Using scenario tree modelling for targeted herd sampling to substantiate freedom from disease.

BACKGROUND: In order to optimise the cost-effectiveness of active surveillance to substantiate freedom from disease, a new approach using targeted sampling of farms was developed and applied on the example of infectious bovine rhinotracheitis (IBR) and enzootic bovine leucosis (EBL) in Switzerland. Relevant risk factors (RF) for the introduction of IBR and EBL into Swiss cattle farms were identified and their relative risks defined based on literature review and expert opinions. A quantitative model based on the scenario tree method was subsequently used to calculate the required sample size of a targeted sampling approach (TS) for a given sensitivity. We compared the sample size with that of a stratified random sample (sRS) with regard to efficiency. RESULTS: The required sample sizes to substantiate disease freedom were 1,241 farms for IBR and 1,750 farms for EBL to detect 0.2% herd prevalence with 99% sensitivity. Using conventional sRS, the required sample sizes were 2,259 farms for IBR and 2,243 for EBL. Considering the additional administrative expenses required for the planning of TS, the risk-based approach was still more cost-effective than a sRS (40% reduction on the full survey costs for IBR and 8% for EBL) due to the considerable reduction in sample size. CONCLUSIONS: As the model depends on RF selected through literature review and was parameterised with values estimated by experts, it is subject to some degree of uncertainty. Nevertheless, this approach provides the veterinary authorities with a promising tool for future cost-effective sampling designs.

Potential and Challenges of Community-Based Surveillance in Animal Health: A Pilot Study Among Equine Owners in Switzerland.

Animal owners' potential to observe and report clinical signs, as the persons with the closest contact to their animals, is an often neglected source of information in surveillance. Allowing community members other than health care professionals, such as animal owners, to report health events can contribute to close current surveillance gaps and enhance early detection. In the present study, we tested a community-based surveillance (CBS) approach in the equine community in Switzerland. We aimed at revealing the attitudes and intentions of equine owners toward reporting clinical signs by making use of an online questionnaire. We further set up and operated an online CBS tool, named Equi-Commun. Finally, we investigated potential reasons for the lack of its use by applying qualitative telephone interviews. The majority of the respondents of the online questionnaire (65.5%, 707/1,078) answered that they could see themselves reporting clinical observations of their equine. The multivariate logistic regression analysis indicated that French-speaking equine owners and those belonging to the positive attitude cluster are more likely to report to a CBS tool. Equi-Commun operated between October 2018 and December 2019 yet received only four reports. With the addition of qualitative interviews, we identified three critical, interlinked issues that may have led to the non-use of Equi-Commun within the Swiss equine community: (1) for successfully implementing CBS, the need for surveillance within the community of interest must be given; (2) the respective population under surveillance, here the equine, needs to show enough clinical cases for owners to be able to maintain the memory of an existing tool and its possible use; and (3) targeted and high effort communication of the system is key for its success. While CBS relying only on lay animal owners, complementary to existing surveillance systems, could potentially provide a good proxy of timely surveillance data, it is questionable whether the added value of generated surveillance knowledge is in balance with efforts necessary to implement a successful system. With this study, we showcased both the potential and challenges of CBS in animal health, as this may be of relevance and guidance for future initiatives.

Simulation Based Evaluation of Time Series for Syndromic Surveillance of Cattle in Switzerland.

Choosing the syndrome time series to monitor in a syndromic surveillance system is not a straight forward process. Defining which syndromes to monitor in order to maximize detection performance has been recently identified as one of the research priorities in Syndromic surveillance. Estimating the minimum size of an epidemic that could potentially be detected in a specific syndrome could be used as a criteria for comparing the performance of different syndrome time series, and could provide some guidance for syndrome selection. The aim of our study was to estimate the potential value of different time series for building a national syndromic surveillance system for cattle in Switzerland. Simulations were used to produce outbreaks of different size and shape and to estimate the ability of each time series and aberration detection algorithm to detect them with high sensitivity, specificity and timeliness. Two temporal aberration detection algorithms were also compared: Holt-Winters generalized exponential smoothing (HW) and Exponential Weighted Moving Average (EWMA). Our results indicated that a specific aberration detection algorithm should be used for each time series. In addition, time series with high counts per unit of time had good overall detection performance, but poor detection performance for small epidemics making them of limited use for an early detection system. Estimating the minimum size of simulated epidemics that could potentially be detected in syndrome TS-event detection pairs can help surveillance system designers choosing the most appropriate syndrome TS to include in their early epidemic surveillance system.

Comparative assessment of passive surveillance in disease-free and endemic situation: example of Brucella melitensis surveillance in Switzerland and in Bosnia and Herzegovina.

BACKGROUND: Globalization and subsequent growth in international trade in animals and animal products has increased the importance of international disease reporting. Efficient and reliable surveillance systems are needed in order to document the disease status of a population at a given time. In this context, passive surveillance plays an important role in early warning systems. However, it is not yet routinely integrated in the assessment of disease surveillance systems because different factors like the disease awareness (DA) of people reporting suspect cases influence the detection performance of passive surveillance. In this paper, we used scenario tree methodology in order to evaluate and compare the quality and benefit of abortion testing (ABT) for Brucella melitensis (Bm) between the disease free situation in Switzerland (CH) and a hypothetical disease free situation in Bosnia and Herzegovina (BH), taking into account DA levels assumed for the current endemic situation in BH. RESULTS: The structure and input parameters of the scenario tree were identical for CH and BH with the exception of population data in small ruminants and the DA in farmers and veterinarians. The sensitivity analysis of the stochastic scenario tree model showed that the small ruminant population structure and the DA of farmers were important influential parameters with regard to the unit sensitivity of ABT in both CH and BH. The DA of both farmers and veterinarians was assumed to be higher in BH than in CH due to the current endemic situation in BH. Although the same DA cannot necessarily be assumed for the modelled hypothetical disease free situation as for the actual endemic situation, it shows the importance of the higher vigilance of people reporting suspect cases on the probability that an average unit processed in the ABT-component would test positive. CONCLUSION: The actual sensitivity of passive surveillance approaches heavily depends on the context in which they are applied. Scenario tree modelling allows for the evaluation of such passive surveillance system components under assumed disease free situation. Despite data gaps, this is a real opportunity to compare different situations and to explore consequences of changes that could be made.

Occurrence, clinical involvement and zoonotic potential of endoparasites infecting Swiss pigs.

In order to estimate the diversity, clinical involvement and zoonotic potential of parasites in pigs submitted for diagnosis to the PathoPig project of the Swiss Federal Food Safety and Veterinary Office, faeces (n=125) from suckling piglets (n=39), weaners (n=60) and piglets beginning fattening (n=26) from 74 Swiss farms were examined by 3 coproscopical methods (i.e. sedimentation/zinc chloride-flotation; SAFC and Ziehl-Neelsen staining). Samples microscopically positive for Cryptosporidium were further tested by PCR/sequencing for species assessment. The most frequently detected parasite was Balantidium coli, a facultative pathogenic ciliate with zoonotic potential, in 5.1, 36.7 and 50.0% of suckling, weaners and fatteners and 43.2% of farms; however, no association with disease was observed. Isospora (syn. Cystoisospora) suis infections were detected in 13.3 and 11.1% of suckling piglets with and without diarrhoea, and in 10.0 and 13.3% of weaners and fatteners with diarrhoea, respectively, and were significant associated with emaciation. Cryptosporidium infections were detected in 10.3, 15.0 and 19.2% of sucklings, weaners and fatteners, respectively, and in 18.9% of the farms. Interestingly, two age-related species were identified: C. suis in younger piglets (2 to 6weeks) and C. scrofarum in older ones (6 to 17weeks). None of the pigs infected with C. scrofarum (n=8), but 3 of 4 piglets infected with C. suis (co-infection with I. suis in 2 cases) had diarrhoea. The zoonotic species C. parvum was not detected, nevertheless, sporadic cases of human infection with the porcine-adapted species have been reported. Ascaris suum, Trichuris suis and Strongylida were rarely detected (<4%) in all age categories.

Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland.

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.

Risk-based design of repeated surveys for the documentation of freedom from non-highly contagious diseases.

The documentation of freedom from disease requires reliable information on the actual disease status in a specific animal population. The implementation of active surveillance (surveys) is an effective method to gain this information. For economical reasons, the sample size should be as small as possible but large enough to achieve the required confidence level for a targeted threshold. When conducting surveys repeatedly, various information sources about the disease status of the population can be taken into account to adjust the required level of confidence for a follow-up survey (e.g. risk assessments regarding disease introduction and results of previous surveys). As a benefit, the sample size for national surveys can be reduced considerably. We illustrate this risk-based approach using examples of national surveys conducted in Switzerland. The sample size for the documentation of freedom from enzootic bovine leucosis (EBL) and Brucella melitensis in sheep and in goats could be reduced from 2325 to 415 cattle herds, from 2325 to 838 sheep herds and from 1975 to 761 goat herds, respectively.

Evaluation of the benefit of emergency vaccination in a foot-and-mouth disease free country with low livestock density.

Foot-and-mouth disease (FMD) is highly contagious and one of the most economically devastating diseases of cloven-hoofed animals. Scientific-based preparedness about how to best control the disease in a previously FMD-free country is therefore essential for veterinary services. The present study used a spatial, stochastic epidemic simulation model to compare the effectiveness of emergency vaccination with conventional (non-vaccination) control measures in Switzerland, a low-livestock density country. Model results revealed that emergency vaccination with a radius of 3 km or 10 km around infected premises (IP) did not significantly reduce either the cumulative herd incidence or epidemic duration if started in a small epidemic situation where the number of IPs is still low. However, in a situation where the epidemic has become extensive, both the cumulative herd incidence and epidemic duration are reduced significantly if vaccination were implemented with a radius of 10 km around IPs. The effect of different levels of conventional strategy measures was also explored for the non-vaccination strategy. It was found that a lower compliance level of farmers for movement restrictions and delayed culling of IPs significantly increased both the cumulative IP incidence and epidemic duration. Contingency management should therefore focus mainly on improving conventional strategies, by increasing disease awareness and communication with stakeholders and preparedness of culling teams in countries with a livestock structure similar to Switzerland; however, emergency vaccination should be considered if there are reasons to believe that the epidemic may become extensive, such as when disease detection has been delayed and many IPs are discovered at the beginning of the epidemic.

Risk-based sample size calculation for consecutive surveys to document freedom from animal diseases.

International trade regulations require disease freedom to be documented. This is generally achieved by national random surveys. Risk-based sample size calculations can reduce both the sample size and the costs for repeated surveys by one-third compared to traditional sample size calculations based on random sampling. In this approach, information from previous surveys can reduce the sample size of a new survey while maintaining its overall level of confidence. Risk-based sample size calculations have only formerly been described for one single survey and not when applied consecutively. Based on the existing deterministic origin of risk-based methods and sample size calculations, we devised a further development of sample size calculation to document freedom from non-highly contagious diseases. We show that for a repeated risk-based sample size calculation not only does the loss of confidence due to the risk of disease import and the risk of undetected disease within the country need to be calculated between the two surveys, but the time value of historical testing information also needs to be considered. As the order of surveys is important, a separate process, capable of calculating the time value of information from all conducted surveys, needs to be incorporated in the sample size calculation. This paper suggests how to use information from previous surveys in a risk-based approach for sample size calculations in consecutive surveys considering the adjusted time value of historical testing information, import risk assessments and the risk of disease spread within the country. Thus, the reduction of confidence between two surveys is adequately estimated. The results of sample size calculations for surveys over various years, under different conditions, show that the risk-based approach, including import risk assessments and adjusted time value of historical testing information, could reduce the sample size of annual surveys by 25% compared to the sample sizes calculated without a risk-based technique. The presented risk-based sample size calculation is appropriate for the requirements of consecutive surveys and outlines how the adjusted time value of historical testing information should be considered in this context. When planning to undertake repeated surveys to document freedom from disease, this method can easily be used to calculate sample sizes and consequently reduce them.

Establishing a cost-effective national surveillance system for Bluetongue using scenario tree modelling.

Vector-borne diseases pose a special challenge to veterinary authorities due to complex and time-consuming surveillance programs taking into account vector habitat. Using stochastic scenario tree modelling, each possible surveillance activity of a future surveillance system can be evaluated with regard to its sensitivity and the expected cost. The overall sensitivity of various potential surveillance systems, composed of different combinations of surveillance activities, is calculated and the proposed surveillance system is optimized with respect to the considered surveillance activities, the sensitivity and the cost. The objective of this project was to use stochastic scenario tree modelling in combination with a simple cost analysis in order to develop the national surveillance system for Bluetongue in Switzerland. This surveillance system was established due to the emerging outbreak of Bluetongue virus serotype 8 (BTV-8) in Northern Europe in 2006. Based on the modelling results, it was decided to implement an improved passive clinical surveillance in cattle and sheep through campaigns in order to increase disease awareness alongside a targeted bulk milk testing strategy in 200 dairy cattle herds located in high-risk areas. The estimated median probability of detection of cases (i.e. sensitivity) of the surveillance system in this combined approach was 96.4%. The evaluation of the prospective national surveillance system predicted that passive clinical surveillance in cattle would provide the highest probability to detect BTV-8 infected animals, followed by passive clinical surveillance in sheep and bulk milk testing of 200 dairy cattle farms in high-risk areas. This approach is also applicable in other countries and to other epidemic diseases.

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.