previously conducted epidemiological studies in the sector, and they could be used for further assessment of the disease impact and planning of control programs. [ABSTRACT FROM AUTHOR]

Syndromic surveillance is a well described tool used in developed countries for alerting authorities to livestock disease incursions. However, little work has been done to evaluate whether this could be a viable tool in countries where disease reporting infrastructure and resources is poor. Consequently, a syndrome-based questionnaire study in Eastern Zambia was designed to gather data on previous encounters farmers had with poultry diseases, as well as control measures they use to mitigate them. Descriptive statistics and logistic regression were used to analyse the data. Farmers reported an overall annual disease incidence in rural poultry for eastern Zambia of 31% (90% CI 29–32%). Occurrence of poultry disease in the last 12 months was associated with use of middlemen to purchase poultry products (p = 0.05, OR = 7.87), poultry products sold or given away from the farm (p = 0.01, OR = 1.92), farmers experiencing a period with more trade of poultry and its products (p = 0.04, OR = 1.70), presence of wild birds near the farm or village (p = 0.00, OR = 2.47) and poultry diseases being reported from neighbouring farms or villages (p = 0.00, OR = 3.12). The study also tentatively identified three poultry diseases (Newcastle Disease, Gumboro Disease and Fowl Pox) from the thirty-four disease syndromes provided by farmers. Farmers reported an incidence of 27% for Newcastle Disease in 2014. When compared with the state veterinary services data which reported Newcastle Disease incidence at 9% in 2014, it seems syndromic data obtained from farmers may be more sensitive in identifying disease incursion. Thirty-six remedies and strategies farmers use to treat and control these diseases were revealed. The main control strategy for identified diseases was vaccination and the main treatment was unspecified herbs, which warrants further investigation and presents an opportunity for further research in ethno-veterinary medicine. More still, this study identified chilli, Aloe Vera, garlic onion, moringa, and ash as traditional remedies that are commonly being used in Eastern Zambia, and which are also used to treat poultry diseases in Zimbabwe and Botswana. Only fourteen remedies described are conventionally accepted by veterinarians as remedies and disease control measures for poultry diseases. This study shows that syndromic data obtained from farmers is a useful disease reporting tool and could be used as an effective means of alerting authorities to disease incursion. In addition, it shows that these data may give a more accurate estimate of incidence for certain diseases than current surveillance methods and could be useful in assessing significant risk factors associated with disease occurrence. [ABSTRACT FROM AUTHOR]

Livestock diseases are a major constraint to agricultural productivity, frequently causing significant livelihood losses for farmers, and negatively affecting public food safety and security. Vaccines provide an effective and profitable means for controlling most infectious livestock diseases, but remain underutilized. This study sought to assess the barriers and determinants of vaccination utilization for priority livestock diseases in Ghana. We conducted a mixed-method study involving a quantitative survey with ruminant livestock farmers (N = 350) and seven focus group discussions (FGD) involving 65 ruminant livestock farmers. The survey data were analyzed, and distribution of barriers to vaccination access described. We evaluated the determinants of vaccination utilization (any use of vaccination against contagious-bovine-pleuropneumonia (CBPP) and peste-des-petits-ruminants (PPR) in 2021) using logistic regression analyses at the 0.05 significance level. FGD transcripts were analyzed deductively. We used triangulation to achieve convergence across the different datasets and analyses. The farmers kept an average (median) of 5 tropical livestock units (TLUs) of ruminant livestock (IQR=2.6–12.0) that were on average 8 kilometers (IQR=1.9–12.4) away from veterinary officers (VOs). Only 16% (56/350) of herds were vaccinated against the diseases. Most farmers (274/350) had limited knowledge on vaccines against CBPP and PPR infections, 63% (222/350) perceived low risk of these diseases to their herds. About half of farmers reported experiencing outbreaks of either disease in the study year (2021). Farmers scored on average 80.5 out of 98 (IQR=74–85) on the RS-14 resilience scale. After adjusting for farmers' livestock rearing experience, herd size, sex, wealth status, distance to VOs, previous disease outbreaks, and perceived risk of the diseases, vaccination utilization was negatively associated with limited knowledge (aOR=0.19, 95%CI=0.08–0.43), and positively associated with personal exposure to outbreaks in the study year (aOR=5.26, 95%CI=2.01–13.7) and increasing resilience (aOR=1.13, 95%CI=1.07–1.19). FGDs revealed farmer misconceptions about vaccines, costs of vaccines, and timely access to vaccines from VOs as additional barriers. Acceptability, affordability, accessibility, and availability of vaccine services represent the main barriers to vaccines utilization by ruminant livestock farmers in Ghana. Given that limited knowledge regarding the value of vaccination and shortfalls in veterinary service supply are of central importance for both the demand and supply side, more collaboration between the different stakeholders in a transdisciplinary manner to effectively address the low vaccination utilization problem is needed. [ABSTRACT FROM AUTHOR]

Health disorders, such as milk fever, displaced abomasum, or retained placenta, as well as poor reproductive performance, are known risk factors for culling in dairy cows. Clinical mastitis (CM) is one of the most influential culling risk factors. However the culling decision could be based either on the disease status or on the current milk yield, milk production being a significant confounder when modelling dairy cow culling risk. But milk yield (and somatic cell count) are time-varying confounders, which are also affected by prior CM and therefore lie on the causal pathway between the exposure of interest, CM, and the outcome, culling. Including these time-varying confounders could result in biased estimates. A marginal structural model (MSM) is a statistical technique allowing estimation of the causal effect of a time-varying exposure in the presence of time-varying covariates without conditioning on these covariates. The objective of this paper is to estimate the causal effect on culling of CM occurring between calving and 120 days in milk, using MSM to control for such time-varying confounders affected by previous exposure. A retrospective longitudinal study was conducted on data from dairy herds in the Province of Québec, Canada, by extracting health information events from the dairy herd health management software used by most Québec dairy producers and their veterinarians. The data were extracted for all lactations starting between January 1st and December 31st, 2010. A total of 3952 heifers and 8724 cows from 261 herds met the inclusion criteria and were used in the analysis. The estimated CM causal hazard ratios were 1.96 [1.57–2.44] and 1.47 [1.28–1.69] for heifers and cows, respectively, and as long as causal assumptions hold. Our findings confirm that CM was a risk factor for culling, but with a reduced effect compared to previous studies, which did not properly control for the presence of time-dependent confounders such as milk yield and somatic cell count. Cows experienced a lower risk for CM, with milk production having more influence on culling risk in cows than heifers. [ABSTRACT FROM AUTHOR]

Comprehensive strategies to improve on-farm antimicrobial use (AMU) are needed to contain antimicrobial resistance (AMR). Little is known about farmers’ motivating and enabling factors, and about their influence on AMU. In a cross-sectional online survey, Dutch dairy, veal and pig farmers (n = 457) reported their on-farm AMU as “Defined Daily Dose Animal” per year (DDDA F ) and completed a detailed questionnaire on their view, knowledge and behavior towards AMU and AMR. Exploratory factor analysis (EFA) on the questionnaire items identified four psychological factors labeled as ‘referent beliefs’, ‘perceived risk’, ‘knowledge’, and ‘undesired attitude to regulations’. Linear regression was done to explore the relationship between the obtained factors and on-farm AMU across the three animal sectors. Dairy farmers showed the highest factor scores for ‘knowledge’ and the lowest for ‘perceived risk’. ‘Knowledge’ scores were significantly and inversely related to AMU (P = 0.0004). Borderline significant associations with AMU were found for ‘perceived risk’ and ‘undesired attitude to regulations’ (negative and positive relationships respectively). There were no apparent differences for these relationships between the three livestock sectors. Behavioral interventions in farmers such as educational campaigns or increased support by veterinarians could empower farmers with more prudent and rational practices, eventually reducing AMU in food animals. [ABSTRACT FROM AUTHOR]

Since 2008, the Swiss veterinary service has been running a mandatory eradication program for Bovine Viral Diarrhea (BVD) that is focused on detecting and eliminating persistently infected (PI) animals. Detection was initially based on antigen testing from ear tag samples of the entire cattle population, followed by antigen testing of all newborn calves until 2012. Since then, bulk milk serology (dairy herds) and blood sample serology (beef herds) have been used for the surveillance of disease-free herds. From 2008 to 2012, the proportion of newborn PI calves decreased from 1.4% to less than 0.02%. However, this success was associated with substantial expenditures. The aim of this study was to conduct an economic evaluation of the BVD eradication program in the Swiss dairy sector. The situation before the start of the program (herd-level prevalence: 20%) served as a baseline scenario. Production models for three dairy farm types were used to estimate gross margins as well as net production losses and expenditures caused by BVD. The total economic benefit was estimated as the difference in disease costs between the baseline scenario and the implemented eradication program and was compared to the total eradication costs in a benefit-cost analysis. Data on the impact of BVD virus (BVDV) infection on animal health, fertility and production parameters were obtained empirically in a retrospective epidemiological case-control study in Swiss dairy herds and complemented by literature. Economic and additional production parameters were based on benchmarking data and published agricultural statistics. The eradication costs comprised the cumulative expenses for sampling and diagnostics. The economic model consisted of a stochastic simulation in @Risk for Excel with 20,000 iterations and was conducted for a time period of 14 years (2008–2021). The estimated annual financial losses in BVDV infected herds were CHF 85–89 per dairy cow and CHF 1337–2535 for an average farm, depending on the production type. The median net present value (NPV) was estimated at CHF 44.9 million (90% central range: CHF 13.4 million–69.4 million) and the break-even point to have been reached in 2015. Overall, the outcomes demonstrate that the Swiss BVD eradication program results in a net benefit for the dairy sector. These findings are relevant for planning similar BVD control programs in other countries. [ABSTRACT FROM AUTHOR]

Small-scale keepers are less likely to engage with production organisations and may therefore be less aware of legislation, rules and biosecurity practices which are implemented in the livestock sector. Their role in the transmission of endemic and exotic diseases is not well studied, but is believed to be important. The authors use small-scale pig keepers in Scotland as an example of how important small-scale livestock keepers might be for national biosecurity. In Scotland more than two thirds of pig producers report that they keep less than 10 pigs, meaning that biosecurity practices and pig health status on a substantial number of holdings are largely unknown; it is considered important to fill this knowledge gap. A questionnaire was designed and implemented in order to gather some of this information. The questionnaire comprised a total of 37 questions divided into seven sections (location of the enterprise, interest in pigs, details about the pig enterprise, marketing of pigs, transport of pigs, pig husbandry, and pig health/biosecurity). Over 610 questionnaires were sent through the post and the questionnaire was also available online. The questionnaire was implemented from June to October 2013 and 135 questionnaires were returned by target respondents. The responses for each question are discussed in detail in this paper. Overall, our results suggest that the level of disease identified by small-scale pig keepers is low but the majority of the small-scale pig keepers are mixed farms, with associated increased risk for disease transmission between species. Almost all respondents implemented at least one biosecurity measure, although the measures taken were not comprehensive in the majority of cases. Overall as interaction between small-scale keepers and commercial producers exists in Scotland the former can pose a risk for commercial production. This investigation fills gaps in knowledge which will allow industry stakeholders and policy makers to adapt their current disease programmes and contingency plans to the reality of small-scale pig-keeping enterprises’ health and biosecurity status. We predict that some conclusions from this work will be relevant to countries with similar pig production systems and importantly some of these findings will relate to small-scale producers in other livestock sectors. [ABSTRACT FROM AUTHOR]

The objective of this study was to use probabilistic sensitivity analysis to evaluate the cost-effectiveness of using an on-farm culture (OFC) approach to the treatment of clinical mastitis in dairy cows and compare this to a ‘standard’ treatment approach. A specific aim was to identify the herd circumstances under which an OFC approach would be most likely to be cost-effective. A stochastic Monte Carlo model was developed to simulate 5000 cases of clinical mastitis at the cow level and to calculate the associated costs simultaneously when treated according to 2 different treatment protocols; i) a 'conventional' approach (3 tubes of intramammary antibiotic) and ii) an OFC programme, whereby cows are treated according to the results of OFC. Model parameters were taken from recent peer reviewed literature on the use of OFC prior to treatment of clinical mastitis. Spearman rank correlation coefficients were used to evaluate the relationships between model input values and the estimated difference in cost between the standard and OFC treatment protocols. The simulation analyses revealed that both the difference in the bacteriological cure rate due to a delay in treatment when using OFC and the proportion of Gram-positive cases that occur on a dairy unit would have a fundamental impact on whether OFC would be cost-effective. The results of this study illustrated that an OFC approach for the treatment of clinical mastitis would probably not be cost-effective in many circumstances, in particular, not those in which Gram-positive pathogens were responsible for more than 20% of all clinical cases. The results highlight an ethical dilemma surrounding reduced use of antimicrobials for clinical mastitis since it may be associated with financial losses and poorer cow welfare in many instances. [ABSTRACT FROM AUTHOR]

Knowledge of mastitis pathogens and their predominance as well as understanding of risk factors are prerequisites to improve udder health in a herd, region or country. In Ethiopia, such information is scarce, despite the fact that mastitis is an important cattle disease in the country. A cross-sectional study that describes prevalence and causative agents of subclinical mastitis (SCM) as well as risk factors at cow and herd level was conducted on 167 dairy farms in North-West Ethiopia. On average, 33% of the quarters and 62% of the cows were California Mastitis Test (CMT) positive, but the within herd quarter level prevalence ranged between 0 and 100%. A total of 1543 milk samples, being 27 quarters that showed signs of CM, 606 CMT positive quarters and 910 CMT negative quarters were cultured, respectively 40%, 67% and 47% was positive on bacteriological culture. Coagulase negative staphylococci (CNS) (31%) followed by Staphylococcus aureus (9%) were the pathogens most frequently isolated. Based on face-to-face questionnaire data, 35 herd level and 13 cow level factors were evaluated for their association with SCM (based on CMT) and with a positive culture for any bacteria, CNS or S. aureus . Cows with a history of CM, of higher parity, >150 days in milk (DIM) and herds with owners that have >10th grade level of education had higher odds of SCM. The odds of being culture positive for any bacteria was higher in cows with ≥25% Holstein Friesian blood level (HBL), >150 DIM, housed on cemented floors, and milked by squeezing rather than stripping. Similarly, the odds of culturing CNS was higher in cows with 25–50% HBL, >150 DIM, and milked by squeezing. Staphylococcus aureus was more often found in cows with a history of CM and in larger herds. Checking the udder for mastitis, feeding cows according to their requirements and allowing calves to suckle the cows were negatively associated with SCM, with culturing any bacteria and with culturing CNS, respectively. Higher odds of SCM and of culturing CNS were found in herds owned by members of a dairy cooperative. In summary, we identified a high prevalence of SCM and intramammary infections with substantial variation between farms, and we found a number of risk factors explaining this variation. The risk factors for mastitis that were identified in this study can form the basis of an udder health control program specific for the dairy industry in North-West Ethiopia. [ABSTRACT FROM AUTHOR]

In this study associations between potential risk factors and salmonella status in Swedish dairy herds were investigated. A case-control study design was used, including existing as well as new cases. Herds were assigned a salmonella status on the basis of antibody analysis of bulk milk samples. Information on potential risk factors was collected from registry data and from farmers via a questionnaire. Univariable and multivariable logistic regression analyses were used to investigate associations between salmonella status and potential risk factors. In addition, multivariate analysis with Additive Bayesian Network (ABN) modelling was performed to improve understanding of the complex relationship between all the variables. Because of the difficulty in identifying associations between potential risk factors and infections with low prevalence and a large regional variation, exposure of potential risk factors in the high-prevalence region (Öland) were compared to exposure in other regions in Sweden. In total 483 of 996 (48%) farmers responded to the questionnaire, 69 herds had test-positive bulk milk samples. The strongest association with salmonella status was ‘presence of salmonella test-positive herds <5 km’ (OR 4.3, 95% CI 2.0–9.4). Associations with salmonella status were also seen between ‘feeding calves residue milk only’ (OR 2.4, 95% CI 1.2–4.6), ‘certified organic herds’ (OR 2.5, 95% CI 1.2–4.9) and ‘frequently seeing signs of rodents’ (OR 0.4, 95% CI 0.13-0.97). The ABN model showed associations between Öland and four of the variables: salmonella status, presence of test-positive herds <5 km, shared pastures and providing protective clothing for visitors. The latter is probably a reflection of increased disease awareness in Öland. The ABN model showed associations between herd size and housing as well as several management procedures. This provides an explanation why herd size frequently has been identified as a risk factor for salmonella by other studies. The study confirms the importance of local transmission routes for salmonella, but does not identify specific components in this local spread. Therefore, it supports the use of a broad biosecurity approach in the prevention of salmonella. In Öland, some potential risk factors are more common than in other parts of Sweden. Theoretically these could contribute to the spread of salmonella, but this was not confirmed in the present study. The study also highlights the difficulty in identifying associations between potential risk factors and infections with low prevalence and large regional variation. [ABSTRACT FROM AUTHOR]

Over the past 175 years, data related to human disease and death have progressed to a summary measure of population health, the Disability-Adjusted Life Year (DALY). As dairies have intensified there has been no equivalent measure of the impact of disease on the productive life and well-being of animals. The development of a disease-adjusted metric requires a consistent set of disability weights that reflect the relative severity of important diseases. The objective of this study was to use an international survey of dairy authorities to derive disability weights for primary disease categories recorded on dairies. National and international dairy health and management authorities were contacted through professional organizations, dairy industry publications and conferences, and industry contacts. Estimates of minimum, most likely, and maximum disability weights were derived for 12 common dairy cow diseases. Survey participants were asked to estimate the impact of each disease on overall health and milk production. Diseases were classified from 1 (minimal adverse effects) to 10 (death). The data was modelled using BetaPERT distributions to demonstrate the variation in these dynamic disease processes, and to identify the most likely aggregated disability weights for each disease classification. A single disability weight was assigned to each disease using the average of the combined medians for the minimum, most likely, and maximum severity scores. A total of 96 respondents provided estimates of disability weights. The final disability weight values resulted in the following order from least to most severe: retained placenta, diarrhea, ketosis, metritis, mastitis, milk fever, lame (hoof only), calving trauma, left displaced abomasum, pneumonia, musculoskeletal injury (leg, hip, back), and right displaced abomasum. The peaks of the probability density functions indicated that for certain disease states such as retained placenta there was a relatively narrow range of expected impact whereas other diseases elicited a wider breadth of impact. This was particularly apparent with respect to calving trauma, lameness and musculoskeletal injury, all of which could be redefined using gradients of severity or accounting for sequelae. These disability weight distributions serve as an initial step in the development of the disease-adjusted lactation (DALact) metric. They will be used to assess the time lost due to dynamic phases of dairy cow diseases and injuries. Prioritizing health interventions based on time expands the discussion of animal health to view profits and losses in light of the quality and length of life. [ABSTRACT FROM AUTHOR]

Pastoralists and agro-pastoralists often occupy remote and hostile environments, which lack infrastructure and capacity in human and veterinary healthcare and disease surveillance systems. Participatory epidemiology (PE) and Participatory Disease Surveillance (PDS) are particularly useful in situations of resource scarcity, where conventional diagnostics and surveillance data of disease prevalence may be intermittent or limited. Livestock keepers, when participating in PE studies about health issues, commonly use their local language terms, which are often syndromic and descriptive in nature. Practitioners of PE recommend confirmation of their findings with triangulation including biomedical diagnostic techniques. However, the latter is not practiced in all studies, usually due to time, financial or logistical constraints. A cross sectional study was undertaken with the Maasai of Ngorongoro District, Tanzania. It aimed to identify the terms used to describe the infectious diseases of livestock and humans with the greatest perceived impact on livelihoods. Furthermore, it aimed to characterise the usefulness and limitations of relying on local terminology when conducting PE studies in which diagnoses were not confirmed. Semi-structured interviews were held with 23 small groups, totalling 117 community members within five villages across the district. In addition, informal discussions and field observations were conducted with village elders, district veterinary and medical officers, meat inspectors and livestock field officers. For human conditions including zoonoses, several biomedical terms are now part of the common language. Conversely, livestock conditions are described using local Maasai terms, usually associated with the signs observed by the livestock keeper. Several of these descriptive, syndromic terms are used inconsistently and showed temporal and spatial variations. This study highlights the complexity and ambiguity which may exist in local terminology when used in PE studies. It emphases the need for further analysis of such findings, including laboratory diagnosis where possible to improve specificity before incorporating them into PDS or disease control interventions. [ABSTRACT FROM AUTHOR]

The planet’s mean air and ocean temperatures have been rising over the last century because of increasing greenhouse gas (GHG) emissions. These changes have substantial effects on the epidemiology of infectious diseases. We describe direct and indirect processes linking climate change and infectious diseases in livestock with reference to specific case studies. Some of the studies are used to show a positive association between temperature and expansion of the geographical ranges of arthropod vectors (e.g. Culicoides imicola , which transmits bluetongue virus) while others are used to illustrate an opposite trend (e.g. tsetse flies that transmit a range of trypanosome parasites in sub-Saharan Africa). We further describe a positive association between extreme events: droughts and El Niño/ southern oscillation (ENSO) weather patterns and Rift Valley fever outbreaks in East Africa and some adaptation practices used to mitigate the impacts of climate change that may increase risk of exposure to infectious pathogens. We conclude by outlining mitigation and adaptation measures that can be used specifically in the livestock sector to minimize the impacts of climate change-associated livestock diseases. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine practices, attitudes and experiences of UK prescribers of anthelmintics for horses and livestock. A questionnaire was sent by direct email to groups licenced to prescribe these medicines. These were veterinarians, Suitably Qualified Persons (SQPs, registered with the Animal Medicines Training Regulatory Authority) and veterinary pharmacists. The survey was also advertised through social media. It comprised questions relating to demographics, training experiences, current prescribing practices, as well as personal opinions on anthelmintic selection, diagnostics and anthelmintic resistance. A total of 193 veterinarians and 326 SQPs were included in final analysis. Pharmacists were excluded from detailed analysis due to the low numbers that responded (n = 3). The results indicated that SQP participants were more likely to receive post-certification parasitology training than the veterinarians, and that both channels consulted similar sources for information about helminths and their control (paper articles in journals, online sources). The SQP participants stated a higher frequency of face-to-face interactions with clients/customers (96.1%) than the veterinarians (76.4%), who stated a higher frequency of telephone interactions (55.1% and 73.5%, respectively). Veterinarians were more likely to state that there were specific factors that limited interactions with their clients (54.1%) than SQPs (19.6%), such as competition from other suppliers. SQP participants considered a wider range of factors as important when deciding on which anthelmintic to recommend (i.e. knowledge of specific parasites, knowledge of specific anthelmintics, discussion of measures to avoid anthelmintic resistance and time to talk with clients/customers); however, the veterinarian participants were more likely to consider the results of diagnostic tests. While discussions about anthelmintic resistance were stated with similar frequency in both groups, less frequent were specific discussions about anthelmintic sensitivity testing. In-house faecal egg count analysis was more likely to be available from those that prescribed anthelmintics for equines alone, compared to prescribers who dispensed anthelmintics for livestock alone or livestock and equines. The SQP participants indicated that they felt a large number of organisations were responsible for ensuring that anthelmintics are used responsibly, whilst veterinarian participants were more likely to place responsibility on the prescribers alone. Taken together, these findings provide an insight into how prescribers of anthelmintics in the UK interact with their clients/customers before and at the point of sale and act as a unique source of information on how best practice advice pertaining to sustainable helminth control is disseminated by the various prescribing channels. [ABSTRACT FROM AUTHOR]

Wild birds that forage around livestock facilities have been implicated as vectors of antimicrobial resistant organisms. Although antimicrobial resistant bacteria have been isolated from European starlings ( Sturnu s vulgaris ), their role in the dissemination of antimicrobial resistant elements in livestock facilities needs further investigation. To determine whether on-farm starling density and other factors were associated with the presence of cefotaxime and ciprofloxacin resistant E. coli among dairy cows in Ohio, bovine fecal pats from 150 farms were tested for the presence of cefotaxime and ciprofloxacin resistant E. coli . Each farm was visited twice (during the summer and fall of 2007–2009). Multi-level logistic regression models with a random intercept to account for fecal pats collected within a specific visit to a farm were used to assess the associations. The percentage of samples with cefotaxime and ciprofloxacin resistant E . coli was 13.4% and 13.6%, respectively. The percentage of farms having at least one sample testing positive for cefotaxime and ciprofloxacin resistant E. coli was 56.7% and 48.7%, respectively. The odds of detecting cefotaxime and ciprofloxacin resistant E. coli in the samples was significantly higher in 2007 compared to 2008 and 2009, in fall compared to summer, and from farms closer than 60 km to starling night roost sites compared to the farms further than 60 km. The presence of starlings during the day had a negative association with the likelihood of detecting cefotaxime resistant E . coli . Presence of calves also had a negative association with the likelihood of detecting both cefotaxime and ciprofloxacin resistant E. coli . European starlings might play a role in the dissemination of antimicrobial resistant agents in livestock facilities related to their daily population movements rather than the specific density of birds on farm during the day. [ABSTRACT FROM AUTHOR]

Many countries implement regionalisation as a measure to control economically important livestock diseases. Given that regionalisation highlights the difference in disease risk between animal subpopulations, this may discourage herd managers in low-risk areas from purchasing animals from high-risk areas to protect the disease-free status of their herds. Using bovine tuberculosis (bTB) in New Zealand as a case example, we develop a novel network simulation model to predict how much the frequency of cattle movements between different disease control areas (DCAs) could theoretically change if herd managers adopted the safest practices (preferentially purchasing cattle from areas with the lowest risk of bTB), if herd managers adopted the riskiest practices (preferentially purchasing cattle from areas with the greatest risk of bTB), or if herd managers made trade decisions completely at random (purchasing cattle without consideration for bTB disease risk). A modified configuration wiring algorithm was used in the network simulation model to preserve key temporal, spatial, and demographic attributes of cattle movement patterns. The simulated frequencies of cattle movements between DCAs in each of the three behavioural scenarios were compared with the actual frequency of cattle movements that occurred between 1st July 2010 and 30th June 2011. Our results showed that the observed frequency of cattle movements from high-risk areas into low-risk areas was significantly less than if trade decisions were made completely at random, but still significantly greater than if herd managers made the safest possible trade decisions. This suggests that while New Zealand cattle farmers may have adopted risk-averse trading behaviour in response to regionalisation, there are other underlying factors driving livestock trade, such as established supplier-buyer relationships and heterogeneous individual perceptions towards disease risk, which may reduce the potential efficacy of regionalisation as a disease control strategy. Physical constraints and socio-psychological factors that determine herd managers’ livestock trading behaviour warrant further studies to better understand how herd managers respond to future livestock disease regulations. The flexibility of a network re-wiring framework presented in this study allows such a behavioural response to be incorporated into a disease simulation model, which will in turn facilitate a better evaluation of disease control strategies. [ABSTRACT FROM AUTHOR]

Digital dermatitis (DD) is the most important infectious claw disease in the cattle industry causing outbreaks of lameness. The clinical course of disease can be classified using 5 clinical stages. M-stages represent not only different disease severities but also unique clinical characteristics and outcomes. Monitoring the proportions of cows per M-stage is needed to better understand and address DD and factors influencing risks of DD in a herd. Changes in the proportion of cows per M-stage over time or between groups may be attributed to differences in management, environment, or treatment and can have impact on the future claw health of the herd. Yet trends in claw health regarding DD are not intuitively noticed without statistical analysis of detailed records. Our specific aim was to develop a mobile application (app) for persons with less statistical training, experience or supporting programs that would standardize M-stage records, automate data analysis including trends of M-stages over time, the calculation of predictions and assignments of Cow Types (i.e., Cow Types I–III are assigned to cows without active lesions, single and repeated cases of active DD lesions, respectively). The predictions were the stationary distributions of transitions between DD states (i.e., M-stages or signs of chronicity) in a class-structured multi-state Markov chain population model commonly used to model endemic diseases. We hypothesized that the app can be used at different levels of record detail to discover significant trends in the prevalence of M-stages that help to make informed decisions to prevent and control DD on-farm. Four data sets were used to test the flexibility and value of the DD Check App. The app allows easy recording of M-stages in different environments and is flexible in terms of the users’ goals and the level of detail used. Results show that this tool discovers trends in M-stage proportions, predicts potential outbreaks of DD, and makes comparisons among Cow Types, signs of chronicity, scorers or pens. The DD Check App also provides a list of cows that should be treated augmented by individual Cow Types to help guide treatment and determine prognoses. Producers can be proactive instead of reactive in controlling DD in a herd by using this app. The DD Check App serves as an example of how technology makes knowledge and advice of veterinary epidemiology widely available to monitor, control and prevent this complex disease. [ABSTRACT FROM AUTHOR]

The objective of this cross-sectional study was to determine the minimal inhibitory concentrations of cephalosporins of the first (cefalonium and cefapirin) and fourth generation (cefquinome) against bacteria isolated from intramammary infections in dairy cows with elevated somatic cell counts in Germany. Additionally, possible regional differences of the minimal inhibitory concentrations within Germany should be evaluated. In total, 6936 quarter milk samples from cows with a somatic cell count >200,000 cells/ml were taken in 43 herds. The concentrations of the first generation cephalosporins inhibiting at least 90% of the isolates of a pathogen (MIC 90 ) were ≥64 μg/ml against Gram-negative bacteria and enterococci whereas the respective MIC 90 against the other Gram-positive bacteria were ≤4 μg/ml. The MIC 90 of cefquinome were ≥16 μg/ml against Gram-negative bacteria, bacilli and enterococci, and ≤2 μg/ml against the other Gram-positive bacteria. Only the minimal inhibitory concentrations against coagulase-negative staphylococci differed significantly between regions in parametric survival models with shared frailties for the herds. However, the minimal inhibitory concentrations of cefquinome against staphylococci were higher than the minimal inhibitory concentrations of the tested cephalosporins of the first generation. Therefore, cefquinome should not be the first choice to treat staphylococcal mastitis in dairy cows. [ABSTRACT FROM AUTHOR]

Several rapid tests for use on farm have been validated for the detection of hyperketonemia (HK) in dairy cattle, however the reported sensitivity and specificity of each method varies and no single study has compared them all. Meta-analysis of diagnostic test accuracy is becoming more common in human medical literature but there are few veterinary examples. The objective of this work was to perform a systematic review and meta-analysis to determine the point-of-care testing method with the highest combined sensitivity and specificity, the optimal threshold for each method, and to identify gaps in the literature. A comprehensive literature search resulted in 5196 references. After removing duplicates and performing relevance screening, 23 studies were included for the qualitative synthesis and 18 for the meta-analysis. The three index tests evaluated in the meta-analysis were: the Precision Xtra ® handheld device measuring beta-hydroxybutyrate (BHB) concentration in whole blood, and Ketostix ® and KetoTest ® semi-quantitative strips measuring the concentration of acetoacetate in urine and BHB in milk, respectively. The diagnostic accuracy of the 3 index tests relative to the reference standard measurement of BHB in serum or whole blood between 1.0–1.4 mmol/L was compared using the hierarchical summary receiver operator characteristic (HSROC) method. Subgroup analysis was conducted for each index test to examine the accuracy at different thresholds. The impact of the reference standard threshold, the reference standard method, the prevalence of HK in the population, the primary study source and risk of bias of the primary study was explored using meta-regression. The Precision Xtra ® device had the highest summary sensitivity in whole blood BHB at 1.2 mmol/L, 94.8% (CI 95% : 92.6–97.0), and specificity, 97.5% (CI 95% : 96.9–98.1). The threshold employed (1.2–1.4 mmol/L) did not impact the diagnostic accuracy of the test. The Ketostix ® and KetoTest ® strips had the highest summary sensitivity and specificity when the trace and weak positive thresholds were used, respectively. Controlling for the source of publication, HK prevalence and reference standard employed did not impact the estimated sensitivity and specificity of the tests. Including only peer-reviewed studies reduced the number of primary studies evaluating the Precision Xtra ® by 43% and Ketostix ® by 33%. Diagnosing HK with blood, urine or milk are valid options, however, the diagnostic inaccuracy of urine and milk should be considered when making economic and treatment decisions. [ABSTRACT FROM AUTHOR]

Surveillance systems are critical for accurate, timely monitoring and effective disease control. In this study, we investigated the performance of univariate process monitoring control algorithms in detecting changes in seroprevalence for endemic diseases. We also assessed the effect of sample size (number of sentinel herds tested in the surveillance system) on the performance of the algorithms. Three univariate process monitoring control algorithms were compared: Shewart p Chart 1 1 Shewart p Chart (PSHEW). (PSHEW), Cumulative Sum 2 2 Cumulative Sum (CUSUM). (CUSUM) and Exponentially Weighted Moving Average 3 3 Exponentially Weighted Moving Average (EWMA). (EWMA). Increases in seroprevalence were simulated from 0.10 to 0.15 and 0.20 over 4, 8, 24, 52 and 104 weeks. Each epidemic scenario was run with 2000 iterations. The cumulative sensitivity 4 4 Cumulative sensitivity (CumSe). (CumSe) and timeliness were used to evaluate the algorithms’ performance with a 1% false alarm rate. Using these performance evaluation criteria, it was possible to assess the accuracy and timeliness of the surveillance system working in real-time. The results showed that EWMA and PSHEW had higher CumSe (when compared with the CUSUM) from week 1 until the end of the period for all simulated scenarios. Changes in seroprevalence from 0.10 to 0.20 were more easily detected (higher CumSe) than changes from 0.10 to 0.15 for all three algorithms. Similar results were found with EWMA and PSHEW, based on the median time to detection. Changes in the seroprevalence were detected later with CUSUM, compared to EWMA and PSHEW for the different scenarios. Increasing the sample size 10 fold halved the time to detection (CumSe = 1), whereas increasing the sample size 100 fold reduced the time to detection by a factor of 6. This study investigated the performance of three univariate process monitoring control algorithms in monitoring endemic diseases. It was shown that automated systems based on these detection methods identified changes in seroprevalence at different times. Increasing the number of tested herds would lead to faster detection. However, the practical implications of increasing the sample size (such as the costs associated with the disease) should also be taken into account. [ABSTRACT FROM AUTHOR]

Be-FAST is a computer program based on a time-spatial stochastic spread mathematical model for studying the transmission of infectious livestock diseases within and between farms. The present work describes a new module integrated into Be-FAST to model the economic consequences of the spreading of classical swine fever (CSF) and other infectious livestock diseases within and between farms. CSF is financially one of the most damaging diseases in the swine industry worldwide. Specifically in Spain, the economic costs in the two last CSF epidemics (1997 and 2001) reached jointly more than 108 million euros. The present analysis suggests that severe CSF epidemics are associated with significant economic costs, approximately 80% of which are related to animal culling. Direct costs associated with control measures are strongly associated with the number of infected farms, while indirect costs are more strongly associated with epidemic duration. The economic model has been validated with economic information around the last outbreaks in Spain. These results suggest that our economic module may be useful for analysing and predicting economic consequences of livestock disease epidemics. [ABSTRACT FROM AUTHOR]

Preparedness against vector-borne threats depends on the existence of a long-term, sustainable surveillance of vector-borne disease and their relevant vectors. This work reviewed the availability of such surveillance systems in five European countries (Denmark, France, The Netherlands, Sweden and United Kingdom, part of the CoVetLab network). A qualitative assessment was then performed focusing on surveillance directed particularly to BTV-8. Information regarding surveillance activities were reviewed for the years 2008 and 2012. The results were then complemented with a critical scoping review of the literature aimed at identifying disease surveillance strategies and methods that are currently suggested as best suited to target vector-borne diseases in order to guide future development of surveillance in the countries in question. Passive surveillance was found to be efficient for early detection of diseases during the early phase of introduction into a free country. However, its value diminished once the disease has been established in a territory. Detection of emerging diseases was found to be very context and area specific, and thus active surveillance designs need to take the available epidemiological, ecological and entomological information into account. This was demonstrated by the effectiveness of the bulk milk surveillance in detecting the first case in Sweden, highlighting the need for output based standards to allow the most effective, context dependent, surveillance strategies to be used. Preparedness was of fundamental importance in determining the timeliness of detection and control in each country and that this in turn was heavily influenced by knowledge of emerging diseases in neighboring countries. Therefore it is crucial to share information on outbreaks between researchers and decision-makers and across borders continuously in order to react timely in case of an outbreak. Furthermore, timely reaction to an outbreak was heavily influenced by availability of control measures (vaccines), which is also strengthened if knowledge is shared quickly between countries. The assessment of the bluetongue surveillance in the affected countries showed that the degree of voluntary engagement varied, and that it is important to engage the public by general awareness and dissemination of results. The degree of engagement will also aid in establishing a passive surveillance system. [ABSTRACT FROM AUTHOR]

Enzootic bovine leucosis (EBL) is a transmissible disease caused by the bovine leukemia virus that is prevalent in cattle herds in many countries. Only a small fraction of infected animals develops clinical symptoms, such as malignant lymphosarcoma, after a long incubation period. In the present study, we aimed to determine the fraction of EBL-infected dairy cattle that develop lymphosarcoma and the length of the incubation period before clinical symptoms emerge. These parameters were determined by a mathematical modeling approach based on the maximum-likelihood estimation method, using the results of a nationwide serological survey of prevalence in cattle and passive surveillance records. The best-fit distribution to estimate the disease incubation period was determined to be the Weibull distribution, with a median and average incubation period of 7.0 years. The fraction of infected animals developing clinical disease was estimated to be 1.4% with a 95% confidence interval of 1.2–1.6%. The parameters estimated here contribute to an examination of efficient control strategies making quantitative evaluation available. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) threatens the effective prevention and treatment of bacterial diseases in both humans and animals. Globally, there has been much research done regarding resistant bacteria in the livestock industry, but few published resources collate this information. This report discusses a risk assessment (RA) framework and subsequent analysis of data availability for AMR in bacteria from 4 livestock sectors: dairy cattle, beef cattle, pigs and poultry, with particular reference to ESBL-producing E scherichia coli (ESBL E. coli ) prevalence in the dairy cattle sector within the United Kingdom. The aim of this assessment was to identify where quality data exist, for the purpose of parameterising a quantitative RA, and where it would be useful to direct future research to provide quality data to improve the current knowledge base. Such research is necessary to support risk modelling and forecasting capability regarding the relative contributions of factors that maintain the emergence and spread of AMR in bacteria. The review suggested that there are data gaps regarding ESBL E. coli occurrence in the following: beef cattle, bulk tank milk and dairy products, animal-by-products, the farm environment (including after flooding) as well as the effect of animal stress on shedding levels. Filling these data gaps prior to undertaking a full quantitative RA would make the assessment more robust and give greater confidence in the final outcome and consequently inform the targeting and prioritising of interventions to minimise spread of AMR in bacteria in farm animals. [ABSTRACT FROM AUTHOR]

Australia, as a relatively isolated country with a high level of agricultural production, depends on, and has the opportunity to maintain, freedom from a range of important diseases of livestock. Occasional incursions of such diseases are generally detected by ‘passive’, general surveillance (GS). In current surveillance planning, a risk-based approach has been taken to optimising allocation of resources to surveillance needs, and having mapped the relative risk of introduction and establishment of diseases of concern, a means of mapping the efficacy of GS for their detection was required, as was a means of assessing the likely efficacy of options for improving GS efficacy if needed. This paper presents the structure and application of a tool for estimating the efficacy of Australia’s GS, using the example of foot and mouth disease (FMD). The GS assessment tool (GSAT) is a stochastic spreadsheet model of the detection, diagnosis and reporting of disease on a single infected farm. It utilises the output of an intraherd disease spread model to determine the duration and prevalence of infection on different types of farm. It was applied separately to each of twelve regions of Australia, demarcated by dominant livestock production practices. Each region supplied estimates of probabilities relevant to the detection of FMD, for each of fourteen farm types and all species susceptible to the disease. Outputs of the GSAT were the average probability that FMD on the farm would be detected (single farm sensitivity), the average time elapsed from incursion of the disease to the chief veterinary officer (CVO) being notified (time to detection), and the number of average properties that would need to be infected before the CVO could be 95% confident of detecting at least one. The median single farm sensitivity for FMD varied among regions from 0.23 to 0.52, the median time to detection from 20 to 33 days, and the number of properties infected for 95% confidence of detecting at least one from 4 to 12. The GSAT has proved a valuable tool in planning surveillance for detection of exotic livestock disease in Australia, and it provides a practical example of the use of probabilistic modelling to answer important questions in the face of imperfect information. [ABSTRACT FROM AUTHOR]

The network of animal movements among livestock premises is an important topological structure for the spread of infectious diseases. The central focus of this study was to analyze strategies for selecting premises based on the friendship paradox (“your friends have more friends than you do”) – in which premises that neighbor randomly selected premises are sampled for surveillance or control – to determine whether these strategies are viable alternatives for the surveillance and control of diseases in scenarios with insufficient data on animal movement. To test the effectiveness of these strategies, we performed three sets of simulations. In the first set, we examined the risk of spreading an infectious disease using the cattle movement network of the state of Mato Grosso, Brazil. All tested strategies based on the friendship paradox have comparable performance to the hub control strategy (controlling premises that sold more animals) and superior performance to random sampling in terms of both reducing the risk of purchasing infected animals and the number of premises that need to be controlled. In the second and third sets of simulations, we observed that the friendship paradox strategies were more sensitive than the random sampling strategy to detect cases and disease, respectively. The survey of the entire animal movement network to identify animal premises with a key role in trade is not always possible, either because the data are insufficient or because informal trade is significant. If surveying the network is not possible, all approaches based on knowledge of the network become useless. As an alternative, knowing that there is a hidden movement network that follows rules inherent to all networks, such as the friendship paradox, can be used to our advantage. Strategies based on the friendship paradox do not assume knowledge of the animal movement network and therefore may be viable alternatives for the surveillance or control of infectious diseases in the absence of network information, thus optimizing the use of human and financial resources. [ABSTRACT FROM AUTHOR]

In contrast to many regions of the world where rabies is endemic in terrestrial wildlife species, wildlife rabies has been controlled in Israel by oral rabies vaccination programs, but canine rabies is re-emerging in the northern area of the Golan Heights. From 2009 to 2014 there were 208 animal rabies cases in Israel; 96 (46%) were considered introduced primary cases in dogs, triggering 112 secondary cases. One third (37/112) of the secondary cases were in cattle. Rabies vaccination is voluntary for cattle in Israel, except those on public exhibit. Rabies vaccination schedules for cattle vary based on farm practices and perception of risk. In this study 59 cattle from a dairy farm which routinely vaccinates against rabies were assigned into six groups according to age and vaccination histories. Four groups contained adult cows which had received one previous rabies vaccination, one group of adults had received two previous vaccinations, and one group was unvaccinated calves. Serum samples were collected and the cows were vaccinated with a commercial rabies vaccine. Sera were again collected 39 days later and the calf group re-vaccinated and re-sampled 18 days later. Sera were analyzed for the presence of rabies virus neutralizing antibodies using the rapid immunofluorescent antibody test. Cattle with antibody titres ≥0.5 IU/ml were considered to be protected against rabies. Twenty-six of 27 adult cattle (96%) vaccinated once at less than five months old did not have protective titres. Sixty percent (6/10) cattle vaccinated once at around six months of age did have adequate titres. Cattle previously vaccinated twice ( n = 10; 100%) with an 18 month interval between inoculations, had protective titres and protective antibody titres following booster vaccination ( n = 51; 100%). The anamnestic response of cattle to a killed rabies vaccine was not affected by the time interval between vaccinations, which ranged from 12 to 36 months. These results suggest that calves from vaccinated cows should not be vaccinated before six months old to avoid maternal antibody interference. Whilst most cattle older than six months old will be protected after a single inoculation, a second inoculation ensures a higher antibody levels for improved protection. Cattle receiving an effective priming dose responded well to a booster up to 36 months later. Such results demonstrate the effectiveness of rabies vaccination in cattle and the added value of a second dose to ensure a prolonged immune response against rabies. [ABSTRACT FROM AUTHOR]

The liver fluke Fasciola hepatica is a trematode parasite with a worldwide distribution and is the cause of important production losses in the dairy industry. The aim of this observational study was to assess the prevalence of exposure to F. hepatica in a group of high yielding dairy herds, to determine the risk factors and investigate their associations with production and fertility parameters. Bulk milk tank samples from 606 herds that supply a single retailer with liquid milk were tested with an antibody ELISA for F. hepatica . Multivariable linear regression was used to investigate the effect of farm management and environmental risk factors on F. hepatica exposure. Higher rainfall, grazing boggy pasture, presence of beef cattle on farm, access to a stream or pond and smaller herd size were associated with an increased risk of exposure. Univariable regression was used to look for associations between fluke exposure and production-related variables including milk yield, composition, somatic cell count and calving index. Although causation cannot be assumed, a significant ( p < 0.001) negative association was seen between F. hepatica exposure and estimated milk yield at the herd level, representing a 15% decrease in yield for an increase in F. hepatica exposure from the 25th to the 75th percentile. This remained significant when fertility, farm management and environmental factors were controlled for. No associations were found between F. hepatica exposure and any of the other production, disease or fertility variables. [ABSTRACT FROM AUTHOR]

In disease surveillance, capture–recapture approaches have been used to estimate the frequency of endemic diseases monitored by imperfect surveillance systems. A standard output of these techniques is an estimate of the sensitivity of the surveillance. In addition, capture–recapture applications contribute to a better understanding of the disease detection processes and of the relationships between different surveillance data sources, and help identify variables associated with the under-detection of diseases. Although capture–recapture approaches have long been used in public health, their application to livestock disease surveillance is only recent. In this paper, we review the different capture–recapture approaches applied in livestock disease surveillance, and discuss their benefits and limitations in the light of the characteristics of the surveillance and control practices used in animal health. [ABSTRACT FROM AUTHOR]

Neosporosis, caused by the intracellular protozoan Neospora caninum , is a major cause of abortion and reproductive failure in cattle worldwide. The principal route of transmission of neosporosis is via in utero infection of the offspring. There is no effective prophylactic treatment or vaccine available against bovine neosporosis. A N. caninum NcIs491 isolate was examined for its ability to immunize and reduce abortions in naturally infected dairy cows under field conditions. N. caninum -seropositive pregnant dams were inoculated with 10 8 live tachyzoites during mid-term pregnancy. A total of 520 N. caninum seropositive dams were included in this study, of these, 146 were immunized and 374 cows served as a non-vaccinated control group. A significantly lower incidence of abortion was observed in vaccinated compared to non-vaccinated cows, 16 and 26% respectively ( P = 0.01), with a vaccine efficacy of 39%. However, the number of seropositive offspring remained similar in both groups. Overall, this field trial suggests that vaccination with live N. caninum tachyzoites should be considered as an effective measure to reduce abortions caused by neosporosis in naturally infected cows. [ABSTRACT FROM AUTHOR]

We describe a method for de-identifying point location data used for disease spread modeling to allow data custodians to share data with modeling experts without disclosing individual farm identities. The approach is implemented in an open-source software program that is described and evaluated here. The program allows a data custodian to select a level of de-identification based on the K-anonymity statistic. The program converts a file of true farm locations and attributes into a file appropriate for use in disease spread modeling with the locations randomly modified to prevent re-identification based on location. Important epidemiological relationships such as clustering are preserved to as much as possible to allow modeling similar to those using true identifiable data. The software implementation was verified by visual inspection and basic descriptive spatial analysis of the output. Performance is sufficient to allow de-identification of even large data sets on desktop computers available to any data custodian. [ABSTRACT FROM AUTHOR]

In this study, we estimated the level of Foot-and-Mouth (FMD) virus infection in a cattle-dense north-western province of Islamic Republic of Iran and analyzed putative risk factors for FMD infection. Calves (6–24 months of age) from all 17 districts of West Azerbaijan were tested for antibodies against non-structural proteins (NSP-Ab) of FMD virus. A proportional stratification with a minimum of 30 epi-units was applied for 3 different husbandry systems: villages, dairy and mixed farms. Within an epi-unit, 30 calves were sampled. For the interpretation of ELISA test results, we used the 50% inhibition (50PI) cut-off as per producer's instructions and created one at 75% inhibition (75PI) based on the lowest point of the histogram of PI results. This approach resulted in three categories of outcomes; negative (N), low-positive (LP) and high-positive (HP). A generalized mixed-effect model for binary outcomes was used for analysing putative risk factors and was run for both cut-off values. A total of 8378 calves from 202 villages, 51 dairy farms and 28 mixed farms were eligible for analysis. The percentage of calves testing positive (LP + HP) was 53.7% (95% Confidence interval (CI): 52.6%–54.8%), with 39.6% (95% CI: 38.6–40.7%) testing HP ( n = 3309) while 14.1% (95% CI: 13.5–15.0%) of calves tested LP ( n = 1188). Of 281 epi-units sampled, all calves sampled tested negative in only 2 epi-units (0.7% (95% CI: 0.1–2.5%)) and more than 25 calves tested positive in 29 epi-units (10.3% (95% CI: 7.0–14.5%)). Outcomes of regression modelling using the 50 PI cut-off indicated that, for each month increase in age, the odds of testing positive increased 1.01 times (95% CI: 1.00–1.03). The odds of calves testing NSP-positive increased 1.46 times (95% CI: 1.22–1.77) for calves residing in epi-units that had experienced clinical FMD in the 12 months preceding this study. The odds of calves owned by livestock owners who traded livestock testing positive were 1.4–1.6 times higher than those owned by persons not engaged in trading while the odds for calves testing positive in dairy herds was 1.62 (95% CI: 1.10–2.35) times higher compared with calves in villages. The results of the model using the 75 PI cut-off value resulted in comparable estimates, with the age-effect becoming more evident. These results have confirmed widespread FMD infection and were used in developing a risk-based control strategy on FMD, in line with Stage 1 of the Progressive Control Pathway for FMD (PCP-FMD). [ABSTRACT FROM AUTHOR]

This study was conducted to determine the prevalence and risk factors for Cryptosporidium infection in calf neonates on dairy farms in Normandy. Fecal samples were randomly collected between July 2010 and September 2011 from 968 calves (7–21 days old) on 97 farms. Up to 10 calves were selected and sampled per farm, and feces examined for oocysts by microscopy. C. parvum oocyst shedding was scored semi-quantitatively (0–5). A questionnaire about calf-level care and management was completed, and mortality rates were obtained from the French national registration database (BDNI). Bivariable and multivariable analyses of potential risk factors for C. parvum oocyst shedding were conducted using generalized estimating equation (GEE) models (family = Binomial).Overall, 402 out of 968 calves (41.5%) were positive for oocysts, and 25.1% of animals had a shedding score >2. Seven of the 97 farms (7%) were negative for oocysts in all fecal samples. At the time of collection, 375 calves (39%) had diarrhea, and its prevalence strongly correlated with the score for C. parvum oocyst shedding ( p < 0.0001). The mortality rate at 90 days was significantly greater for calves with high combined scores of diarrhea and shedding. Factors associated with the shedding of C. parvum were the Normande breed (odds ratio = 1.49; 95% confidence interval (CI): 0.93–2.37), dispensing of colostrum using a bucket (odds ratio = 1.37; 95% CI: 1.00–1.89), treatment with halofuginone (odds ratio = 0.46; 95% CI: 0.19–1.15) and feeding with fermented milk (odds ratio = 0.32; 95% CI: 0.17–0.63). C. parvum is widespread among calves under 21 days old in dairy herds of western France. Shedding of C. parvum is associated with a high incidence of diarrhea and increased risk of mortality in young calves. This study identified some associated calf-level factors, although further investigations are necessary to determine appropriate measures that farmers and veterinary practitioners should take to reduce the prevalence of C. parvum . [ABSTRACT FROM AUTHOR]

Q fever is a zoonotic disease caused by Coxiella burnetii , a bacterial agent for which ruminants are the main reservoir. An extensive cross-sectional study to determine the seroprevalence of and associated risk factors for Q fever was performed in dairy and mixed (dairy–beef) cattle herds in Ecuador. A total of 2668 serum samples from 386 herds were analyzed using an ELISA. In addition, a questionnaire with 57 variables related to management, feeding, facilities, biosecurity and animal health was completed for every cattle farm. A Generalized Estimating Equations model was used to determine the factors associated with C. burnetii seropositivity. The true prevalence of C. burnetii seropositivity in dairy and mixed cattle from Ecuador reached 12.6% (CI 95% : 11.3–13.9%). The herd prevalence was 46.9% (181/386) (CI 95% : 41.9–51.9%), and the within herd prevalence ranged between 8% and 100% (mean: 25.0%; Q1: 12.5%, Q2: 25.0%, Q3: 37.5%). Four factors were included in the GEE model for C. burnetii seropositivity: age of the cattle (OR: 1.01; CI 95% : 1.006–1.014), feeding of calves with milk replacers (OR: 1.94; CI 95% : 1.1–3.3), bovine respiratory syncytial virus seropositivity (OR: 1.54; CI 95% : 1.1–2.3), and disinfection of the umbilical cord (OR: 0.60; CI 95% : 0.4–0.9). [ABSTRACT FROM AUTHOR]

The central United States (U.S.) has a large livestock population including cattle, swine, sheep and goats. Simulation models were developed to assess the impact of livestock herd types and vaccination on foot and mouth disease (FMD) outbreaks using the North American Animal Disease Spread Model. In this study, potential FMD virus outbreaks in the central region of the U.S. were simulated to compare different vaccination strategies to a depopulation only scenario. Based on data from the U.S. Department of Agriculture National Agricultural Statistics Service, a simulated population of 151,620 livestock operations characterized by latitude and longitude, production type, and herd size was generated. For the simulations, a single 17,000 head feedlot was selected as the initial latently infected herd in an otherwise susceptible population. Direct and indirect contact rates between herds were based on survey data of livestock producers in Kansas and Colorado. Control methods included ring vaccination around infected herds. Feedlots ≥3000 head were either the only production type that was vaccinated or were assigned the highest vaccination priority. Simulated vaccination scenarios included low and high vaccine capacity, vaccination zones of 10 km or 50 km around detected infected premises, and vaccination trigger of 10 or 100 detected infected herds. Probability of transmission following indirect contact, movement controls and contact rate parameters were considered uncertain and so were the subjects of sensitivity analysis. All vaccination scenarios decreased number of herds depopulated but not all decreased outbreak duration. Increased size of the vaccination zone during an outbreak decreased the length of the outbreak and number of herds destroyed. Increased size of the vaccination zone primarily resulted in vaccinating feedlots ≥3000 head across a larger area. Increasing the vaccination capacity had a smaller impact on the outbreak and may not be feasible if vaccine production and delivery is limited. The ability to vaccinate all the production types surrounding an infected herd did not appear as beneficial as priority vaccination of feedlot production types that have high numbers of indirect contacts. Outbreak duration, number of herds depopulated and the effectiveness of vaccination were sensitive to indirect contact transmission probability and movement restrictions. The results of this study will provide information about the impacts of disease control protocols which may be useful in choosing the optimal control methods to meet the goals of rapid effective control and eradication. [ABSTRACT FROM AUTHOR]

Mastitis is a complex disease affecting dairy cows and is considered to be the most costly disease of dairy herds. The hazard of mastitis is a function of many factors, both managerial and environmental, making its control a difficult issue to milk producers. Observational studies of clinical mastitis (CM) often generate datasets with a number of characteristics which influence the analysis of those data: the outcome of interest may be the time to occurrence of a case of mastitis, predictors may change over time (time-dependent predictors), the effects of factors may change over time (time-dependent effects), there are usually multiple hierarchical levels, and datasets may be very large. Analysis of such data often requires expansion of the data into the counting-process format – leading to larger datasets – thus complicating the analysis and requiring excessive computing time. In this study, a nested frailty Cox model with time-dependent predictors and effects was applied to Canadian Bovine Mastitis Research Network data in which 10,831 lactations of 8035 cows from 69 herds were followed through lactation until the first occurrence of CM. The model was fit to the data as a Poisson model with nested normally distributed random effects at the cow and herd levels. Risk factors associated with the hazard of CM during the lactation were identified, such as parity, calving season, herd somatic cell score, pasture access, fore-stripping, and proportion of treated cases of CM in a herd. The analysis showed that most of the predictors had a strong effect early in lactation and also demonstrated substantial variation in the baseline hazard among cows and between herds. A small simulation study for a setting similar to the real data was conducted to evaluate the Poisson maximum likelihood estimation approach with both Gaussian quadrature method and Laplace approximation. Further, the performance of the two methods was compared with the performance of a widely used estimation approach for frailty Cox models based on the penalized partial likelihood. The simulation study showed good performance for the Poisson maximum likelihood approach with Gaussian quadrature and biased variance component estimates for both the Poisson maximum likelihood with Laplace approximation and penalized partial likelihood approaches. [ABSTRACT FROM AUTHOR]

Despite cattle herds can harbor Coxiella burnetii , risk factors for C. burnetii presence in dairy cattle herds are largely unknown. Therefore, C. burnetii herd prevalence and risk factors for bulk tank milk (BTM) positivity were investigated. In this cross-sectional study, a questionnaire was filled out by the farmer and BTM from 301 farms was tested by ELISA for presence of C. burnetii antibodies and PCR for presence of C. burnetii DNA. Risk factors were identified by univariable and multivariable logistic regression analyses. Antibodies to C. burnetii were detected in 81.6% (CI: 77.2–85.9) and C. burnetii DNA in 18.8% (CI: 14.4–23.1) of the BTM samples. Herd size (OR = 1.1 per 10 cows), cleaning the bedding of the cubicles at most every other day (OR = 2.8) and purchase of cattle from at least two addresses (OR = 3.1) showed a significant and positive association with ELISA positivity and use of an automatic milking system a negative association (OR = 0.3). Risk factors for PCR positivity were purchase of cattle from at least two delivery addresses (OR = 3.2), presence of cows with ticks (OR = 2.0), use of an automatic milking system (OR = 0.2) and presence of goats or sheep on the farm (OR = 0.4). Biosecurity and general hygiene seem associated with introduction and spread of C. burnetii in dairy herds. [ABSTRACT FROM AUTHOR]

In autumn 2011, a novel species of the genus Orthobunyavirus of the Simbu serogroup was discovered close to the German/Dutch border and named Schmallenberg virus (SBV). Since then, SBV has caused a large epidemic in European livestock. Like other viruses of the Simbu serogroup, SBV is transmitted by insect vectors. Adult ruminants may show a mild transient disease, while an infection during a critical period of pregnancy can lead to severe congenital malformation, premature birth or stillbirth. The current knowledge about the virus, its diagnosis, the spread of the epidemic, the impact and the possibilities for preventing infections with SBV is described and discussed. [ABSTRACT FROM AUTHOR]

What are all the species of pathogen that affect our livestock? As 6 out of every 10 human pathogens came from animals, with a good number from livestock and pets, it seems likely that the majority that emerge in the future, and which could threaten or devastate human health, will come from animals. Only 10 years ago, the first comprehensive pathogen list was compiled for humans; we still have no equivalent for animals. Here we describe the creation of a novel pathogen database, and present outputs from the database that demonstrate its value. The ENHanCEd Infectious Diseases database (EID2) is open-access and evidence-based, and it describes the pathogens of humans and animals, their host and vector species, and also their global occurrence. The EID2 systematically collates information on pathogens into a single resource using evidence from the NCBI Taxonomy database, the NCBI Nucleotide database, the NCBI MeSH (Medical Subject Headings) library and PubMed. Information about pathogens is assigned using data-mining of meta-data and semi-automated literature searches. Here we focus on 47 mammalian and avian hosts, including humans and animals commonly used in Europe as food or kept as pets. Currently, the EID2 evidence suggests that: • Within these host species, 793 (30.5%) pathogens were bacteria species, 395 (15.2%) fungi, 705 (27.1%) helminths, 372 (14.3%) protozoa and 332 (12.8%) viruses. • The odds of pathogens being emerging compared to not emerging differed by taxonomic division, and increased when pathogens had greater numbers of host species associated with them, and were zoonotic rather than non-zoonotic. • The odds of pathogens being zoonotic compared to non-zoonotic differed by taxonomic division and also increased when associated with greater host numbers. • The pathogens affecting the greatest number of hosts included: Escherichia coli , Giardia intestinalis , Toxoplasma gondii , Anaplasma phagocytophilum , Cryptosporidium parvum , Rabies virus, Staphylococcus aureus , Neospora caninum and Echinococcus granulosus . • The pathogens of humans and domestic animal hosts are characterised by 4223 interactions between pathogen and host species, with the greatest number found in: humans, sheep/goats, cattle, small mammals, pigs, dogs and equids. • The number of pathogen species varied by European country. The odds of a pathogen being found in Europe compared to the rest of the world differed by taxonomic division, and increased if they were emerging compared to not emerging, or had a larger number of host species associated with them. [ABSTRACT FROM AUTHOR]

Theileriosis or East Coast Fever (ECF) is an important livestock disease widespread in Zambia except for some provinces such as Luapula. This freedom status has been achieved due to strict livestock movement regulations that only authorise cattle imports from commercial farms implementing strict ECF control regimens. Recent increases in both the demand and price of beef in Zambia are stimulating a policy change towards a more inclusive inter-provincial trade in live cattle. This may also encourage the introduction of breeding cattle from high production pastoral sectors such as Central Province to stimulate the beef industry in disease free low production areas such as the Luapula Province. To estimate and compare the risks linked with those potential introductions of cattle from the traditional or commercial production sectors of the Central Province, a quantitative risk assessment model was developed. This risk comparison was necessary because the traditional livestock production sector accounts for over 79% of breeding cattle trade in Central Province but is characterised by minimalistic tick-borne disease control and a higher prevalence of ECF. We estimate that should the importation of breeding cattle from Central into Luapula Province be permitted, we could expect to import ECF by the introduction of infected animals at a median rate (5th and 95th percentiles) of every 0.44 years (0.12, 2.60), from the traditional sector compared to every 3.57 years (0.37, 103.6) from the commercial sector. Infected ticks would be expected to enter every 3.46 (0.66, 43.8) years via traditional cattle imports. These risks are strongly influenced by the prevalence of infection, performance of pre-transport screening tests, and the effectiveness of pre-transport tick cleansing. This assessment is expected to provide a model for tick borne disease risk assessments in similar settings, as well as inform ECF control, cattle trade, and stock movement policies in Zambia. [ABSTRACT FROM AUTHOR]

Movement of animals from one farm to another is a potential risk and can lead to the spreading of livestock diseases. Therefore, in order to implement effective control measures, it is important to understand the movement network in a given area. Using the SANITEL data from 2005 to 2009, around 2 million cattle movements in Belgium were traced. Exploratory analysis revealed different spatial structures for the movement of different cattle types: fattening calves are mostly moved to the Antwerp region, adult cattle are moved to different parts in Belgium. Based on these differences, movement of cattle would more likely cause a spread of disease to a larger number of areas in Belgium as compared to the fattening calves. A closer inspection of the spatial and temporal patterns of cattle movement using a weighted negative binomial model, revealed a significant short-distance movement of bovine which could be an important factor contributing to the local spreading of a disease. The model however revealed hot spot areas of movement in Belgium; four areas in the Walloon region (Luxembourg, Hainaut, Namur and Liege) were found as hot spot areas while East and West Flanders are important "receivers" of movement. This implies that an introduction of a disease to these Walloon regions could result in a spread toward the East and West Flanders regions, as what happened in the case of Bluetongue BTV-8 outbreak in 2006. The temporal component in the model also revealed a linear trend and short- and long-term seasonality in the cattle movement with a peak around spring and autumn. The result of this explorative analysis enabled the identification of "hot spots" in time and space which is important in enhancing any existing monitoring and surveillance system. [ABSTRACT FROM AUTHOR]

Abstract: Lumpy skin disease (LSD) is one of the major livestock disease problems in most areas of Ethiopia. A questionnaire-based cross-sectional study was conducted from October 2011 to February 2012 in four selected districts of Afar and Tigray regions to estimate the herd-level prevalence of LSD, and to assess its associated risk factors. Herd-owners were selected based on the willingness to provide information to complete the questionnaire. A total of 393 questionnaires were collected. Out of 393 herd-owners, 173 reported having LSD in their herds, giving an estimated herd- and animal-level prevalence of (44%, 95% CI: 37–50%) and (7.4%, 95% CI: 6–8%), respectively. Herd prevalence between regions and among the districts were significantly different (χ 2 =8, P <0.01 and χ 2 =9.9, P <0.01), respectively. The risk factors of LSD occurrence were introduction of a new animal to the herd, herd size, and utilization of communal grazing and watering points. These management characteristics cannot be readily changed in the studied area, hence, disease control should rely on a greater use of effective LSD vaccines. [Copyright &y& Elsevier]

Abstract: This study presents a multi-disciplinary decision-support tool, which integrates geo-statistics, social network analysis (SNA), spatial-stochastic spread model, economic analysis and mapping/visualization capabilities for the evaluation of the sanitary and socio-economic impact of livestock diseases under diverse epidemiologic scenarios. We illustrate the applicability of this tool using foot-and-mouth disease (FMD) in Peru as an example. The approach consisted on a flexible, multistep process that may be easily adapted based on data availability. The first module (mI) uses a geo-statistical approach for the estimation (if needed) of the distribution and abundance of susceptible population (in the example here, cattle, swine, sheep, goats, and camelids) at farm-level in the region or country of interest (Peru). The second module (mII) applies SNA for evaluating the farm-to-farm contact patterns and for exploring the structure and frequency of between-farm animal movements as a proxy for potential disease introduction or spread. The third module (mIII) integrates mI–II outputs into a spatial-stochastic model that simulates within- and between-farm FMD-transmission. The economic module (mIV) connects outputs from mI–III to provide an estimate of associated direct and indirect costs. A visualization module (mV) is also implemented to graph and map the outputs of module I–IV. After 1000 simulated epidemics, the mean (95% probability interval) number of outbreaks, infected animals, epidemic duration, and direct costs were 37 (1, 1164), 2152 (1, 13, 250), 63 days (0, 442), and US$ 1.2 million (1072, 9.5 million), respectively. Spread of disease was primarily local (<4.5km), but geolocation and type of index farm strongly influenced the extent and spatial patterns of an epidemic. The approach is intended to support decisions in the last phase of the FMD eradication program in Peru, in particular to inform and support the implementation of risk-based surveillance and livestock insurance systems that may help to prevent and control potential FMD virus incursions into Peru. [Copyright &y& Elsevier]

Abstract: Rabies continues to spread through the Indonesian archipelago. During the past 20 years, several islands – including Flores, Ambon and Bali – that had historically been free of rabies have become infected. However, the Dutch East Indies (a Dutch colony that became modern Indonesia following World War II) had been infected since the 1880s. The spread of rabies is a lesson in the emergence of an infectious disease. Reports of human cases treated for rabies and livestock rabies cases from the 1880s to 1917 were compiled. The spatial and temporal distribution of these cases was analyzed using maps, spatial statistics and time-series techniques. The first confirmed case of rabies was reported in 1889 from the Batavia [Jakarta] district (although disease suspicion was reported as early as 1884). During the 1890s rabies was already commonly reported from Java and the east coast of Sumatra, and by the late 1890s, from Celebes [Sulawesi]. Between 1900 and 1916, cases were reported from other parts of Java, Sumatra and Sulawesi, and from Borneo, the Moluccas and other outlying islands. Between 1897 and 1916, a total of 8826 human cases treated for rabies were reported and between 1908 and 1917, 1033 livestock cases were reported. Most (97.5%) human cases treated were attributed to rabid dogs. Increasing numbers of reports were observed during the period. Between 1908 and 1916 the correlation between human and livestock case reports was 64.2%, and at the district level it was 75.9%. Moderate correlations (>40%) were found between human cases and livestock cases reported up to six months previously. Based on year of first report from each district, human cases were strongly clustered (Moran's autocorrelation 0.47, P =0.005). The most likely spatio-temporal cluster of reported cases of humans treated for rabies originated from the west coast of Sumatra between 1899 and 1905, and other clusters were identified in west Java (1898–1899), the district of Batavia and in east Java (1910–1911), Nusa Tengarra Barat (1912), Borneo (1914) and the east coast of Sumatra (1903–1906). Rabies was probably first introduced to the colonial capital of the Dutch Indies, Batavia [Jakarta] in the 1880s. It then spread rapidly throughout most of the archipelago during the next two to three decades because of the movement of dogs via the military forces, for trade and as pets, despite government regulations designed to control the epidemic. Such a history suggests that further emergence and reemergence of rabies in rabies-free islands will occur based on an island's location and position within the complex social, trade and transport network that represents the Indonesian archipelago. Targeted surveillance and enforcement of quarantine regulations remain critical, to prevent history repeating itself. [Copyright &y& Elsevier]

Abstract: Endemic animal diseases such as tsetse-transmitted trypanosomosis are a constant drain on the financial resources of African livestock keepers and on the productivity of their livestock. Knowing where the potential benefits of removing animal trypanosomosis are distributed geographically would provide crucial evidence for prioritising and targeting cost-effective interventions as well as a powerful tool for advocacy. To this end, a study was conducted on six tsetse-infested countries in Eastern Africa: Ethiopia, Kenya, Somalia, South Sudan, Sudan and Uganda. First, a map of cattle production systems was generated, with particular attention to the presence of draught and dairy animals. Second, herd models for each production system were developed for two scenarios: with or without trypanosomosis. The herd models were based on publications and reports on cattle productivity (fertility, mortality, yields, sales), from which the income from, and growth of cattle populations were estimated over a twenty-year period. Third, a step-wise spatial expansion model was used to estimate how cattle populations might migrate to new areas when maximum stocking rates are exceeded. Last, differences in income between the two scenarios were mapped, thus providing a measure of the maximum benefits that could be obtained from intervening against tsetse and trypanosomosis. For this information to be readily mappable, benefits were calculated per bovine and converted to US$ per square kilometre. Results indicate that the potential benefits from dealing with trypanosomosis in Eastern Africa are both very high and geographically highly variable. The estimated total maximum benefit to livestock keepers for the whole of the study area amounts to nearly US$ 2.5 billion, discounted at 10% over twenty years – an average of approximately US$ 3300 per square kilometre of tsetse-infested area – but with great regional variation from less than US$ 500 per square kilometre to well over US$ 10,000. The greatest potential benefits accrue to Ethiopia, because of its very high livestock densities and the importance of animal traction, but also to parts of Kenya and Uganda. In general, the highest benefit levels occur on the fringes of the tsetse infestations. The implications of the models’ assumptions and generalisations are discussed. [Copyright &y& Elsevier]

Abstract: Livestock disease surveillance is particularly challenging in resource-scarce settings, where disease events are often unreported. Surveillance performance is determined as much by the quantifiable biological attributes of the disease, as it is by motivations and barriers perceived by livestock keepers for disease reporting. Mixed methods designs, which integrate the collection, analysis and interpretation of qualitative and quantitative data in a single study, are increasingly used across different disciplines. These designs allow for a deeper exploration of the topic under investigation, than can be achieved by either approach alone. In this study a mixed methods design was used in order to gain a greater understanding of the factors that influence reporting of livestock diseases in Bolivia. There is a need to strengthen passive surveillance in this country, among other reasons as part of an eradication programme for Foot and Mouth Disease (FMD). Findings revealed livestock keepers in the study area were extremely unlikely to report the occurrence of livestock health events to the Official Veterinary Services (OVS). Communication outside the local community occurs more often through alternative routes and this is positively correlated with disease awareness. The main barriers to disease reporting identified were a lack of institutional credibility and the conflicting priorities of the OVS and livestock keepers. As for other animal and human diseases across the developing world, passive surveillance of livestock diseases in Bolivia should be enhanced; this is urgent in view of the current FMD eradication programme. Increasing timeliness and smallholders’ participation requires a detailed understanding of their likely actions and perceived barriers towards disease reporting. These insights are most likely to be developed through a holistic mixed methods approach of quantitative and qualitative analyses. [Copyright &y& Elsevier]

Abstract: We describe stakeholder preference modelling using a combination of new and recently developed techniques to elicit criterion weights to incorporate into a multi-criteria decision analysis framework to prioritise exotic diseases for the pig industry in Australia. Australian pig producers were requested to rank disease scenarios comprising nine criteria in an online questionnaire. Parallel coordinate plots were used to visualise stakeholder preferences, which aided identification of two diverse groups of stakeholders – one group prioritised diseases with impacts on livestock, and the other group placed more importance on diseases with zoonotic impacts. Probabilistic inversion was used to derive weights for the criteria to reflect the values of each of these groups, modelling their choice using a weighted sum value function. Validation of weights against stakeholders’ rankings for scenarios based on real diseases showed that the elicited criterion weights for the group who prioritised diseases with livestock impacts were a good reflection of their values, indicating that the producers were able to consistently infer impacts from the disease information in the scenarios presented to them. The highest weighted criteria for this group were attack rate and length of clinical disease in pigs, and market loss to the pig industry. The values of the stakeholders who prioritised zoonotic diseases were less well reflected by validation, indicating either that the criteria were inadequate to consistently describe zoonotic impacts, the weighted sum model did not describe stakeholder choice, or that preference modelling for zoonotic diseases should be undertaken separately from livestock diseases. Limitations of this study included sampling bias, as the group participating were not necessarily representative of all pig producers in Australia, and response bias within this group. The method used to elicit criterion weights in this study ensured value trade-offs between a range of potential impacts, and that the weights were implicitly related to the scale of measurement of disease criteria. Validation of the results of the criterion weights against real diseases – a step rarely used in MCDA – added scientific rigour to the process. The study demonstrated that these are useful techniques for elicitation of criterion weights for disease prioritisation by stakeholders who are not disease experts. Preference modelling for zoonotic diseases needs further characterisation in this context. [Copyright &y& Elsevier]