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Abstract A cross-sectional study of 127 dairy herds distributed across four regions of New Zealand (NZ) was conducted to estimate the regional herd-level prevalence of bovine digital dermatitis (BDD) and the prevalence of cows with BDD lesions within affected herds. Each herd was visited once during the 2016–2017 lactating season and the rear feet of all cows in the milking herd were examined to detect the presence of BDD lesions. Of the 127 herds examined, 63 had at least one cow with a detected BDD lesion. Of the 59 849 cows observed, 646 cows were observed with BDD lesions. All of the herds in which BBD was detected were located in three of the four regions (Waikato, Manawatu and South Canterbury). No convincing lesions were observed on the West Coast. The probability of BDD freedom on the West Coast was predicted to be 99.97% using a Bayesian latent class model. For the three regions where BDD lesions were observed, the true herd level and cow level prevalences were estimated using a Bayesian superpopulation approach which accounted for the imperfect diagnostic method. Based on priors obtained from previous research in another region of NZ (Taranaki), the true herd level prevalences in Waikato, Manawatu and South Canterbury were estimated to be 59.2% (95% probability interval [PI]: 44.3%–73.9%), 43.3% (95%PI: 29%–59%) and 65.9% (95%PI: 49.5%–79.9%), respectively, while the true median within-herd prevalences were estimated as 3.2% (95%PI: 2%–5%), 1.7% (95%PI: 0.9%–3.1%) and 3.7% (95%PI: 2.4%–5.5%), respectively. All of these estimates except for the true herd level prevalence in Manawatu were fairly robust to changes in the priors. For Manawatu region, changing from the prior obtained in Taranaki (the best estimate of the herd level prevalence = 60%, 95% sure > 40%) to one where the mode was 50% (95% sure < 80%) reduced the posterior from 43.3% to 35.2% (95%PI: 20.1%–53.5%). The marked variation in BDD prevalence between regions and between farms highlights the need for further exploration into risk factors for disease. [ABSTRACT FROM AUTHOR]

According to Chapter 1.4 of the World Organisation for Animal Health (WOAH) Aquatic Animal Health Code, an entire country or zone can be classified as free of a disease only if there is compelling evidence that all susceptible populations within the country or zone are free. However, the methods for achieving freedom are not prescribed in the WOAH standards and guidelines. Within this context, this paper describes a novel methodology to determine if surveillance results can be extrapolated from a study population to a target population. A framework of six criteria was developed to standardize a method for extrapolating surveillance results to other susceptible populations that have not been sampled. Criteria 1 assesses the internal validity for the freedom claim on the source population. Criteria 2 assesses which other susceptible populations have a non-negligible probability of exposure. Criteria 3 assesses whether the risk of infection upon exposure of the source population is the same or greater than each of the other susceptible populations. Finally, Criteria 4, 5 and 6 assess if the other susceptible populations would transmit the infection to the source population or if they have the same exposure pathways as the source population. We illustrate the use of this novel methodology using two hypothetical case scenarios. The presented methodology has the advantage of being applicable either retrospectively or prospectively. When applied retrospectively, it can be used to assess if the surveillance results of the source population can be extrapolated to the target population. When applied prospectively it can be used to design a more efficient surveillance system by selecting source populations from which it is easier to extrapolate surveillance results to the rest of the target population. Conclusions drawn using this methodology depend on the validity of the assumptions made when working through the methodology. We therefore recommend cautious application of the criteria and thorough review of all assumptions. [ABSTRACT FROM AUTHOR]

Since the mid-1980s, clinical inspections of aquaculture sites carried out on a regular basis by authorized veterinarians and fish health biologists (known as fish health services: FHS) have been an essential part of aquatic animal health surveillance in Norway. The aims of the present study were (1) to evaluate the performance of FHS routine clinical inspections for the detection of VHS and (2) to explore the effectiveness of risk-based prioritisation of FHS inspections for demonstrating freedom from VHS in marine salmonid sites in Norway. A stochastic simulation model was developed to estimate site sensitivity (SeS), population sensitivity (SeP), and probability of freedom (PFree). The estimation of SeS takes into consideration the probability that FHS submit samples if a site is infected, the probability that a sample is tested if submitted, the effective probability of infection in fish with clinical signs, laboratory test sensitivity, and the number of tested samples. SeP and PFree were estimated on a monthly basis over a 12 month period for six alternative surveillance scenarios and included the risk factors: region, species, area production density, and biosecurity level. Model results indicate that the current surveillance system, based on routine inspections by the FHS has a high capability for detecting VHS and that there is a high probability of freedom from VHS in Norwegian marine farmed salmonids (PFree >95%). Sensitivity analysis identified the probabilities that samples are submitted and submitted samples are tested, as the most influential input variables. The model provides a supporting tool for evaluation of potential changes in the surveillance strategy, and can be viewed as a platform for similar exotic viral infectious diseases in marine salmonid farming in Norway, if they share similar risk factors. [ABSTRACT FROM AUTHOR]

Abstract: We developed a model to calculate a quantitative risk score for individual aquaculture sites. The score indicates the risk of the site being infected with a specific fish pathogen (viral haemorrhagic septicaemia virus (VHSV); infectious haematopoietic necrosis virus, Koi herpes virus), and is intended to be used for risk ranking sites to support surveillance for demonstration of zone or member state freedom from these pathogens. The inputs to the model include a range of quantitative and qualitative estimates of risk factors organised into five risk themes (1) Live fish and egg movements; (2) Exposure via water; (3) On-site processing; (4) Short-distance mechanical transmission; (5) Distance-independent mechanical transmission. The calculated risk score for an individual aquaculture site is a value between zero and one and is intended to indicate the risk of a site relative to the risk of other sites (thereby allowing ranking). The model was applied to evaluate 76 rainbow trout farms in 3 countries (42 from England, 32 from Italy and 2 from Switzerland) with the aim to establish their risk of being infected with VHSV. Risk scores for farms in England and Italy showed great variation, clearly enabling ranking. Scores ranged from 0.002 to 0.254 (mean score 0.080) in England and 0.011 to 0.778 (mean of 0.130) for Italy, reflecting the diversity of infection status of farms in these countries. Requirements for broader application of the model are discussed. Cost efficient farm data collection is important to realise the benefits from a risk-based approach. [Copyright &y& Elsevier]

Abstract: The United States (U.S.) response to viral hemorrhagic septicemia virus (VHSV) IVb emergence in the Laurentian Great Lakes (GL) included risk-based surveillance for cost-effective decision support regarding the health of fish populations in open systems. All U.S. VHSV IVb isolations to date derive from free-ranging fish from GL States. Most originate in the region designated by US Geological Survey hydrologic unit code (HUC) 04, with the exception of two detections in neighboring Upper Mississippi (HUC 05) and Ohio (HUC 07) regions. For States outside the GL system, disease probability was assessed using multiple evidence sources. None substantiated VHSV IVb absence using surveillance alone, in part due to the limited temporal relevance of data in open systems. However, Bayesian odds risk-based analysis of surveillance and population context, coupled with exclusions where water temperatures likely preclude viral replication, achieved VHSV IVb freedom assurance for 14 non-GL States by the end of 2012, with partial evidence obtained for another 17 States. The non-GL region (defined as the aggregate of 4-digit HUCs located outside of GL States) met disease freedom targets for 2012 and is projected to maintain this status through 2016 without additional active surveillance. Projections hinge on continued basic biosecurity conditions such as movement restrictions and passive surveillance. Areas with navigable waterway connections to VHSV IVb-affected HUCs (and conducive water temperatures) should receive priority for resources in future surveillance or capacity building efforts. However, 6 years of absence of detections in non-GL States suggests that existing controls limit pathogen spread, and that even spread via natural pathways (e.g., water movement or migratory fish) appears contained to the Great Lakes system. This report exemplifies the cost-effective use of risk-based surveillance in decision support to assess and manage aquatic animal population health in open systems. [Copyright &y& Elsevier]

Abstract: Scenario tree models with temporal discounting have been applied in four continents to support claims of freedom from animal disease. Recently, a second (new) model was developed for the same population and disease. This is a natural development because surveillance is a dynamic process that needs to adapt to changing circumstances – the difficulty is the justification for, documentation of, presentation of and the acceptance of the changes. Our objective was to propose a systematic approach to present changes to an existing scenario tree model for freedom from disease. We used the example of how we adapted the deterministic Canadian Notifiable Avian Influenza scenario tree model published in 2011 to a stochastic scenario tree model where the definition of sub-populations and the estimation of probability of introduction of the pathogen were modified. We found that the standardized approach by Vanderstichel et al. (2013) with modifications provided a systematic approach to make and present changes to an existing scenario tree model. We believe that the new 2013 CanNAISS scenario tree model is a better model than the 2011 model because the 2013 model included more surveillance data. In particular, the new data on Notifiable Avian Influenza in Canada from the last 5 years were used to improve input parameters and model structure. [Copyright &y& Elsevier]

Abstract: Over recent years there have been considerable methodological developments in the field of animal disease surveillance. The principles of risk analysis were conceptually applied to surveillance in order to further develop approaches and tools (scenario tree modelling) to design risk-based surveillance (RBS) programmes. In the terrestrial animal context, examples of risk-based surveillance have demonstrated the substantial potential for cost saving, and a similar benefit is expected also for aquatic animals. RBS approaches are currently largely absent for aquatic animal diseases. A major constraint in developing RBS designs in the aquatic context is the lack of published data to assist in the design of RBS: this applies to data on (i) the relative risk of farm sites becoming infected due to the presence or absence of a given risk factor; (ii) the sensitivity of diagnostic tests (specificity is often addressed by follow-up investigation and re-testing and therefore less of a concern); (iii) data on the variability of prevalence of infection for fish within a holding unit, between holding units and at farm level. Another constraint is that some of the most basic data for planning surveillance are missing, e.g. data on farm location and animal movements. In Europe, registration or authorisation of fish farms has only recently become a requirement under EU Directive 2006/88. Additionally, the definition of the epidemiological unit (at site or area level) in the context of aquaculture is a challenge due to the often high level of connectedness (mainly via water) of aquaculture facilities with the aquatic environment. This paper provides a review of the principles, methods and examples of RBS in terrestrial, farmed and wild animals. It discusses the special challenges associated with surveillance for aquatic animal diseases (e.g. accessibility of animals for inspection and sampling, complexity of rearing systems) and provides an overview of current developments relevant for the design of RBS for fish diseases. Suggestions are provided on how the current constraints to applying RBS to fish diseases can be overcome. [Copyright &y& Elsevier]

Abstract: Spring viraemia of carp (SVC) is a disease of international importance that predominantly affects cyprinid fish and can cause significant mortality. In the United Kingdom (UK), SVC was first detected in 1977 with further cases occurring in fisheries, farms, wholesale and retail establishments throughout England and Wales (but not Scotland, where few cyprinid populations exist, nor Northern Ireland where SVC has never been detected) over the subsequent 30years. Following a control and eradication programme for the disease initiated in 2005, the UK was recognised free of the disease in 2010. This study compiles historic records of SVC cases in England and Wales with a view to understanding its routes of introduction and spread, and assessing the effectiveness of the control and eradication programme in order to improve contingency plans to prevent and control future disease incursions in the cyprinid fish sectors. Between 1977 and 2010 the presence of SVC was confirmed on 108 occasions, with 65 of the cases occurring in sport fisheries and the majority of the remainder occurring in the ornamental fish sector. The study found that throughout the history of SVC in the UK, though cases were widely distributed, their occurrence was sporadic and the virus did not become endemic. All evidence indicates that SVC was not able to persist under UK environmental conditions, suggesting that the majority of cases were a result of new introductions to the UK as opposed to within-country spread. The control and eradication programme adopted in 2005 was highly effective and two years after its implementation cases of SVC ceased. Given the non-persistent nature of the pathogen the most important aspect of the control programme focused on preventing re-introduction of the virus to the UK. Despite the effectiveness of these controls against SVC, this approach is likely to be less effective against more persistent pathogens such as koi herpesvirus, which are likely to require more stringent measures to prevent within-country spread. [Copyright &y& Elsevier]

Abstract: Expert opinions supplement empirical data in many epidemiologic assessments. For veterinary disease freedom surveillance, where the geographic scope of concern is often broad, populations subject to change, decisions eminent and empirical data, expert opinion can be a critical component of the decision making process. However, opinion is by definition subjective and the manner in which opinion is sought can impact the quality and reliability of estimates. Group interaction can hinder or improve the estimation process, depending on its facilitation. Further, whether and how validation is conducted can limit or increase acceptance of the resulting model. While the utility of expert opinion is widely recognized in many fields, and the impact of its use or misuse implicit, standards for application to veterinary assessments are not readily available. This paper aims to foster discussion on this influential component of epidemiology, with disease freedom application as a focus. Benefits and concerns attributed to expert judgment and guidelines for its structured elicitation are described, borrowing insights from its long history of use in decision science fields and examples from recent veterinary assessments. [Copyright &y& Elsevier]

Abstract: Alveolar echinococosis is caused by a parasitic tapeworm Echinococcus multilocularis and is a serious disease with high fatality in humans. The definitive primary host is the red fox (Vulpes vulpes) but domestic animals (dogs and to a lesser extent cats) as well as several genera of rodents can also be infected with the parasite. There is, to date, no evidence of indigenous cases of E. multilocularis in Great Britain (GB) but in most of continental Europe the parasite is considered to be endemic and/or slowly spreading. All pet dogs entering the United Kingdom (UK) under the pet travel scheme (PETS) are therefore currently treated with an anthelmintic effective against Echinococcus spp. Surveillance of red foxes is required to demonstrate disease freedom and maintain this regulation to prevent further geographical spread of the parasite to free areas within the EU. A study of 588 wild red foxes collected from across Great Britain (GB) between October 1999 and November 2000 found no Echinococcus spp. This report describes a further study of GB foxes collected predominately during 2005 and 2006. Fox faecal samples (n =384) were examined for both E. multilocularis and Echinococcus granulosus using an egg isolation procedure followed by PCR method, based on published primer sets. A non-specific primer set that amplifies Taenia spp. as well as Mesocestoides, Dipylidium and Diphyllobothrium was also included in the assay to validate the test procedure as these parasites are expected to be more common in wild fox populations. All faecal samples tested negative for both E. multilocularis and E. granulosus but results for approximately 35% of the samples indicated the presence of Taenia spp. or other closely related cestodes. This data contributes to the evidence that suggests that E. multilocularis is not present in mainland Britain and justifies the requirement for ongoing surveillance to demonstrate disease freedom. [Copyright &y& Elsevier]

Abstract: This manuscript was written in honour of Dr. Preben Willeberg to illustrate some tools that may be useful to “make surveillance happen” and to build bridges between science and application in animal health surveillance. The paper illustrates how four elements (science, project management, communication and documentation) may be combined with some tools into a practical framework for Foreign Animal Disease surveillance. Specifically, I will show how the four elements are essential to make surveillance happen and provide a link between science and application in animal health surveillance. The Canadian Notifiable Avian Influenza Surveillance system is used as an example. In surveillance for Foreign Animal Diseases (FAD), with veterinary authorities as the lead and with many stakeholders, project management can support science in building evidence (documentation) that can be delivered (communicated) to trade negotiators and international trade partners. To bridge the gap between science and application in FAD surveillance I propose that we need people with skills in science, project management, communication and documentation. [Copyright &y& Elsevier]

Abstract: EC Council Directive 2006/88/EC, adopted during 2008, has for the first time introduced controls for crustacean diseases to be applied across all Member States of the European Union. It lists three crustacean diseases, all of which are caused by viral pathogens and primarily associated with the production of marine penaeid shrimp: White Spot Disease (WSD) caused by the White Spot Syndrome Virus (WSSV), Yellowhead disease (YHD) caused by Yellowhead Virus (YHV) and Taura syndrome (TS) caused by Taura syndrome Virus (TSV). Under Directive 2006/88/EC, WSD is listed as ‘non-exotic’ to the EU while YHD and TS are listed as exotic. The listing of crustacean diseases in the Directive recognises the global potential for the transboundary movement of economically and ecologically significant pathogens with live animals and with aquatic animal products and in essence, aligns approaches to biosecurity of farmed and wild crustacean populations of Europe with measures in place for molluscan shellfish and for finfish. Here, we discuss the implications of Directive 2006/88/EC for European Union Member States (net importers) and for producer nations wishing to export live crustaceans and associated products into the European Union. These implications are further compared to recommendations from the World Organisation for Animal Health (OIE) for trading of live crustaceans and products arising from them. [Copyright &y& Elsevier]

Abstract: Demonstrating disease freedom is becoming important in different fields including animal disease control. Most methods consider sampling only from a homogeneous population in which each animal has the same probability of becoming infected. In this paper, we propose a new methodology to calculate the probability of detecting the disease if it is present in a heterogeneous population of small size with potentially different risk groups, differences in risk being defined using relative risks. To calculate this probability, for each possible arrangement of the infected animals in the different groups, the probability that all the animals tested are test-negative given this arrangement is multiplied by the probability that this arrangement occurs. The probability formula is developed using the assumption of a perfect test and hypergeometric sampling for finite small size populations. The methodology is applied to scrapie, a disease affecting small ruminants and characterized in sheep by a strong genetic susceptibility defining different risk groups. It illustrates that the genotypes of the tested animals influence heavily the confidence level of detecting scrapie. The results present the statistical power for substantiating disease freedom in a small heterogeneous population as a function of the design prevalence, the structure of the sample tested, the structure of the herd and the associated relative risks. [Copyright &y& Elsevier]

Abstract: The ability to combine evidence streams to establish disease freedom or prioritize surveillance is important for the evaluation of emerging diseases, such as viral hemorrhagic septicemia virus (VHSV) IVb in freshwater systems of the United States and Canada. Waterways provide a relatively unconstrained pathway for the spread of VHSV; and structured surveillance for emerging disease in open systems has many challenges. We introduce a decision framework for estimating VHSV infection probability that draws from multiple evidence streams and addresses challenges associated with the assessment of emerging disease. Using this approach, historical and risk-based evidence, whether empirical or expert-derived, supplement surveillance data to estimate disease probability. Surveillance-based estimates of VHSV prevalence were described using beta distributions. Subjective likelihood ratios (LRs), representing contextual risk, were elicited by asking experts to estimate the predicted occurrence of risk factors among VHSV-affected vs. VHSV-unaffected watersheds. We used the odds form of Bayes’ theorem to aggregate expert and surveillance evidence to predict the risk-adjusted posterior probability of VHSV-infection for given watersheds. We also used LRs representing contextual risk to quantify the time value of past surveillance data. This evidence aggregation model predicts disease probability from the combined assessment of multiple sources of information. The method also provides a flexible framework for iterative revision of disease freedom status as knowledge and data evolve. [Copyright &y& Elsevier]

Abstract: In July 2007, PRRS was detected for the first time in Sweden. A total of eight positive herds were identified and various measures were taken to eradicate the disease, including restrictions and slaughter of infected herds. Subsequently, both active and passive surveillance activities were undertaken. This study describes stochastic scenario-tree modelling of all the various surveillance system components, to estimate the current probability that Sweden is free from PRRS. The model includes all actions taken after the first positive herd was detected. The surveillance system components included in the model were as follows: investigations undertaken in association with the outbreak, a serological study based on samples collected at slaughter, samples collected in the national PRRS surveillance programme and passive clinical surveillance. The probability of freedom was estimated in time steps of 1 month, from July to December 2007. After each time step, the calculated posterior probability of freedom from the previous month, combined with the probability of introduction, was used as a prior probability for the next month. The result from the model showed a 99.8% probability that Sweden was free from PRRS at the end of December 2007. The estimated total sensitivity of the surveillance system varied between 81.2% and 94.3% and was highest during the first months after the outbreak. For sensitivity analysis purposes, the model was also applied using higher risks of introduction. However, this did not make considerable difference to the final estimates. [Copyright &y& Elsevier]

Highly pathogenic avian influenza (HPAI) is a serious disease affecting multiple organ systems and resulting in high levels of mortality in domestic poultry and may also be a serious zoonotic condition. In July-August 2020, HPAI was confirmed on 3 egg-laying chicken farms in Victoria, Australia, while a further two turkey farms and one emu farm were diagnosed with low pathogenicity viruses. All six farms were depopulated and decontaminated by 26 November 2020 and Australia declared regained freedom from HPAI on 26 February 2021. As part of the follow-up surveillance in support of claiming HPAI freedom, a scenario-tree model was developed to estimate the population sensitivity of passive surveillance for the detection of HPAI in the Victorian commercial poultry industry, and to also estimate the confidence of freedom from HPAI provided by passive surveillance, predicted over a 2-year period. Risk factors included in the model were industry sector (breeder, broiler, layer and other), flock size: small commercial (50 ≤ 5000 birds) or large commercial (> 5000 birds) and housing type (cage, barn or free-range). A detection cascade was also modelled, with probabilities allocated, to estimate the flock sensitivity for flocks in each risk stratum. System sensitivity and confidence of freedom were then estimated across all flocks in the industry. Design prevalence was set at 1, 2, 5 or 10 infected flocks and prior confidence of freedom at 0.5. Other model inputs were entered as probability distributions and the model was simulated for 10,000 iterations. Outputs were expressed as median and 95% probability intervals (PI), with the time period for analysis set at 1 month. Median system sensitivity was 0.58 (95% PI: 0.47–0.69) per time period for a single infected flock, increasing to 0.81, 0.985 and 0.9998 for 2, 5 and 10 infected flocks respectively. Median confidence of freedom was > 0.7 (95% PI: 0.65–0.76) after one time period and exceeded 0.95 and 0.99 after 4 and 7 months, respectively for one infected flock and 2 and 3 months respectively for 2 infected flocks. These results support the conclusion that passive surveillance is a highly effective tool for the detection of HPAI in commercial poultry and add further weight to evidence that HPAI has been successfully eradicated from the Victorian poultry industry and that the industry has regained HPAI free status. • Passive surveillance is effective for detecting HPAI in commercial poultry. • The Victorian commercial poultry industry is free of HPAI. • Confidence of freedom from HPAI rapidly approaches 100%. • HPAI detection relies on farmers recognising and investigating possible cases. [ABSTRACT FROM AUTHOR]

Abstract: There has been much debate about the use of the so-called “vaccinate-to-live” policy for the control of foot-and-mouth disease (FMD) in Europe, according to which, spread of the FMD virus (FMDV) from future outbreaks could be controlled by a short period of “emergency” vaccination of surrounding herds, reducing the need for large-scale pre-emptive culling of at-risk animals. Since vaccinated animals may become subclinically infected with FMDV following challenge exposure, it is necessary to either remove all vaccinates (vaccinate-to-kill) or to detect and remove vaccinates in which virus is circulating or has established persistent infections (vaccinate-to-live), in order to rapidly regain the most favoured trading status of FMD-free without vaccination. The latter approach can be supported by testing vaccinated animals for the presence of antibodies to certain non-structural proteins (NSP) of FMDV, which are induced by infection with the virus, but not by vaccination with purified FMD vaccines. Using test sensitivity and specificity data established at a recent workshop on NSP assays [Brocchi E, Bergmann I, Dekker A, Paton DJ, Sammin DJ, Greiner M, et al. Comparative performance of six ELISAs for antibodies to the non-structural proteins of foot-and-mouth disease. Vaccine, in press], this paper examines the ways in which serological testing with NSP ELISAs can be used and interpreted and the effect that this will have on the confidence with which freedom from infection can be demonstrated within guidelines specified by the World Animal Health Organisation and the European Commission. [Copyright &y& Elsevier]

Abstract: Small herds may present a problem in surveillance for infectious animal diseases because typical levels of a within-herd design prevalence are not directly applicable. We suggest a definition of small herds as those smaller than 2/(within-herd design prevalence) on the basis that such herds would be expected to have less than two (i.e. only one) infected animals. Consequently, the probability of detecting small herds cannot be improved by choosing a larger sample size within the herd. We derive necessary sample sizes of herds and the probability (“confidence”) of detecting disease within a stratum of small herds, given the among-herd design prevalence and test diagnostic sensitivity. Both a binomial model and a Poisson model can be used to establish the confidence for a given sample size of herds (and vice versa). The results of a simulation study suggest that the Poisson model provides more conservative (lower) estimates of the confidence for a given sample size and should therefore be preferred. [Copyright &y& Elsevier]

Certification that a country, region or state is “free” from a pathogen or has a prevalence less than a threshold value has implications for trade in animals and animal products. We develop a Bayesian model for assessment of (i) the probability that a country is “free” of or has an animal pathogen, (ii) the proportion of infected herds in an infected country, and (iii) the within-herd prevalence in infected herds. The model uses test results from animals sampled in a two-stage cluster sample of herds within a country. Model parameters are estimated using modern Markov-chain Monte Carlo methods. We demonstrate our approach using published data from surveys of Newcastle disease and porcine reproductive and respiratory syndrome in Switzerland, and for three simulated data sets. [Copyright &y& Elsevier]

Part of the requirements for demonstrating disease freedom usually will be that sufficient testing be done to give a specified confidence of detecting the disease if it were present at a specified level. Often, this requirement is translated into a fixed testing regime that must be followed (an inflexible approach that might not be the most economic or practical solution).A more flexible approach is to specify the capabilities of the various tests that can be used to detect the disease, and let the party hoping to demonstrate disease freedom decide upon the testing regime. The question then arises as to how to combine information that can come from a variety of sources over a period of time to give an overall level of confidence.Two methods are given. The first, an exact method based on multiplying probabilities, would be more appropriate for a survey of an area in which no disease is thought to be present. The second method (more appropriate for a herd-assurance program within an infected area) is a point-based system that takes into account the different sensitivities of the methods used to detect disease and the change in prevalence over time. It allocates points for each test done proportional to the sensitivity of the test and the prevalence at the time of testing. [Copyright &y& Elsevier]

• Existing data from multiple divergent sources can be useful in monitoring temporal trends. • Clinical syndromic surveillance should be coupled with a good intelligence network to interpret and disseminate the results. • Clinical impression survey data can be used in stochastic scenario tree models for disease freedom. The Canada West Swine Health Intelligence Network (CWSHIN) is a surveillance system imbedded in an intelligence network. It has been conducting syndromic surveillance in the four western provinces of Canada since 2012. The quarterly activities include repeated clinical impression surveys, compilation of laboratory data, discussion of trends with an expert group (practitioners, laboratory diagnosticians) and swine health reports for producers and swine practitioners. However, due to the lack of standardized population identifiers across data sources usual methods of combining data could not be applied and the collated data were not being fully utilized and analysed. Therefore in 2019, CWSHIN underwent a substantial review resulting in the "Next Generation CWSHIN". The objectives of this study were to develop and evaluate a new data merging method to combine CWSHIN's clinical impression survey and laboratory data; and to provide examples of analyses and modeling based on these data. The data for analysis were restricted to repeated clinical impression surveys (2019–2020) from veterinary practitioners and laboratory diagnostic data (2016–2020). Merging surveillance data from existing sources can be challenging. Therefore, as an alternative to merge data using a hierarchy of population identifiers, we developed a Disease Map to link surveillance data from all our data-sources. The resulting Data Repository allowed monitoring of temporal trends of syndromes, clinical diseases, and laboratory identified organisms, but it cannot provide estimates of disease occurrence. Two main reasons were the lack of denominators and using existing data on routine diagnostic tests. Therefore, discussion in the expert group (veterinary practitioners, laboratory diagnosticians, swine health experts) was critical to the system's success. Based on repeated clinical impression surveys a stochastic scenario tree model for freedom from Foot and Mouth Disease (CWSHIN Blister model) was also developed. In conclusion, the method to link existing data systems from multiple divergent sources by means of a Disease Map improved CWSHIN's veterinary syndromic surveillance. Together the Data Repository and Disease map provided flexibility to monitor temporal trends, define populations and diseases, and allow analysis. However, it is critical that the surveillance is coupled with a good intelligence network that can help interpret the results and disseminate knowledge to veterinarians and producers. [ABSTRACT FROM AUTHOR]