Cost-effectiveness of bulk-tank milk testing for surveys to demonstrate freedom from infectious bovine rhinotracheitis and bovine enzootic leucosis in Switzerland

In Switzerland, annual surveys to substantiate freedom from infectious bovine rhinotracheitis (IBR) and enzootic bovine leucosis (EBL) are implemented by a random allocation of farms to the respective survey as well as blood sampling of individual animals at farm level. Contrary to many other European countries, bulk-tank milk (BTM) samples have not been used for active cattle disease surveillance for several years in Switzerland. The aim of this project was to provide a financial comparison between the current surveillance programme consisting of blood sampling only and a modified surveillance programme including BTM sampling. A financial spreadsheet model was used for cost comparison. Various surveillance scenarios were tested with different sample sizes and sampling frequencies for BTM samples. The costs could be halved without compromising the power to substantiate the freedom from IBR and EBL through the surveillance programme. Alternatively, the sensitivity could be markedly increased when keeping the costs at the actual level and doubling the sample size. The risk-based sample size of the actual programme results in a confidence of 94,18 % that the farm level prevalence is below 0,2 %. Which the doubled sample size, the confidence is 99,69 % respectively.     

Evaluation of the antibacterial residue surveillance programme in Danish pigs using Bayesian methods

Residues of pharmacological active substances or their metabolites might be found in food products from food-producing animals. Maximum Residue Limits for pharmacological active substances in foodstuffs of animal origin are established to assure high food safety standards. Each year, more than 20,000 samples are analysed for the presence of antibacterial residues in Danish pigs. This corresponds to 0.1% of the size of the slaughter pig population and more than 1% of the sows slaughtered. In this study, a Bayesian model was used to evaluate the Danish surveillance system accuracy and to investigate the impact of a potential risk-based sampling approach to the residue surveillance programme in Danish slaughter pigs. Danish surveillance data from 2005 to 2009 and limited knowledge about true prevalence and test sensitivity and specificity were included in the model. According to the model, the true antibacterial residue prevalence in Danish pigs is very low in both sows (～0.20%) and slaughter pigs (～0.01%). Despite data constraints, the results suggest that the current screening test used in Denmark presents high sensitivity (85-99%) and very high specificity (>99%) for the most relevant antibacterial classes used in Danish pigs. If high-risk slaughter pigs could be identified by taking into account antibacterial use or meat inspection risk factors, a potential risk-based sampling approach to antibacterial residue surveillance in slaughter pigs would allow reducing the sample size substantially, while increasing or maintaining the probability of detection. Hence, the antibacterial residue surveillance programme in Danish pigs would be more cost-effective than today.     

Designing and evaluating risk-based surveillance systems: potential unwarranted effects of applying adjusted risk estimates

Risk-based surveillance systems reveal occurrence of disease or infection in a sample of population units, which are selected on the basis of risk factors for the condition under study. The purpose of such systems for supporting practical animal disease policy formulations and management decisions are: A: to detect an emerging disease or infection, if it becomes introduced into a population; or B: to substantiate freedom from a condition in a population; or C: to detect cases and estimate the prevalence of an endemic condition in a population. In risk-based surveillance these aims should be met with prudent use of resources while maintaining acceptable system performance. High-risk category units are selected for testing by identification of the presence of specific high-risk factor(s), while disregarding other factors that might also influence the risk. On this basis we argue that the most applicable risk estimate for use in designing and evaluating a risk-based surveillance system would be a crude (unadjusted) relative risk, odds ratio or apparent prevalence. Risk estimates found in the published literature, however, are often the results of multivariable analyses implicitly adjusting the estimates for confounding from other risk factors. We describe some potential unintentional effects when using adjusted risk estimates in evaluating the efficacy and sensitivity of risk-based surveillance systems (SSe). In two examples, we quantify and compare the efficacy and SSe using adjusted and crude risk estimates. The examples use Danish surveillance data from previously published studies to evaluate systems aimed at risk-based detection of new cases of an endemic infection, i.e. Salmonella in dairy cattle herds (Example 1), and for substantiating the absence of a specific infection, i.e. Trichinella in the national slaughter pig population (Example 2), respectively.     

Application of network analysis parameters in risk-based surveillance - examples based on cattle trade data and bovine infections in Sweden

Financial resources may limit the number of samples that can be collected and analysed in disease surveillance programmes. When the aim of surveillance is disease detection and identification of case herds, a risk-based approach can increase the sensitivity of the surveillance system. In this paper, the association between two network analysis measures, i.e. 'in-degree' and 'ingoing infection chain', and signs of infection is investigated. It is shown that based on regression analysis of combined data from a recent cross-sectional study for endemic viral infections and network analysis of animal movements, a positive serological result for bovine coronavirus (BCV) and bovine respiratory syncytial virus (BRSV) is significantly associated with the purchase of animals. For BCV, this association was significant also when accounting for herd size and regional cattle density, but not for BRSV. Examples are given for different approaches to include cattle movement data in risk-based surveillance by selecting herds based on network analysis measures. Results show that compared to completely random sampling these approaches increase the number of detected positives, both for BCV and BRSV in our study population. It is concluded that network measures for the relevant time period based on updated databases of animal movements can provide a simple and straight forward tool for risk-based sampling.     

Stochastic modelling as a tool for planning animal-health surveys and interpreting screening-test results

Traditionally, the planning of surveys (in particular, sample-size calculations) has relied on assumptions including the assumption of perfect screening tests. This paper presents a novel approach that can be used for planning animal-health surveys and interpreting screening-test results in the context of these surveys. A stochastic simulation model developed to assess the properties of herd-level sampling schemes and surveys has been adapted for large surveys aimed at substantiating freedom from infection at a national or regional level. We use a Bayesian approach to derive the post-survey probability of freedom from infection from the pre-survey probability of freedom and the likelihood ratio that is associated with screening-test results. We applied the model to two consecutive surveys conducted in 1998 and 1999 in Switzerland to substantiate freedom from infectious bovine rhinotracheitis (IBR) in the cattle population of about 56000 herds (median herd size of 15 cattle > 2 yr of age in 1999). In 1998, serum samples were taken from five cattle > 2 yr in 4672 herds, and in 1999 from all cattle > 2 yr old in 648 herds; samples were analysed by ELISA. The survey of 1999 provided less evidence than that of 1998 to support a status of freedom from infection; also, the characteristics of both herd-level sampling schemes were similar. We argue that the rationale for survey planning depends on the pre-survey probability of freedom from infection (i.e. our level of confidence that the infection does not occur in the targeted animal population). In consequence, surveys should be tailored to individual populations in the respective countries or regions. The model has been developed in an Excel spreadsheet to allow flexibility of use, and adaptation to many other animal-health issues.     

Animal health surveillance applications: The interaction of science and management

Animal health surveillance is an ever-evolving activity, since health- and risk-related policy and management decisions need to be backed by the best available scientific evidence and methodology. International organizations, trade partners, politicians, media and the public expect fast, understandable, up-to-date presentation and valid interpretation of animal disease data to support and document proper animal health management - in crises as well as in routine control applications. The delivery and application of surveillance information need to be further developed and optimized, and epidemiologists, risk managers, administrators and policy makers need to work together in order to secure progress. Promising new developments in areas such as risk-based surveillance, spatial presentation and analysis, and genomic epidemiology will be mentioned. Limitations and areas in need of further progress will be underlined, such as the general lack of a wide and open exchange of international animal disease surveillance data. During my more than 30 year career as a professor of Veterinary Epidemiology I had the good fortune of working in challenging environments with different eminent colleagues in different countries on a variety of animal health surveillance issues. My career change from professor to Chief Veterinary Officer (CVO) - "from science to application" - was caused by my desire to see for myself if and how well epidemiology would actually work to solve real-life problems as I had been telling my students for years that it would. Fortunately it worked for me! The job of a CVO is not that different from that of a professor of Veterinary Epidemiology; the underlying professional principles are the same. Every day I had to work from science, and base decisions and discussions on documented evidence - although sometimes the evidence was incomplete or data were simply lacking. A basic understanding of surveillance methodology is very useful for a CVO, since it provides a sound working platform not only for dealing with immediate questions when new or emerging disease situations arise, but also for more long-term activities, such as policy development, contingency planning and trade negotiations. Animal health issues, which emerged during my eight years as a CVO in Denmark from 1999 to 2007, will be used as examples, including BSE, FMD, HPAI and Trichinella testing. Emphasis will be placed on how science-based surveillance methodology and tools were developed, applied and documented.     

Evaluation and optimization of surveillance systems for rare and emerging infectious diseases

Surveillance for rare and emerging infectious diseases poses a special challenge to veterinary services. Most emerging infectious diseases like bovine tuberculosis (bTB) are zoonoses, affecting both human and animal populations. Despite the low prevalence of such an emerging infectious disease at time of incursion, the surveillance system should be able to detect the presence of the disease as early as possible. Because passive surveillance is a relatively cost-effective and therefore commonly used process, it is the basic tool for infectious disease surveillance. Because of under-reporting in passive surveillance, cost-intensive active surveillance is often required to increase the sensitivity of the surveillance system. Using scenario tree modelling, the sensitivity of passive and active surveillance system components (SSC) can be quantified and an optimal, cost-effective surveillance system developed considering the contributions of each SSC. We illustrate this approach with the example of bTB surveillance in Switzerland where the surveillance system for bTB consists of meat inspection at the slaughterhouse (SLI), passive clinical surveillance on farm (CLIN) and human surveillance (HS). While the sensitivities for CLIN and HS were both negligible (<1%), SLI was assessed to be 55.6%. The scenario tree model showed that SLI is increasable up to 80.4% when the disease awareness of meat inspectors in Switzerland is enhanced. A hypothetical random survey (RS) was also compared with a targeted survey (TS) in high-risk strata of the cattle population, and the sensitivity of TS was 1.17-fold better than in RS but with 50% of the sample size.     

Towards a risk-based surveillance for Trichinella spp. in Danish pig production

Increasing demands for cost-effectiveness in surveillance for human health hazards from animal origins can be met by introducing risk-based principles. This e.g. implies targeting subpopulations with higher risk of infection compared to the whole population. Furthermore, historical data from surveillance can be collated and used to assess future risk of infection. To demonstrate the effectiveness of combining these two approaches, we used a model called “Discounting historical evidence”. It depends mainly on the annual risk of introduction (PIntro) and the surveillance system sensitivity (SSe) (ability to detect infection if present). The model implies simulations that reiterate for a number of years. For each year the output is updated with the confidence on absence in infection. Trichinella spiralis infection in pigs is used as an example. In Denmark, more than 20 million pigs are tested annually. Despite more than 70 years of testing no pigs have been found positive for Trichinella. Hence, PIntro is low. SSe can be estimated from the maximum number of infected carcasses expected under the specified design prevalence, and the sensitivity of the test applied. According to our assessment, the current prevalence of Trichinella in Danish pigs is less than one case per million, which we interpret as negligible risk. Based on this, a risk-based surveillance programme for Trichinella is designed that targets all out-door reared pigs as well as all sows and boars (current total 610,000 slaughtered annually). These subpopulations are judged to have higher risk of getting Trichinella. Again, SSe and PIntro are estimated and the model results show that risk-based surveillance can be applied without jeopardizing human health. Finally, we incorporate wildlife surveys and test quality assurance in the programme. The results of the simulation model were included in an application to the European Commission concerning Denmark's status as a region with negligible risk of Trichinella. In July 2007, the European Commission granted status as “negligible risk” to Danish pigs and pork.     

Towards incorporating spatial risk analysis for Salmonella sero-positivity into the Danish swine surveillance programme

An increased incidence of pork-related human salmonellosis in Denmark led to the development of a national control programme for Salmonella in Danish swine herds in 1993. The aim of the programme has been met and now the issue of cost-effectiveness is receiving greater attention. An appropriate way to address this is to bring a risk-based focus to the programme.

We describe a practical approach to risk-based surveillance through spatial risk assessment using serological and questionnaire data from 2280 herds in 1995. A mixed effects logistic regression model was fitted and both first- and second-order spatial properties of the random effects were investigated. We identified wet-feeding (OR: 0.64; 95% CI: 0.54–0.75) and SPF health status (OR: 0.65; 95% CI: 0.52–0.81) as protective factors for Salmonella sero-positivity. Purchasing feed (OR: 1.81; 95% CI: 1.61–2.04) was a risk factor. The west of the study area generally, and the north of Jutland in particular, experienced the greatest disease risk after controlling for the covariates. There was some evidence for spatial dependency between farms at distances of 6 km (95% CI: 2–35 km) on the Jutland peninsula.

We conclude that when farm location details are analysed in conjunction with routinely recorded surveillance information (such as that collected by the Danish swine Salmonella control programme) and targeted industry surveys (such as those conducted by slaughterhouse co-operatives), our knowledge of the behaviour of disease in animal populations is enhanced and this provides a more informed framework for designing efficient, risk-based surveillance strategies.     

An assessment of external biosecurity on southern Ontario swine farms and its application to surveillance on a geographic level

Risk-based surveillance is becoming increasingly important in the veterinary and public health fields. It serves as a means of increasing surveillance sensitivity and improving cost-effectiveness in an increasingly resource-limited environment. Our approach for developing a tool for the risk-based geographical surveillance of contagious diseases of swine incorporates information about animal density and external biosecurity practices within swine herds in southern Ontario. The objectives of this study were to group the sample of herds into discrete biosecurity groups, to develop a map of southern Ontario that can be used as a tool in the risk-based geographical surveillance of contagious swine diseases, and to identify significant predictors of biosecurity group membership. A subset of external biosecurity variables was selected for 2-step cluster analysis and latent class analysis (LCA). It was determined that 4 was the best number of groups to describe the data, using both analytical approaches. The authors named these groups: i) high biosecurity herds that were open with respect to replacement animals; ii) high biosecurity herds that were closed with respect to replacement animals; iii) moderate biosecurity herds; and iv) low biosecurity herds. The risk map was developed using information about the geographic distribution of herds in the biosecurity groups, as well as the density of swine sites and of grower-finisher pigs in the study region. Finally, multinomial logistic regression identified heat production units (HPUs), number of incoming pig shipments per month, and herd type as significant predictors of biosecurity group membership. It was concluded that the ability to identify areas of high and low risk for disease may improve the success of surveillance and eradication projects.     

Modelling the effect of surveillance programmes on spread of bovine herpesvirus 1 between certified cattle herds

For the eradication of an infectious agent, like bovine herpesvirus 1 (BHV-1), surveillance and certification can be used to reduce the transmission between herds. The goal of surveillance is that a certified herd that becomes infected is detected timely so that infection of several other certified herds is prevented. What counts is whether the reproduction ratio R, i.e. the average number of certified herds infected by one infected certified herd can be kept below 1. To support policy makers in making decisions about the minimal demands for a surveillance programme in an eradication campaign of BHV-1 in cattle, two mathematical models were investigated. With these models, the basic reproduction ratio between herds was calculated. The surveillance programmes were characterised with sample size, sampling frequency, test sensitivity, herd size, vaccination status, and contacts between herds. When R between herds is below 1, then the surveillance programme is sufficiently good to prevent spread of infection, provided that R is estimated well. In the model based on bulk milk testing sample size was replaced by a threshold at which bulk milk can be found positive. The R between herds was mainly influenced by the vaccination status, sampling frequency, and contacts between herds. Herd size moderately affected the outcome. Test sensitivity and sample size, however, were of minor importance. If herds of 50 cows became free of BHV-1 without vaccination, then spread of infection between herds might be prevented when animals within herds are sampled once a year (milk or blood samples). This frequency needs to be intensified, being twice a year, for larger herds and/or herds with extensive contacts with other herds. When bulk milk is sampled instead, sampling should be done at least every 5 months and more intensively, being each month, with larger herd sizes and more contacts between herds.     

Demonstrating freedom from disease using multiple complex data sources 1: a new methodology based on scenario trees

Current methods to demonstrate zone or country freedom from disease are based on either quantitative analysis of the results of structured representative surveys, or qualitative assessments of multiple sources of evidence (including complex non-representative sources). This paper presents a methodology for objective quantitative analysis of multiple complex data sources to support claims of freedom from disease. Stochastic scenario tree models are used to describe each component of a surveillance system (SSC), and used to estimate the sensitivity of each SSC. The process of building and analysing the models is described, as well as techniques to take into account any lack of independence between units at different levels within a SSC. The combination of sensitivity estimates from multiple SSCs into a single estimate for the entire surveillance system is also considered, again taking into account lack of independence between components. A sensitivity ratio is used to compare different components of a surveillance system. Finally, calculation of the probability of country freedom from the estimated sensitivity of the surveillance system is illustrated, incorporating the use and valuation of historical surveillance evidence.     

Implementing a probabilistic definition of freedom from infection to facilitate trade of livestock: putting theory into praxis for the example of bovine herpes virus-1

International trade of livestock and livestock products poses a significant potential threat for spread of diseases, and importing countries therefore often require that imported animals and products are free from certain pathogens. However, absolute freedom from infection cannot be documented, since all test protocols are imperfect and can lead to false-negative results. It is possible instead to estimate the "probability of freedom from infection" and its opposite, the probability of infection despite having a negative test result. These probabilities can be estimated based on a pre-defined target prevalence, known surveillance efforts in the target population and known test characteristics of any pre-export test. Here, calculations are demonstrated using the example of bovine herpes virus-1 (BoHV-1). In a population that recently became free of BoHV-1 without using vaccination, the probability of being infected of an animal randomly selected for trade is 800 per 1 million and this probability is reduced to 64 (95% probability interval PI 6-161) per 1 million when this animal is tested negatively prior to export with a gB-ELISA. In a population that recently became free of BoHV-1 using vaccination, the probability of being infected of an animal randomly selected for trade is 200 per 1 million, and this probability can be reduced to 63 (95% PI 42-87) when this animal is tested negatively prior to export with a gE-ELISA. Similar estimations can be made on a herd level when assumptions are made about the herd size and the intensity of the surveillance efforts. Subsequently, the overall probability for an importing country of importing at least 1 infected animal can be assessed by taking into account the trade volume. Definition of the acceptable level of risk, including the probability of false-negative results to occur, is part of risk management. Internationally harmonized target prevalence levels for the declaration of freedom from infection from selected pathogens provide a significant contribution to the facilitation of international trade of livestock and livestock products by allowing exporting countries to design tailor-made output-based surveillance programs, while providing equivalent guarantees regarding the probability of freedom from infection of the population. Combining this with an approach to assess the overall probability of introducing at least 1 infected animal into an importing country during a defined time interval will help importing countries to achieve their desired level of acceptable risk and will help to assess the equivalence of animal health and food safety standards between trading partners.     

Analysis of sampling strategies to substantiate freedom from disease in large areas

In this paper, we deal with the strategies of surveys to substantiate freedom from disease for a certain territory. Infection might not be distributed homogeneously. So, a relatively high within-herd prevalence might be observed while the herd-level prevalence is lower. For this situation, we compare various two-stage sample strategies.

The calculation of appropriate sample sizes becomes quite complicated. The theoretical generalization of the hypergeometric distribution by Cameron and Baldock [Prev. Vet. Med. 24 (1998) 1] introduces a simple way to evaluate multi-stage sample sizes while regarding real-test properties. We demonstrate the theoretical foundations of these calculations. These principles open up the possibility of optimizing costs or other relevant variables, by choosing the appropriate sample strategy (each of which ensures the same -level for the first stage). In addition, we evaluate the statistical power of the complete strategies under consideration.

Furthermore, we apply our theoretical results to a data example of Brucella melitensis. We used the herd-size situation in Germany, characterized by many small sheep holdings and only a few large ones. The consequences of real-test properties on sample sizes and on the applicability of several strategies are discussed.     

Animal health monitoring and surveillance in Switzerland

Switzerland has traditionally used a passive disease reporting system for all notifiable diseases. This type of system is not suitable for the documentation of very low prevalences (freedom from disease), sub-clinical cases and non-notifiable diseases. In order to meet the high international standards for animal health surveillance and to fulfil the general need for sound animal health data, Switzerland has evaluated the feasibility of modern monitoring and surveillance concepts. In general, the principle of active surveillance has been acquired and is now being applied whenever possible. In this paper, several examples of Swiss surveillance systems are presented and discussed. They include systematic testing of random population samples, carcase screening at abattoirs and sentinel herd monitoring.     

The application of epidemiology in aquatic animal health -opportunities and challenges

ABSTRACT: Over recent years the growth in aquaculture, accompanied by the emergence of new and transboundary diseases, has stimulated epidemiological studies of aquatic animal diseases. Great potential exists for both observational and theoretical approaches to investigate the processes driving emergence but, to date, compared to terrestrial systems, relatively few studies exist in aquatic animals. Research using risk methods has assessed routes of introduction of aquatic animal pathogens to facilitate safe trade (e.g. import risk analyses) and support biosecurity. Epidemiological studies of risk factors for disease in aquaculture (most notably Atlantic salmon farming) have effectively supported control measures. Methods developed for terrestrial livestock diseases (e.g. risk-based surveillance) could improve the capacity of aquatic animal surveillance systems to detect disease incursions and emergence. The study of disease in wild populations presents many challenges and the judicious use of theoretical models offers some solutions. Models, parameterised from observational studies of host pathogen interactions, have been used to extrapolate estimates of impacts on the individual to the population level. These have proved effective in estimating the likely impact of parasite infections on wild salmonid populations in Switzerland and Canada (where the importance of farmed salmon as a reservoir of infection was investigated). A lack of data is often the key constraint in the application of new approaches to surveillance and modelling. The need for epidemiological approaches to protect aquatic animal health will inevitably increase in the face of the combined challenges of climate change, increasing anthropogenic pressures, limited water sources and the growth in aquaculture. TABLE OF CONTENTS: 1 Introduction 42 The development of aquatic epidemiology 73 Transboundary and emerging diseases 93.1 Import risk analysis (IRA) 103.2 Aquaculture and disease emergence 113.3 Climate change and disease emergence 133.4 Outbreak investigations 134 Surveillance and surveys 154.1 Investigation of disease prevalence 154.2 Developments in surveillance methodology 164.2.1 Risk-based surveillance and scenario tree modelling 164.2.2 Spatial and temporal analysis 164.3 Test validation 175 Spread, establishment and impact of pathogens 185.1 Identifying routes of spread 185.1.1 Ex-ante studies of disease spread 195.1.2 Ex-post observational studies 215.2 Identifying risk factors for disease establishment 235.3 Assessing impact at the population level 245.3.1 Recording mortality 245.3.2 Farm health and production records 265.3.3 Assessing the impact of disease in wild populations 276 Conclusions 317 Competing interests 328 Authors' contributions 329 Acknowledgements 3310 References 33.     

A novel method to identify herds with an increased probability of disease introduction due to animal trade

In the design of surveillance, there is often a desire to target high risk herds. Such risk-based approaches result in better allocation of resources and improve the performance of surveillance activities. For many contagious animal diseases, movement of live animals is a main route of transmission, and because of this, herds that purchase many live animals or have a large contact network due to trade can be seen as a high risk stratum of the population. This paper presents a new method to assess herd disease risk in animal movement networks. It is an improvement to current network measures that takes direction, temporal order, and also movement size and probability of disease into account. In the study, the method was used to calculate a probability of disease ratio (PDR) of herds in simulated datasets, and of real herds based on animal movement data from dairy herds included in a bulk milk survey for Coxiella burnetii. Known differences in probability of disease are easily incorporated in the calculations and the PDR was calculated while accounting for regional differences in probability of disease, and also by applying equal probability of disease throughout the population. Each herd's increased probability of disease due to purchase of animals was compared to both the average herd and herds within the same risk stratum. The results show that the PDR is able to capture the different circumstances related to disease prevalence and animal trade contact patterns. Comparison of results based on inclusion or exclusion of differences in risk also highlights how ignoring such differences can influence the ability to correctly identify high risk herds. The method shows a potential to be useful for risk-based surveillance, in the classification of herds in control programmes or to represent influential contacts in risk factor studies.     

Meeting report: panel on the potential utility and strategies for design and implementation of a national companion animal infectious disease surveillance system

This meeting report summarizes the discussions and recommendations of a Blue Ribbon Panel convened by the Science and Technology Policy Institute at the Institute for Defense Analysis on behalf of the White House Office of Science and Technology Policy (OSTP) on 13 September 2006 to discuss the potential utility and possible strategies for design and implementation of a companion animal health surveillance system. The panel comprised representatives from federal agencies, state agencies, academia, professional societies, and the private sector. The panel concluded that a companion animal surveillance system might prove valuable to efforts to protect public health, but that further study of the relationship between companion animal health and human health were needed to assess the utility and potential applications of a companion animal surveillance system. The findings of this panel may be used, along with other important sources of information, to inform policy discussions focussed on identifying strategies for recognizing and monitoring zoonotic disease threats appearing in companion animals in the USA.     

Current value of historical and ongoing surveillance for disease freedom: surveillance for bovine Johne's disease in Western Australia

‘Confidence’ in freedom from disease is generally derived from multiple sources of varied surveillance information, and typically this surveillance evidence has been accumulated over time. In the state of Western Australia (WA) the main surveillance evidence supporting Free Zone status in the national bovine Johne's disease (BJD) program comprises periodic surveys and the ongoing clinical diagnostic system. This paper illustrates a simple approach to current valuation of historical surveillance information, based on the calculated sensitivity of the surveillance processes, the time elapsed since the data were accumulated, and the probability of new introduction of disease into the population during that elapsed time. Surveillance system components (SSCs) contributing to the overall sensitivity of the surveillance system were the clinical diagnostic system and periodic targeted surveys. Sensitivity of each component was estimated using a stochastic scenario tree model of the surveillance process as implemented. Probability of introduction of BJD into WA during each time period was estimated retrospectively from a stochastic import risk analysis model applied to actual cattle importation data. The probability that the WA cattle population was free from infection (at design prevalences of 0.2% of herds and 2% of animals within an infected herd) was estimated following each of 11 years, giving a median probability that the State was free of BJD (at these design prevalences) at the end of 2005 of 0.89. The meaning of this result is discussed.     

Animal Health Policy Principles for Highly Pathogenic Avian Influenza: Shared Experience from China and Canada

Animal health policy for highly pathogenic avian influenza (HPAI) must, for the time being, be based on expert opinion and shared international experience. We used the intellectual capital and knowledge of experienced Chinese and Canadian practitioners and policy makers to inform policy options for China and find shared policy elements applicable to both countries. No peer‐reviewed comprehensive evaluations or systematic regulatory impact assessments of animal health policies were found. Sixteen guiding policy principles emerged from our thematic analysis of Chinese and Canadian policies. We provide a list of shared policy goals, targets and elements for HPAI preparedness, response and recovery. Policy elements clustered in a manner consistent with core public health competencies. Complex situations like HPAI require complex and adaptive policies, yet policies that cross jurisdictions and are fully integrated across agencies are rare. We encourage countries to develop or deploy capacity to undertake and publish regulatory impact assessments and policy evaluation to identify policy needs and provide a basis for evidence‐based policy development.