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

Vaccination of poultry against highly pathogenic avian influenza - Part 2. Surveillance and mitigation measures

Selecting appropriate diagnostic methods that take account of the type of vaccine used is important when implementing a vaccination programme against highly pathogenic avian influenza (HPAI). If vaccination is effective, a decreased viral load is expected in the samples used for diagnosis, making molecular methods with high sensitivity the best choice. Although serological methods can be reasonably sensitive, they may produce results that are difficult to interpret. In addition to routine molecular monitoring, it is recommended to conduct viral isolation, genetic sequencing and phenotypic characterisation of any HPAI virus detected in vaccinated flocks to detect escape mutants early. Following emergency vaccination, various surveillance options based on virological testing of dead birds ('bucket sampling') at defined intervals were assessed to be effective for early detection of HPAIV and prove disease freedom in vaccinated populations. For ducks, virological or serological testing of live birds was assessed as an effective strategy. This surveillance could be also applied in the peri-vaccination zone on vaccinated establishments, while maintaining passive surveillance in unvaccinated chicken layers and turkeys, and weekly bucket sampling in unvaccinated ducks. To demonstrate disease freedom with > 99% confidence and to detect HPAI virus sufficiently early following preventive vaccination, monthly virological testing of all dead birds up to 15 per flock, coupled with passive surveillance in both vaccinated and unvaccinated flocks, is recommended. Reducing the sampling intervals increases the sensitivity of early detection up to 100%. To enable the safe movement of vaccinated poultry during emergency vaccination, laboratory examinations in the 72 h prior to the movement can be considered as a risk mitigation measure, in addition to clinical inspection; sampling results from existing surveillance activities carried out in these 72 h could be used. In this Opinion, several schemes are recommended to enable the safe movement of vaccinated poultry following preventive vaccination.

Surveillance for lumpy skin disease and foot and mouth disease in the Kimberley, Western Australia

We quantified the sensitivity of surveillance for lumpy skin disease (LSD) and foot and mouth disease (FMD) in cattle in the Kimberley region of Western Australia. We monitored producer and veterinary activity with cattle for 3 years commencing January 2020. Each year, ~274,000 cattle of 685,540 present on 92 pastoral leases (stations) were consigned to other stations, live export or slaughter. Veterinarians examined 103,000 cattle on the stations, 177,000 prior to live export, and 10,000 prior to slaughter. Detection probabilities for the disease prior to transport or during veterinary procedures and inspections were elicited by survey of 17 veterinarians working in Northern Australia. The veterinarians estimated the probabilities that they would notice, recognise, and submit samples from clinical cases of LSD and FMD, given a 5% prevalence of clinical signs in the herd. We used scenario tree methodology to estimate monthly surveillance sensitivity of observations made by producers and by veterinarians during herd management visits, pre-export inspections, and ante-mortem inspections. Average monthly combined sensitivities were 0.49 for FMD and 0.37 for LSD. Sensitivity was high for both diseases during the dry season and low in the wet season. We estimated the confidence in freedom from the estimated surveillance sensitivity given one hypothetically infected herd, estimated probability of introduction, and prior confidence in freedom. This study provided assurance that the Kimberley is free of these diseases and that routine producer and veterinary interactions with cattle are adequate for the timely detection of the disease should they be introduced.

Utility of surveillance data for planning for dengue elimination in Yogyakarta, Indonesia: a scenario-tree modelling approach

INTRODUCTION

Field trials and modelling studies suggest that elimination of dengue transmission may be possible through widespread release of Aedes aegypti mosquitoes infected with the insect bacterium Wolbachia pipientis (wMel strain), in conjunction with routine dengue control activities. This study aimed to develop a modelling framework to guide planning for the potential elimination of locally acquired dengue in Yogyakarta, a city of almost 400 000 people in Java, Indonesia.

METHODS

A scenario-tree modelling approach was used to estimate the sensitivity of the dengue surveillance system (including routine hospital-based reporting and primary-care-based enhanced surveillance), and time required to demonstrate elimination of locally acquired dengue in Yogyakarta city, assuming the detected incidence of dengue decreases to zero in the future. Age and gender were included as risk factors for dengue, and detection nodes included the probability of seeking care, probability of sample collection and testing, diagnostic test sensitivity and probability of case notification. Parameter distributions were derived from health system data or estimated by expert opinion. Alternative simulations were defined based on changes to key parameter values, separately and in combination.

RESULTS

For the default simulation, median surveillance system sensitivity was 0.131 (95% PI 0.111 to 0.152) per month. Median confidence in dengue elimination reached 80% after a minimum of 13 months of zero detected dengue cases and 90% confidence after 25 months, across different scenarios. The alternative simulations investigated produced relatively small changes in median system sensitivity and time to elimination.

CONCLUSION

This study suggests that with a combination of hospital-based surveillance and enhanced clinic-based surveillance for dengue, an acceptable level of confidence (80% probability) in the elimination of locally acquired dengue can be reached within 2 years. Increasing the surveillance system sensitivity could shorten the time to first ascertainment of elimination of dengue and increase the level of confidence in elimination.

A new methodology to extrapolate disease freedom to an area using surveillance results from selected aquatic populations

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.

Scenario tree modelling to inform surveillance design for maintaining freedom from Coxiella burnetii infection in Australian commercial dairy goat herds

We used scenario tree methods to determine how different disease detection methods might be used to provide quantitative evidence that Australian dairy goat herds are free of coxiellosis. The aim of our proposed C. burnetii surveillance programme is to find evidence of the absence of antigen as well as evidence of an absence of an immune response to C. burnetii infection in individual dairy goat herds. We defined a C. burnetii infected dairy goat herd as a herd in which at least one doe was showing evidence of either active infection or past C. burnetii exposure using four candidate surveillance system components (SSCs): (1) testing of individual doe whole blood using the C. burnetii com1 PCR; (2) testing of individual doe whole blood using the C. burnetii ELISA; (3) testing bulk tank milk (BTM) using the com1 PCR and the C. burnetii ELISA; and (4) investigations of abortions and stillborn kids submitted to a diagnostic laboratory for testing. Of eight candidate surveillance strategies (combinations of the SSCs listed above) individual doe ELISAs every six months combined with monthly BTM PCR and ELISA testing returned the highest surveillance system sensitivity of 0.963 (95% probability interval [PI] 0.911-0.982) for the lowest cost, at AUD 28.94 (95% PI 28.38-30.59) over a 12-month period, for every one percent increase in surveillance system sensitivity. Assuming a probability of disease freedom of 0.10 at the start of the surveillance program and a probability of C. burnetii introduction per month of 0.01 we estimate that 95% confidence that C. burnetii was absent from a herd could be achieved after a single round of individual doe ELISAs followed by period of 6 consecutive monthly BTM PCR and ELISA tests. The results of this study show that selection of the most efficient combination of surveillance system components requires a good understanding of initial herd C. burnetii status and the probability of introduction of infection and how this may change over time. Scenario tree analyses results have provided insight into the key determinants of C. burnetii detection ability.

Evaluation of the application of the Czech Republic to be recognised as having a negligible risk of classical scrapie

The Czech Republic submitted a request to the European Commission to be recognised as a Member State with negligible risk of classical scrapie. EFSA has been asked to assess if the Czech Republic in its application has demonstrated for a period of at least 7 years (2015-2021) and proposed for the future, that a sufficient number of ovine and caprine animals over 18 months of age, representative of slaughtered, culled or found dead on farm animals, have been and will continue to be tested annually to provide a 95% level of confidence of detecting classical scrapie if it is present in that population at a prevalence rate exceeding 0.1%. A risk-based approach using stochastic scenario-tree modelling accounting for surveillance stream and species was applied. There is still a lack of data on the actual performance of the approved tests under field conditions, especially in sheep. Therefore, alternative scenarios were explored extending the range from the sensitivity provided by the past European Union evaluations of diagnostic screening tests to a sensitivity of 50%, consistent with published data obtained under field conditions in infected goat populations. Using data provided by the Czech Republic for 2015-2022, the estimated parameters of the scenario-tree model, the range of values of diagnostic sensitivity and applying the criterion for the 95% confidence level, it is concluded that the Czech Republic has tested annually a sufficient number of small ruminants to meet the requirement, for all combinations of years and diagnostic sensitivity scenarios except for 60% diagnostic sensitivity in 2021 and 2022, and 50% in 2015, 2016 and 2018-2022. Based on the proposed number of samples to be tested in 2023 and future years, the Czech Republic would test a sufficient number of animals to meet the requirement for all combinations of diagnostic sensitivity, except for the 50% scenario.

Enhancing Insights into Australia's Gonococcal Surveillance Programme through Stochastic Modelling

Continued surveillance of antimicrobial resistance is critical as a feedback mechanism for the generation of concerted public health action. A characteristic of importance in evaluating disease surveillance systems is representativeness. Scenario tree modelling offers an approach to quantify system representativeness. This paper utilises the modelling approach to assess the Australian Gonococcal Surveillance Programme's representativeness as a case study. The model was built by identifying the sequence of events necessary for surveillance output generation through expert consultation and literature review. A scenario tree model was developed encompassing 16 dichotomous branches representing individual system sub-components. Key classifications included biological sex, clinical symptom status, and location of healthcare service access. The expected sensitivities for gonococcal detection and antibiotic status ascertainment were 0.624 (95% CI; 0.524, 0.736) and 0.144 (95% CI; 0.106, 0.189), respectively. Detection capacity of the system was observed to be high overall. The stochastic modelling approach has highlighted the need to consider differential risk factors such as sex, health-seeking behaviours, and clinical behaviour in sample generation. Actionable points generated by this study include modification of clinician behaviour and supplementary systems to achieve a greater contextual understanding of the surveillance data generation process.

Monitoring of chronic wasting disease (CWD) (IV)

The European Commission requested an analysis of the Chronic Wasting Disease (CWD) monitoring programme in Norway, Sweden, Finland, Iceland, Estonia, Latvia, Lithuania and Poland (9 January 2017-28 February 2022). Thirteen cases were detected in reindeer, 15 in moose and 3 in red deer. They showed two phenotypes, distinguished by the presence or absence of detectable disease-associated normal cellular prion protein (PrP) in lymphoreticular tissues. CWD was detected for the first time in Finland, Sweden and in other areas of Norway. In countries where the disease was not detected, the evidence was insufficient to rule out its presence altogether. Where cases were detected, the prevalence was below 1%. The data also suggest that the high-risk target groups for surveillance should be revised, and 'road kill' removed. Data show that, in addition to differences in age and sex, there are differences in the prion protein gene (PRNP) genotypes between positive and negative wild reindeer. A stepwise framework has been proposed with expanded minimum background surveillance to be implemented in European countries with relevant cervid species. Additional surveillance may include ad hoc surveys for four different objectives, specific to countries with/without cases, focusing on parallel testing of obex and lymph nodes from adult cervids in high-risk target groups, sustained over time, using sampling units and a data-driven design prevalence. Criteria for assessing the probability of CWD presence have been outlined, based on the definition of the geographical area, an annual assessment of risk of introduction, sustained minimum background surveillance, training and engagement of stakeholders and a surveillance programme based on data-driven parameters. All positive cases should be genotyped. Sample sizes for negative samples have been proposed to detect and estimate the frequency of PRNP polymorphisms. Double-strand sequencing of the entire PRNP open reading frame should be undertaken for all selected samples, with data collated in a centralised collection system at EU level.

Estimating probability of visual detection of exotic pests and diseases in the grains industry—An expert elicitation approach

Participants in the grains industry undertake general surveillance monitoring of grain crops for early detection of pests and diseases. Evaluating the adequacy of monitoring to ensure successful early detection relies on understanding the probability of detection of the relevant exotic crop pests and diseases. Empirical data on probability of detection is often not available. Our aim was to both gain a better understanding of how agronomists undertake visual crop surveillance, and use this insight to help inform structured expert judgments about the probability of early detection of various exotic grain pests and diseases. In our study we surveyed agronomists under a state funded program to identify survey methods used to undertake visual inspection of grain crops, and their confidence in detecting pests and diseases using the associated methods. We then elicited expert judgments on the probabilities of visual detection by agronomists of key exotic pests and diseases, and compared these estimates with the self-assessments of confidence made by agronomists. Results showed that agronomists used a systematic approach to visual crop inspection but that they were not confident in detecting exotic pests and diseases, with the exception of pest and diseases that affect leaves. They were most confident in visually detecting Barley stripe rust and Russian wheat aphid; however, confidence in detecting the latter was influenced by recent training. Expert judgments on the ability of agronomists to visually detect exotic pests and diseases early was in accordance with agronomists’ self-rated confidence of detection but highlighted uncertainty around the ability of agronomists in detecting non-leaf pests and diseases. The outcomes of the study demonstrated the utility of structured expert elicitation as a cost-effective tool for reducing knowledge gaps around the sensitivity of general surveillance for early detection, which in turn improves area freedom estimates.

Quantifying the probability of detection of wild ungulates with the Judas technique

The Judas technique is often used in control or eradication of particular vertebrate pests. The technique exploits the tendency of individuals to form social groups. A radio collar is affixed to an individual and its subsequent monitoring facilitates the detection of other conspecifics. Efficacy of this technique would be improved if managers could estimate the probability that a Judas individual would detect conspecifics. To calculate this probability, we estimated association rates of Judas individuals with other Judas individuals, given the length of time the Judas has been deployed. We developed a simple model of space-use for individual Judas animals and constrained detection probabilities to those specific areas. We then combined estimates for individual Judas animals to infer the probability that a wild individual could be detected in an area of interest via Judas surveillance. We illustrated the method by using data from a feral goat eradication program on Isla Santiago, Galápagos, and a feral pig eradication program on Santa Cruz Island, California. Association probabilities declined as the proximity between individual areas of use of a Judas pair decreased. Unconditional probabilities of detection within individual areas of use averaged 0.09 per month for feral pigs and 0.11 per month for feral goats. Probabilities that eradication had been achieved, given no detections of wild conspecifics, and an uninformative prior probability of eradication were 0.79 (90% CI 0.22-0.99) for feral goats and 0.87 (90% CI 0.44-1.0) for feral pigs. We envisage several additions to the analyses used that could improve estimates of Judas detection probability. Analyses such as these can help managers increase the efficacy of eradication efforts, leading to more effective effects to restore native biodiversity.

Confirming the broadscale eradication success of nutria (Myocastor coypus) from the Delmarva Peninsula, USA

Nutria (Myocastor coypus) were introduced to the eastern shore of Chesapeake Bay, USA in the 1940s. They reached peak densities in the late 1990s, causing massive wetland loss. Beginning in 2002, a systematic plan to eradicate nutria from the 1.7M ha Delmarva Peninsula was implemented. Since that time the nutria population has been effectively reduced, and no nutria have been detected since May 2015. A lack of detection does not equate with complete absence. We address the following three questions. (1) What is the expected probability of nutria eradication from the Delmarva Peninsula as of the end of 2020? (2) If the probability of eradication is below the management target of 0.95, how much more surveillance is required? (3) How sensitive is the estimated probability of eradication to varying levels of public surveillance and modelled population growth rates? These questions were addressed by employing a stochastic spatially-explicit surveillance model that uses data in which no nutria were detected to quantify the probability of complete absence (PoA) over the entire Delmarva Peninsula. We applied an analytical framework that decomposes the spatial risk of survivors and data into management zones, and took advantage of low-cost public reporting of nutria sightings. Active surveillance by the eradication program included detector dog and tracker surveys, shoreline surveys, detection with ground and water platforms (with hair snares), and camera traps. Results showed that the PoA increased with time and surveillance from a beginning PoA in May 2015 of  0.01 to a mean of 0.75 at the end of 2020. This indicates that the PoA on the Delmarva was well below the target threshold of 0.95 for declaring eradication success. However, given continued surveillance without detection, a PoA of 0.95 would be achieved by June 2022. This analysis provides an objective mechanism to align the expectations of policy makers, managers and the public on when eradication of nutria from the entire Delmarva Peninsula should be declared successful.

Detection of Low MAP Shedder Prevalence in Large Free-Stall Dairy Herds by Repeated Testing of Environmental Samples and Pooled Milk Samples

Simple Summary

Paratuberculosis is a disease which affects ruminants worldwide. Many countries have implemented certification and monitoring systems to control the disease, particularly in dairy herds. Monitoring herds certified as paratuberculosis non-suspect is an important component of paratuberculosis herd certification programs. The challenge is to detect the introduction or reintroduction of the infectious agent as early as possible with reasonable efforts but high certainty. In our study, we evaluated different low-cost testing schemes in herds where the share of infected animals was low, resulting in a low within-herd prevalence of animals shedding the bacteria that causes paratuberculosis in their feces. The test methods used were repeated pooled milk samples and fecal samples from the barn environment. Our study showed that numerous repetitions of different samples are necessary to monitor such herds with sufficiently high certainty. In the case of herds with a very low prevalence, our study showed that a combination of different sampling approaches is required.

Abstract

An easy-to-use and affordable surveillance system is crucial for paratuberculosis control. The use of environmental samples and milk pools has been proven to be effective for the detection of Mycobacterium avium subsp. paratuberculosis (MAP)-infected herds, but not for monitoring dairy herds certified as MAP non-suspect. We aimed to evaluate methods for the repeated testing of large dairy herds with a very low prevalence of MAP shedders, using different sets of environmental samples or pooled milk samples, collected monthly over a period of one year in 36 herds with known MAP shedder prevalence. Environmental samples were analyzed by bacterial culture and fecal PCR, and pools of 25 and 50 individual milk samples were analyzed by ELISA for MAP-specific antibodies. We estimated the cumulative sensitivity and specificity for up to twelve sampling events by adapting a Bayesian latent class model and taking into account the between- and within-test correlation. Our study revealed that at least seven repeated samplings of feces from the barn environment are necessary to achieve a sensitivity of 95% in herds with a within-herd shedder prevalence of at least 2%. The detection of herds with a prevalence of less than 2% is more challenging and, in addition to numerous repetitions, requires a combination of different samples.

Assessment of the Current Surveillance System for Human Leptospirosis in Ecuador by Decision Analytic Modeling

Leptospirosis is a globally disseminated zoonotic disease with no national surveillance systems. On the other hand, surveillance is crucial for improving population health, and surveillance systems produce data that motivates action. Unfortunately, like many other countries, Ecuador put in place a monitoring system that has never been tested. The goal of this study was to use scenario tree modeling to assess the sensitivity of Ecuador's current national surveillance system to human leptospirosis as the basis for an economic assessment of the system. We created a decision-tree model to analyze the current system's sensitivity. The inputs were described as probabilities distributions, and the model assessed the program's sensitivity as an output. The model also considers the geographical and weather variations across Ecuador's three continental regions: Andean, Amazonia, and the Coast. Several data sources were used to create the model, including leptospirosis records from Ecuador's Ministry of Public Health, national and international literature, and expert elicitation, all of which were incorporated in a Bayesian framework. We were able to determine the most critical parameters influencing each scenario's output (CSU) sensitivity through sensitivity analysis. The Coast region had the best sensitivity scenario, with a median of 0.85% (IC 95% 0.41-0.99), followed by the Amazonia with a median of 0.54% (CI 95% 0.18-0.99) and the Andes with a median of 0.29% (CI 95% 0.02-0.89). As per the sensitivity study, the most influential criteria on the system's sensitivity were "Attendance or probability of going to a health center" and "probability of having symptoms," notably for the Coast and Amazonia Regions.

Evaluation of diagnostic tests' sensitivity, specificity and predictive values in bovine carcasses showing brucellosis suggestive lesions, condemned by Brazilian Federal Meat Inspection Service in the Amazon Region of Brazil

Cervical bursitis is a suggestive lesion of bovine brucellosis. Diagnostic sensitivity and specificity of two brucellosis serological tests, Rose Bengal (RB) and serum agglutination test with 2-mercaptoethanol (SAT/2-ME), and of isolation and identification (bacteriology) were evaluated through Bayesian latent class analysis (BLCA). A total of 165 paired serum and cervical bursitis samples detected at inspection by Brazilian federal meat inspection services were analyzed. The best model fit to the data occurred when accounting for the conditional dependence between serological tests. According to this model, RB and SAT/2-ME had almost the same sensitivity, 0.960 [0.903 - 0.992] and 0.963 [0.906 - 0.994] with 95 % Credible Interval (95 %CrI), respectively. Specificities were 0.9068 [0.562 - 0.997] and 0.875 [0.546 - 0.990] for RB and SAT/2-ME, respectively, also with 95 %CrI. Bacteriology had lower sensitivity than serological tests, 0.594 (95 %CrI: [0.525 - 0.794]) and the highest specificity of all evaluated tests, 0.992 (95 %CrI: [0.961-1.00]). Prevalence of infected animals was 0.829 (95 %CrI: [0.700-0.900]). BLCA showed that both RB and SAT/2-ME fitted to the purpose of initial screening the brucellosis suspect in carcasses with cervical bursitis in a reliable way. The results of RB or SAT/2-ME can guide the sanitary actions for brucellosis control and help the implementation of a risk-based surveillance system in the meat production chain. This strategy is especially true in remote areas with large beef cattle herds, raised extensively, where in vivo tests are rarely performed due to logistic and management constraints, as in the Northern region of Brazil.

Use of scenario tree modelling to plan freedom from infection surveillance: Mycoplasma bovis in New Zealand

Since mid-2018, the New Zealand (NZ) Ministry for Primary Industries (MPI) has been operating an eradication program for an incursion of Mycoplasma bovis. Although NZ is still delimiting the outbreak, consideration is being given to how freedom from M. bovis will be demonstrated. Rapid demonstration of freedom will minimise the length of the program, significantly reducing its financial burden. This collaborative research was undertaken to help inform planning of surveillance to demonstrate freedom after M. bovis is believed eradicated. Scenario tree modelling (STM) involves assimilating multiple surveillance system components to determine whether disease is absent. STM has infrequently been used to plan appropriate surveillance but this was the approach used here. A stochastic simulation model was implemented in R. The model represented the NZ commercial dairy and non-dairy cattle industries and the current surveillance components that are also planned to be used to gather evidence of absence of M. bovis once it is eradicated. Different surveillance intensities and risk based versus random surveillance were simulated and compared for probability of freedom, financial cost of sampling and testing and the time to demonstrate freedom. The results indicate that the current surveillance components will enable demonstration of freedom. Surveillance components included bulk tank milk testing, herd testing and testing at meat processing plants, predominantly using an imperfect ELISA. Several combinations of surveillance components appeared most efficient achieving >95 % confidence of freedom over 2-4 years, whilst sampling 4-7 % of the non-dairy herds and less than 25 % of dairy herds annually. The results indicate that surveillance intensity can be lower than is currently occurring to support the delimiting phase, thereby saving significant resources in the post eradication phase (proof of freedom phases). Further consideration is required to enable the assumption of 100 % herd specificity made in the model to be achieved. The ELISA used is very specific, but will yield some false positives that must be resolved to their true status. This may occur for example through modified diagnostic test interpretation (e.g. cut point optimisation at individual and herd level) or resolution of putative false positive herds with epidemiological investigation. In conclusion this research demonstrates the utility of STM for planning surveillance programs, and in this instance has highlighted efficient and effective surveillance components for demonstrating freedom from M. bovis in NZ. It also highlights the need to achieve 100 % specificity for M. bovis in herds tested during the proof of freedom phases.

Risk-based surveillance of chronic wasting disease in semi-domestic reindeer

Reindeer pastoralism is a widespread practise across Fennoscandia and Russia. An outbreak of chronic wasting disease (CWD) among wild reindeer (Rangifer tarandus) poses a severe threat to the semi-domestic reindeer herding culture. Establishing surveillance is therefore key, but current models for surveillance of CWD are designed for wild cervids and rely on samples obtained from recreational hunters. Targeting animal groups with a higher infection probability is often used for more efficient disease surveillance. CWD has a long incubation period of 2-3 years, and the animals show clinical signs in the later stages of the infection i.e. 1-4 months prior to death. The semi-domestic reindeer are free-ranging most of the year, but during slaughtering in late fall, herders stress the animals in penned areas. This allows removal of animals with deviant behaviour or physical appearance, and such removals are likely to include animals in the clinical stages of CWD if the population is infected. In Norway, the semi-domestic reindeer in Filefjell is adjacent to a previously CWD infected wild population. We developed a risk-based surveillance method for this semi-domestic setting to establish the probability of freedom from infection over time, or enable early disease detection and mitigation. The surveillance scheme with a scenario tree using three risk categories (sample category, demographic group, and deviations in behaviour or physical appearance) was more effective and less invasive as compared to the surveillance method developed for wild reindeer. We also simulated how variation in susceptibility, incubation period and time for onset of clinical signs (linked to variation in the prion protein gene, PRNP) would potentially affect surveillance. Surveillance for CWD was mandatory within EU-member states with reindeer (2018-2020). The diversity of management systems and epidemiological settings will require the development of a set of surveillance systems suitable for each different context. Our surveillance model is designed for a population with a high risk of CWD introduction requiring massive sampling, while at the same time aiming to limit adverse effects to the populations in areas of surveillance.

Analysis of German BSE Surveillance Data: Estimation of the Prevalence of Confirmed Cases versus the Number of Infected, but Non-Detected, Cattle to Assess Confidence in Freedom from Infection

Quantitative risk assessments for Bovine spongiform encephalopathy (BSE) necessitate estimates for key parameters such as the prevalence of infection, the probability of absence of infection in defined birth cohorts, and the numbers of BSE-infected, but non-detected cattle entering the food chain. We estimated three key parameters with adjustment for misclassification using the German BSE surveillance data using a Gompertz model for latent (i.e., unobserved) age-dependent detection probabilities and a Poisson response model for the number of BSE cases for birth cohorts 1999 to 2015. The models were combined in a Bayesian framework. We estimated the median true BSE prevalence between 3.74 and 0.216 cases per 100,000 animals for the birth cohorts 1990 to 2001 and observed a peak for the 1996 birth cohort with a point estimate of 16.41 cases per 100,000 cattle. For birth cohorts ranging from 2002 to 2013, the estimated median prevalence was below one case per 100,000 heads. The calculated confidence in freedom from disease (design prevalence 1 in 100,000) was above 99.5% for the birth cohorts 2002 to 2006. In conclusion, BSE surveillance in the healthy slaughtered cattle chain was extremely sensitive at the time, when BSE repeatedly occurred in Germany (2000–2009), because the entry of BSE-infected cattle into the food chain could virtually be prevented by the extensive surveillance program during these years and until 2015 (estimated non-detected cases/100.000 [95% credible interval] in 2000, 2009, and 2015 are 0.64 [0.5,0.8], 0.05 [0.01,0.14], and 0.19 [0.05,0.61], respectively).

Control and Eradication Programs for Non-EU Regulated Cattle Diseases in the Netherlands

Within the European Union, infectious cattle diseases are categorized in the Animal Health Law. No strict EU regulations exist for control, evidence of disease freedom, and surveillance of diseases listed other than categories A and B. Consequently, EU member states follow their own varying strategies for disease control. The aim of this study was to provide an overview of the control and eradication programs (CPs) for six cattle diseases in the Netherlands between 2009 and 2019 and to highlight characteristics specific to the Dutch situation. All of these diseases were listed as C,D or E in the New Animal Health Law. In the Netherlands, CPs are in place for six endemic cattle diseases: bovine viral diarrhea, infectious bovine rhinotracheitis, salmonellosis, paratuberculosis, leptospirosis, and neosporosis. These CPs have been tailored to the specific situation in the Netherlands: a country with a high cattle density, a high rate of animal movements, a strong dependence on export of dairy products, and a high-quality data-infrastructure. The latter specifically applies to the dairy sector, which is the leading cattle sector in the Netherlands. When a herd enters a CP, generally the within-herd prevalence of infection is estimated in an initial assessment. The outcome creates awareness of the infection status of a herd and also provides an indication of the costs and time to achieve the preferred herd status. Subsequently, the herd enrolls in the control phase of the CP to, if present, eliminate the infection from a herd and a surveillance phase to substantiate the free or low prevalence status over time. The high-quality data infrastructure that results in complete and centrally registered census data on cattle movements provides the opportunity to design CPs while minimizing administrative efforts for the farmer. In the CPs, mostly routinely collected samples are used for surveillance. Where possible, requests for proof of the herd status are sent automatically. Automated detection of risk factors for introduction of new animals originating from a herd without the preferred herd status i.e., free or unsuspected, is in place using centrally registered data. The presented overview may inspire countries that want to develop cost-effective CPs for endemic diseases that are not (yet) regulated at EU level.

Quantitative decision making in animal health surveillance: Bovine Tuberculosis Surveillance in Belgium as case study

Despite eradication and control measures applied across Europe, bovine tuberculosis (bTB) remains a constant threat. In Belgium, after several years of official bTB-free status, routine movement testing, as currently practiced, revealed itself inadequate to detect some herds affected by sporadic breakdowns. The aim of this study was to assess different surveillance system components that strike a balance between cost and effectiveness and to identify sustainable alternatives, which substantiate a bTB-free claim while ensuring early detection and acceptance by various animal health stakeholders. For this pupose, a stochastic iteration model was used to simulate the current surveillance system's expected performance in terms of detection sensitivity and specificity. These results were then descriptively compared with observed field results. Second, the cost and effectiveness of simulated alternative surveillance components were quantified. Sensitivity analyses were performed to measure key assumptions' impacts (i.e. regarding diagnostic tests and true prevalence). The results confirmed discrepancies between the observed and simulated expected performance of bTB surveillance in Belgium. Second, simulated alternatives showed that interferon gamma (IFN-γ) and serological testing with antibody-enzyme linked immunosorbent assay (Ab-ELISA) targeting at-risk herds would enable an increase in the overall cost effectiveness (sensitivity and specificity) of the Belgian bTB surveillance system. Sensitivity analyses showed that results remained constant despite the modification of some key assumptions. While the performance of the ongoing bTB surveillance system in Belgium was questionable at the time of the study, this exercise highlighted that not only sensitivity but specificity also are key drivers of surveillance performance. The quantitative approach, taking into consideration various stakeholders' needs and priorities, revealed itself to be a useful tool in allowing evidence-based decision making for future tuberculosis surveillance in Belgium, in line with the international standards.

Development and evaluation of a new method to combine clinical impression survey data with existing laboratory data for veterinary syndromic surveillance with the Canada West Swine Health Intelligence Network (CWSHIN)

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.

Existence and Quality of Data on Control Programs for EU Non-regulated Cattle Diseases: Consequences for Estimation and Comparison of the Probability of Freedom From Infection

Some European countries have successfully implemented country-specific control programs (CPs) for infectious cattle diseases that are not regulated or are regulated only to a limited extent at the European Union (EU) level. Examples of such diseases include bovine viral diarrhea (BVD), infectious bovine rhinotracheitis (IBR), and Johne's disease (JD). The CPs vary between countries in the design and quality of collected data as well as methods used to detect infection and estimate prevalence or probability of freedom from infection. Differences in disease status between countries and non-standardized approaches to assess freedom from infection pose a risk for countries with CPs for non-regulated diseases as infected animals may influence the progress of the disease control or eradication program. The implementation of output-based standards allows estimation and comparison of the probability of freedom for non-regulated cattle diseases in European countries. The aim of the current study was to assess the existence and quality of data that could be used for estimating freedom from infection in European countries. The online data collection tool was sent to 32 countries participating in the SOUND control COST Action and was completed by 24 countries. Data on cattle demographics and data from CPs of IBR and BVD exist in more than 50% of the response countries. However, data describing risk factors and CP of JD was reported as existing in <25% of the countries. The overall quality of data in the sections on demographics and CPs of IBR and BVD were evaluated as "good", but risk factors and JD data were mostly evaluated as "fair." Data quality was considered less good mainly due to two quality criteria: accessibility and accuracy. The results of this study show that the quantity and quality of data about cattle populations and CPs are relatively similar in many surveyed countries. The outcome of this work provides an overview of the current situation in the European countries regarding data on EU non-regulated cattle diseases and will further assist in the development and implementation of output-based standards.

Risk of Introduction of Classical Swine Fever Into the State of Mato Grosso, Brazil

Classical swine fever (CSF) is considered one of the most important diseases of swine because of the far-reaching economic impact the disease causes to affected countries and regions. The state of Mato Grosso (MT) is part of Brazil's CSF-free zone. CSF status is uncertain in some of MT's neighboring States and countries, which has resulted in the perception that MT is at high risk for the disease. However, the risk for CSF introduction into MT has not been previously assessed. Here, we estimated that the risk for CSF introduction into the MT is highly heterogeneous. The risk associated with shipment of commercial pigs was concentrated in specific municipalities with intense commercial pig production, whereas the risk associated with movement of wild boars was clustered in certain municipalities located close to the state's borders, mostly in northern and southwestern MT. Considering the two pathways of possible introduction assessed here, these results demonstrate the importance of using alternative strategies for surveillance that target different routes and account for different likelihoods of introduction. These results will help to design, implement, and monitor surveillance activities for sustaining the CSF-free status of MT at times when Brazil plans to expand the recognition of disease-free status for other regions in the country.

Optimizing surveillance for early disease detection: Expert guidance for Ostreid herpesvirus surveillance design and system sensitivity calculation

To keep pace with rising opportunities for disease emergence and spread, surveillance in aquaculture must enable the early detection of both known and new pathogens. Conventional surveillance systems (designed to provide proof of disease freedom) may not support detection outside of periodic sampling windows, leaving substantial blind spots to pathogens that emerge in other times and places. To address this problem, we organized an expert panel to envision optimal systems for early disease detection, focusing on Ostreid herpesvirus 1 (OsHV-1), a pathogen of panzootic consequence to oyster industries. The panel followed an integrative group process to identify and weight surveillance system traits perceived as critical to the early detection of OsHV-1. Results offer a road map with fourteen factors to consider when building surveillance systems geared to early detection; factor weights can be used by planners and analysts to compare the relative value of different designs or enhancements. The results were also used to build a simple, but replicable, model estimating the system sensitivity (SSe) of observational surveillance and, in turn, the confidence in disease freedom that negative reporting can provide. Findings suggest that optimally designed observational systems can contribute substantially to both early detection and disease freedom confidence. In contrast, active surveillance as a singular system is likely insufficient for early detection. The strongest systems combined active with observational surveillance and engaged joint industry and government involvement: results suggest that effective partnerships can generate highly sensitive systems, whereas ineffective partnerships may seriously erode early detection capability. Given the costs of routine testing, and the value (via averted losses) of early detection, we conclude that observational surveillance is an important and potentially very effective tool for health management and disease prevention on oyster farms, but one that demands careful planning and participation. This evaluation centered on OsHV-1 detection in farmed oyster populations. However, many of the features likely generalize to other pathogens and settings, with the important caveat that the pathogens need to manifest via morbidity or mortality events in the species, life stages and environments under observation.

The effectiveness of bovine tuberculosis surveillance in Dutch badgers

Countries survey wildlife for bovine tuberculosis (bTB) to ensure case detection or to ascertain a high probability of freedom from bTB in wildlife. The Eurasian badger (Meles meles) is a potential bTB reservoir host. Between 2008 and 2019, 282 badgers were examined post‐mortem in the context of general wildlife disease and targeted bTB surveillance programmes in the Netherlands, and no bTB cases were detected. However, it was unclear how effective this surveillance effort was to demonstrate freedom from Mycobacterium bovis infection in the badger population of ±6000 or to detect cases if present.

Therefore, surveillance effectiveness was assessed using scenario tree modelling. For lack of standards for wildlife, the models were run against three assumed levels of disease in the population called design prevalence P*: 0.1%, 0.5%, and 3%. A small risk of introduction (0.015/year) was applied, because the Netherlands are officially free from bTB in cattle, with rare import of bTB‐infected cattle and no bTB‐infected wildlife reported along the Belgian and German borders with the Netherlands. Surveillance more readily picks up bTB presence in badgers when case detection sensitivity tends towards 100% and demonstrates freedom best when the probability of freedom tends towards 100%.

For P* 0.1%, 0.5% and 3%, respectively, maximum case detection sensitivity during 2008–2019 was 8%, 35% and 94% and the probability of freedom in 2019 was 46%, 67%, and 95%. At P* = 3%, performing targeted surveillance on 300 badgers in a year would make it extremely unlikely to miss a case (case detection sensitivity > 99.9%); and if no cases are detected, the adjusted probability of freedom would then reach nearly 98.5%. Stakeholders should be made aware that at P* = 3%, one case detected implies around 3% infected badgers. Additional surveillance system components to assess bTB in wildlife and its economics are to be explored further.

Key Learnings During the Development of a Generic Data Collection Tool to Support Assessment of Freedom of Infection in Cattle Herds

Various European Member States have implemented control or eradication programmes for endemic infectious diseases in cattle. The design of these programmes varies between countries and therefore comparison of the outputs of different control programmes is complex. Although output-based methods to estimate the confidence of freedom resulting from these programmes are under development, as yet there is no practical modeling framework applicable to a variety of infectious diseases. Therefore, a data collection tool was developed to evaluate data availability and quality and to collect actual input data required for such a modeling framework. The aim of the current paper is to present the key learnings from the process of the development of this data collection tool. The data collection tool was developed by experts from two international projects: STOC free (Surveillance Tool for Outcome-based Comparison of FREEdom from infection, www.stocfree.eu) and SOUND control (Standardizing OUtput-based surveillance to control Non-regulated Diseases of cattle in the EU, www.sound-control.eu). Initially a data collection tool was developed for assessment of freedom of bovine viral diarrhea virus in six Western European countries. This tool was then further generalized to enable inclusion of data for other cattle diseases i.e., infectious bovine rhinotracheitis and Johne's disease. Subsequently, the tool was pilot-tested by a Western and Eastern European country, discussed with animal health experts from 32 different European countries and further developed for use throughout Europe. The developed online data collection tool includes a wide range of variables that could reasonably influence confidence of freedom, including those relating to cattle demographics, risk factors for introduction and characteristics of disease control programmes. Our results highlight the fact that data requirements for different cattle diseases can be generalized and easily included in a data collection tool. However, there are large differences in data availability and comparability across European countries, presenting challenges to the development of a standardized data collection tool and modeling framework. These key learnings are important for development of any generic data collection tool for animal disease control purposes. Further, the results can facilitate development of output-based modeling frameworks that aim to calculate confidence of freedom from disease.

Sensitivity of bovine tuberculosis surveillance through intradermal tests in cattle in France: An evaluation of different scenarios

The current situation regarding bovine tuberculosis (bTB) in Europe is spatially heterogeneous, with stagnating or increasing trends in bTB prevalence in many European regions, underlying the challenge in controlling this disease. In France, in spite of the implementation of two control programs in 2010-2012 to eradicate the disease and maintain the bTB-free status, bTB prevalence has continued to increase, underlying the need to reinforce and adapt surveillance measures. The goal of this study was to evaluate the effectiveness of bTB surveillance in high-risk areas in metropolitan France, with an emphasis on the criteria to select herds and animals within herds in the context of programmed surveillance and movement testing. The fraction of bTB-infected herds detected by the surveillance was quantified using a stochastic scenario tree modelling approach, with input parameter values based on surveillance and cattle traceability data and literature. The detection fraction was assessed for the current surveillance system and for alternative scenarios. The model predicted that the median detection fraction of infected herds by the current programmed surveillance in high-risk areas, which consists in annual testing of herds with a minimum age of testing of 24 months, was 71.5 % (interquartile interval: 47.4-89.4). The results showed a significant gain of the detection fraction with a decrease from 24 to 12 months old (83.5 % [60.6-95.9]) or to six weeks old (91.3 % [71.6-99.0]). Regarding pre-movement surveillance, tests are currently mandatory for bovines that originate from a previously infected herd or from a herd epidemiologically linked to a bTB-infected herd. The median detection fraction predicted by the model for this surveillance scenario was 1.2 % [0.7-1.8]. For the alternative scenario, where surveillance would be extended to all herds in high-risk areas, the model predicted a significant increase of the detection fraction to 26.5 % [18.1-37.9]. The results were sensitive to the following input values: the number of infected bovines within herds and, to a lower extent, the comparative intradermal tuberculin test sensitivity for both models, and surveillance coverage for the model on pre-movement surveillance. Our study underlines several complementary ways to improve the detection of infected herds, which is critical for implementing control measures and epidemiological investigations as early as possible. These necessary changes in surveillance must be accompanied by a global reflexion on surveillance financing.

Evaluation of the sensitivity of the classical swine fever surveillance system in two free zones in Colombia

Infection with the classical swine fever virus (CSFV) causes a disease in pigs that ranges from a hyperacute form in which animals die in a few hours to subclinical disease. Due to this wide range of virulence, several complementary surveillance strategies should be implemented for the early detection of the disease. The objective of the present study was to determine the sensitivity of the surveillance system to detect CSFV outbreaks in a free zone (Zone 1) and in a zone undergoing an eradication process (Zone 2) in Colombia. Stochastic scenario tree models were used to describe the population and surveillance structures and to determine the probability of CSFV detection. The total sensitivity of the surveillance system in the case of a single infected farm in Zone 1 was 31.4% (CI 95%: 7.2-54.1) and in the case of 5 infected farms was 85.2% (CI 95%: 67.3-93.7), while in Zone 2 the sensitivities were 27.8% (CI 95%: 6.4-55.1) and 82.5% (CI 95%: 65-92.9), respectively. The on-farm passive surveillance shows the highest sensitivity for detection of a single CSFV infected farm in both zones (22.8% in Zone 1 and 22.5% in Zone 2). The probability of detection was higher in a family / backyard premise than on a commercial farm in both zones. The passive surveillance at slaughterhouse had a sensitivity of 5.3% and 4.5% for the detection of a single infected farm in Zone 1 and 2, respectively. Active surveillance presented a range of sensitivity between 2.2% and 4.5%. In conclusion, the sensitivity of the surveillance in the two studied zones was quite high, one of reasons for this good sensitivity being the sentinel network based on the voluntary participation of 5,500 collaborators that were trained for the identification and notification of diseases of national interest.

Sample Size Estimation in Veterinary Epidemiologic Research

In the design of intervention and observational epidemiological studies sample size calculations are used to provide estimates of the minimum number of observations that need to be made to ensure that the stated objectives of a study are met. Justification of the number of subjects enrolled into a study and details of the assumptions and methodologies used to derive sample size estimates are now a mandatory component of grant application processes by funding agencies. Studies with insufficient numbers of study subjects run the risk of failing to identify differences among treatment or exposure groups when differences do, in fact, exist. Selection of a number of study subjects greater than that actually required results in a wastage of time and resources. In contrast to human epidemiological research, individual study subjects in a veterinary setting are almost always aggregated into hierarchical groups and, for this reason, sample size estimates calculated using formulae that assume data independence are not appropriate. This paper provides an overview of the reasons researchers might need to calculate an appropriate sample size in veterinary epidemiology and a summary of sample size calculation methods. Two approaches are presented for dealing with lack of data independence when calculating sample sizes: (1) inflation of crude sample size estimates using a design effect; and (2) simulation-based methods. The advantage of simulation methods is that appropriate sample sizes can be estimated for complex study designs for which formula-based methods are not available. A description of the methodological approach for simulation is described and a worked example provided.

A highly effective reverse-transcription loop-mediated isothermal amplification (RT-LAMP) assay for the rapid detection of SARS-CoV-2 infection

The COVID-19 pandemic has illustrated the importance of simple, rapid and accurate diagnostic testing. This study describes the validation of a new rapid SARS-CoV-2 RT-LAMP assay for use on extracted RNA or directly from swab offering an alternative diagnostic pathway that does not rely on traditional reagents that are often in short supply during a pandemic. Analytical specificity (ASp) of this new RT-LAMP assay was 100% and analytical sensitivity (ASe) was between 1 × 101 and 1 × 102 copies per reaction when using a synthetic DNA target. The overall diagnostic sensitivity (DSe) and specificity (DSp) of RNA RT-LAMP was 97% and 99% respectively, relative to the standard of care rRT-PCR. When a CT cut-off of 33 was employed, above which increasingly evidence suggests there is a low risk of patients shedding infectious virus, the diagnostic sensitivity was 100%. The DSe and DSp of Direct RT-LAMP (that does not require RNA extraction) was 67% and 97%, respectively. When setting CT cut-offs of ≤33 and ≤25, the DSe increased to 75% and 100%, respectively, time from swab-to-result, CT < 25, was < 15 min. We propose that RNA RT-LAMP could replace rRT-PCR where there is a need for increased sample throughput and Direct RT-LAMP as a near-patient screening tool to rapidly identify highly contagious individuals within emergency departments and care homes during times of increased disease prevalence ensuring negative results still get laboratory confirmation.

Modelling spread and surveillance of Mycobacterium avium subsp. paratuberculosis in the Swedish cattle trade network

To monitor a state of disease freedom and to ensure a timely detection of new introductions of disease, surveillance programmes need be evaluated prior to implementation. We present a strategy to evaluate surveillance of Mycobacterium avium subsp. paratuberculosis (MAP) using simulated testing of bulk milk in an infectious disease spread model. MAP is a globally distributed, chronic infectious disease with substantial animal health impact. Designing surveillance for this disease poses specific challenges because methods for surveillance evaluation have focused on estimating surveillance system sensitivity and probability of freedom from disease and do not account for spread of disease or complex and changing population structure over long periods. The aims of the study were to 1. define a model that describes the spread of MAP within and between Swedish herds; 2. define a method for simulation of imperfect diagnostic testing in this framework; 3. to compare surveillance strategies to support surveillance design choices. The results illustrate how this approach can be used to identify differences between the probability of detecting disease in the population based on choices of the number of herds sampled and the use of risk-based or random selection of these herds. The approach was also used to assess surveillance to detect introduction of disease and to detect a very low prevalence endemic state. The use of bulk milk sampling was determined to be an effective method to detect MAP in the population with as few as 500 herds tested per year if the herd-level prevalence was 0.2 %. However, detection of point introductions in the population was unlikely in the 13-year simulation period even if as many as 2000 herds were tested per year. Interestingly, the use of a risk-based selection strategy was found to be a disadvantage to detect MAP given the modelled disease dynamics.

Hunting strategies to increase detection of chronic wasting disease in cervids

The successful mitigation of emerging wildlife diseases may involve controversial host culling. For livestock, ‘preemptive host culling’ is an accepted practice involving the removal of herds with known contact to infected populations. When applied to wildlife, this proactive approach comes in conflict with biodiversity conservation goals. Here, we present an alternative approach of ‘proactive hunting surveillance’ with the aim of early disease detection that simultaneously avoids undesirable population decline by targeting demographic groups with (1) a higher likelihood of being infected and (2) a lower reproductive value. We applied this harvesting principle to populations of reindeer to substantiate freedom of chronic wasting disease (CWD) infection. Proactive hunting surveillance reached 99% probability of freedom from infection (<4 reindeer infected) within 3–5 years, in comparison to ~10 years using ordinary harvest surveillance. However, implementation uncertainties linked to social issues appear challenging also with this kind of host culling.

Rarely are the outcomes of mathematical (probability) models of wildlife disease detection used to inform policy or management changes. Here the authors develop a proactive hunting surveillance program that shortened the time required to establish freedom from chronic wasting disease at the population level in reindeer.

Post-outbreak African horse sickness surveillance: A scenario tree evaluation in South Africa's controlled area

An African horse sickness (AHS) outbreak occurred in March and April 2016 in the controlled area of South Africa. This extended an existing trade suspension of live equids from South Africa to the European Union. In the post-outbreak period ongoing passive and active surveillance, the latter in the form of monthly sentinel surveillance and a stand-alone freedom from disease survey in March 2017, took place. We describe a stochastic scenario tree analysis of these surveillance components for 24 months, starting July 2016, in three distinct geographic areas of the controlled area. Given that AHS was not detected, the probability of being free from AHS was between 98.3% and 99.8% assuming that, if it were present, it would have a prevalence of at least one infected animal in 1% of herds. This high level of freedom probability had been attained in all three areas within the first 9 months of the 2-year period. The primary driver of surveillance outcomes was the passive surveillance component. Active surveillance components contributed minimally (<0.2%) to the final probability of freedom. Sensitivity analysis showed that the probability of infected horses showing clinical signs was an important parameter influencing the system surveillance sensitivity. The monthly probability of disease introduction needed to be increased to 20% and greater to decrease the overall probability of freedom to below 90%. Current global standards require a 2-year post-incursion period of AHS freedom before re-evaluation of free zone status. Our findings show that the length of this period could be decreased if adequately sensitive surveillance is performed. In order to comply with international standards, active surveillance will remain a component of AHS surveillance in South Africa. Passive surveillance, however, can provide substantial evidence supporting AHS freedom status declarations, and further investment in this surveillance activity would be beneficial.

Johne's disease in Irish dairy herds: considerations for an effective national control programme

The Irish dairy industry has established a reputation for the production of safe and healthy dairy products and is seeking to further expand its export market for high value dairy products. To support its reputation, stakeholders aim to control Johne’s disease. To assist decision-makers determine the most appropriate design for an Irish programme, a narrative review of the scientific literature on the epidemiology of Johne’s disease, and selected control programmes throughout the world was undertaken. Two modelling studies specifically commissioned by Animal Health Ireland to assess testing methods used to demonstrate confidence of freedom in herds and to evaluate a range of possible surveillance strategies provided additional information. The majority of control programmes tend to be voluntary, because of the unique epidemiology of Johne’s disease and limited support for traditional regulatory approaches. While acknowledging that test performance and sub-clinical sero-negative shedders contributes to the spread of infection, a range of socio-political issues also exist that influence programme activities. The paper provides a rationale for the inclusion of a Veterinary Risk Assessment and Management Plan (VRAMP), including voluntary whole herd testing to identify infected herds and to support assurance-based trading through repeated rounds of negative testing, national surveillance for herd-level case-detection, and improved understanding of biosecurity management practices. Identification and promotion of drivers for industry and producer engagement in Ireland is likely to guide the future evolution of the Irish Johne’s Control Programme (IJCP) and further enhance its success. The provision of training, education and extension activities may encourage farmers to adopt relevant farm management practices and help them recognize that they are ultimately responsible for their herd’s health and biosecurity.

Assessment of the cost-effectiveness of alternative bovine tuberculosis surveillance protocols in French cattle farms using the mixed interferon gamma test

Periodic screening in farms, using intradermal cervical comparative tuberculin test (ICCT), is a component of the French ante mortem surveillance of bovine tuberculosis (bTB). Previous studies have estimated the cost-effectiveness of the French mandatory bTB screening protocols. In these protocols, a second ICCT (ICCT2) is performed 42 days after the first one (ICCT1), either on the entire herd (strict protocol) or in series on animals with non-negative results (reactors) to ICCT1 (compliant protocol). The 42-days interval reduced protocols' cost-effectiveness. To minimize this interval, we suggested two alternative protocols, in which a mixed interferon gamma test (IFNMIX), with better sensitivity than ICCT2 and comparable specificity, replaces the ICCT2, and is carried out directly after the ICCT1. In the strict alternative protocol, reactors to ICCT1 are culled to perform laboratory analyses (PCR, bacteriology). Negative results to these analyses imply the IFNMIX testing of the entire herd. In the compliant alternative protocol, only reactor(s) to ICCT1 are tested with IFNMIX, and animals with positive results to IFNMIX are culled for laboratory analyses. We evaluated these protocols through scenario tree modelling. The estimated cost-effectiveness indexes showed that the compliant alternative protocol was the most efficient. The strict protocols (mandatory and alternative) were never the most efficient, but were the most effective. Therefore, using IFNMIX instead of ICCT2 may be useful in reducing the costs of the compliant protocol used when the probability of infection is considered low. The strict alternative protocol may become more attractive would IFNMIX's price decreased.

Assessing the probability of freedom from pine wood nematode based on 19 years of surveys

Many quarantine pests, such as the pine wood nematode (PWN, Bursaphelenchus xylophilus), are surveyed annually in all EU countries. Although a lot of resources are spent in the surveys, the confidence in pest freedom achieved with them is not commonly analysed. We assessed the probability that Finland is free from PWN, based on the surveys done in 2000–2018. We used the methods employed in the risk-based estimate of system sensitivity tool (RiBESS), which has recently been recommended for quarantine pest applications. We considered two scenarios: 1) the surveys aimed to justify phytosanitary import requirements and to facilitate exports and 2) the surveys aimed to detect invasions early to enable eradication of outbreaks. These differed only in the pest prevalence that the surveys were expected to detect. The surveys appeared to support the assumption that PWN is not present in Finland, but they did not seem extensive enough to ensure early detection of invasions. The sensitivity of the import-export surveys was greater than 0.6 in 13 years, whereas that of the early detection surveys was always below 0.25. The probability of freedom achieved in 2018 following 19 years of surveys increased asymptotically with the mean time between invasions. For the import-export surveys, this probability was at least 0.95 unless the mean time between invasions was less than 13 years. For the early detection surveys, the probability of freedom was less than 0.73 unless the mean time between invasions was 63 years or more. The results were rather robust with respect to the parameters for which exact information was lacking. To improve the assessment, a quantitative estimate of the probability of PWN invasion to Finland and a thorough assessment of the maximum area of an eradicable infestation would be needed. To gain an understanding about the true impact of quarantine pest surveys on biosecurity, more assessments, like the one presented in this paper, are needed.

Why lockdown? Why national unity? Why global solidarity? Simplified arithmetic tools for decision-makers, health professionals, journalists and the general public to explore containment options for the 2019 novel coronavirus

As every country in the world struggles with the ongoing COVID-19 pandemic, it is essential that as many people as possible understand the epidemic containment, elimination and exclusion strategies required to tackle it. Simplified arithmetic models of COVID-19 transmission, control and elimination are presented in user-friendly Shiny and Excel formats that allow non-specialists to explore, query, critique and understand the containment decisions facing their country and the world at large. Although the predictive model is broadly applicable, the simulations presented are based on parameter values representative of the United Republic of Tanzania, which is still early enough in its epidemic cycle and response to avert a national catastrophe. The predictions of these models illustrate (1) why ambitious lock-down interventions to crush the curve represent the only realistic way for individual countries to contain their national-level epidemics before they turn into outright catastrophes, (2) why these need to be implemented so early, so stringently and for such extended periods, (3) why high prevalence of other pathogens causing similar symptoms to mild COVID-19 precludes the use of contact tracing as a substitute for lock down interventions to contain and eliminate epidemics, (4) why partial containment strategies intended to merely flatten the curve, by maintaining epidemics at manageably low levels, are grossly unrealistic, and (5) why local elimination may only be sustained after lock down ends if imported cases are comprehensively excluded, so international co-operation to conditionally re-open trade and travel between countries certified as free of COVID-19 represents the best strategy for motivating progress towards pandemic eradication at global level. The three sequential goals that every country needs to emphatically embrace are contain, eliminate and exclude. As recently emphasized by the World Health Organization, success will require widespread genuine national unity and unprecedented global solidarity.

A risk-based detection survey for the predatory mirid Macrolophus pygmaeus in New Zealand

Macrolophus pygmaeus, a predatory mirid used to manage greenhouse whitefly, was illegally imported into New Zealand, and for a time was reared and sold to commercial tomato growers. We designed and implemented a risk-based detection survey to determine whether M. pygmaeus was still present in New Zealand a decade later. The survey was designed to have an 80% chance of detecting a single low density (0.05 per lineal metre of host plants) population within 1 km of known points of introduction. The survey was implemented between 8 and 15 March 2018. Local habitat constraints meant that the planned sampling had to be modified but this was accounted for in the subsequent analysis. No M. pygmaeus were found in the samples, but 93 specimens from seven other mirid taxa were detected, validating the sample methods. The survey gives 60% confidence that M. pygmaeus was not present at a mean density of 0.05 per lineal metre of habitat. It gives 80% confidence that a population at 0.1 m-1 was not present and 90% confidence that no population exists at >0.18 m-1. Though there are no published data on typical field population densities of M. pygmaeus, for related species the survey would have had high confidence in detecting any medium to high density population present. Therefore, it is likely that M. pygmaeus is no longer present in New Zealand, but if extant within the sampled areas then we have high certainty that it was at low densities compared to other predaceous mirids.

Quantification of the sensitivity of early detection surveillance

Early detection surveillance is used for various purposes, including the early detection of non‐communicable diseases (e.g. cancer screening), of unusual increases of disease frequency (e.g. influenza or pertussis outbreaks), and the first occurrence of a disease in a previously free population. This latter purpose is particularly important due to the high consequences and cost of delayed detection of a disease moving to a new population. Quantifying the sensitivity of early detection surveillance allows important aspects of the performance of different systems, approaches and authorities to be evaluated, compared and improved. While quantitative evaluation of the sensitivity of other branches of surveillance has been available for many years, development has lagged in the area of early detection, arguably one of the most important purposes of surveillance. This paper, using mostly animal health examples, develops a simple approach to quantifying the sensitivity of early detection surveillance, in terms of population coverage, temporal coverage and detection sensitivity. This approach is extended to quantify the benefits of risk‐based approaches to early detection surveillance. Population‐based clinical surveillance (based on either farmers and their veterinarians, or patients and their local health services) provides the best combination of sensitivity, practicality and cost‐effectiveness. These systems can be significantly enhanced by removing disincentives to reporting, for instance by implementing effective strategies to improve farmer awareness and engagement with health services and addressing the challenges of well‐intentioned disease notification policies that inadvertently impose barriers to reporting.

Surveillance optimisation to detect poliovirus in the pre-eradication era: a modelling study of England and Wales

Surveillance for acute flaccid paralysis (AFP) cases are essential for polio eradication. However, as most poliovirus infections are asymptomatic and some regions of the world are inaccessible, additional surveillance tools require development. Within England and Wales, we demonstrate how inclusion of environmental sampling (ENV) improves the sensitivity of detecting both wild and vaccine-derived polioviruses (VDPVs) when compared to current surveillance. Statistical modelling was used to estimate the spatial risk of wild and VDPV importation and circulation in England and Wales. We estimate the sensitivity of each surveillance mode to detect poliovirus and the probability of being free from poliovirus, defined as being below a pre-specified prevalence of infection. Poliovirus risk was higher within local authorities in Manchester, Birmingham, Bradford and London. The sensitivity of detecting wild poliovirus within a given month using AFP and enterovirus surveillance was estimated to be 0.096 (95% CI 0.055–0.134). Inclusion of ENV in the three highest risk local authorities and a site in London increased surveillance sensitivity to 0.192 (95% CI 0.191–0.193). The sensitivity of ENV strategies can be compared using the framework by varying sites and the frequency of sampling. The probability of being free from poliovirus slowly increased from the date of the last case in 1993. ENV within areas thought to have the highest risk improves detection of poliovirus, and has the potential to improve confidence in the polio-free status of England and Wales and detect VDPVs.

Rigorous surveillance is necessary for high confidence in end-of-outbreak declarations for Ebola and other infectious diseases

The World Health Organization considers an Ebola outbreak to have ended once 42 days have passed since the last possible exposure to a confirmed case. Benefits of a quick end-of-outbreak declaration, such as reductions in trade/travel restrictions, must be balanced against the chance of flare-ups from undetected residual cases. We show how epidemiological modelling can be used to estimate the surveillance level required for decision-makers to be confident that an outbreak is over. Results from a simple model characterizing an Ebola outbreak suggest that a surveillance sensitivity (i.e. case reporting percentage) of 79% is necessary for 95% confidence that an outbreak is over after 42 days without symptomatic cases. With weaker surveillance, unrecognized transmission may still occur: if the surveillance sensitivity is only 40%, then 62 days must be waited for 95% certainty. By quantifying the certainty in end-of-outbreak declarations, public health decision-makers can plan and communicate more effectively. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This issue is linked with the earlier theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

Base protocol for real time active random surveillance of coronavirus disease (COVID-19) - Adapting veterinary methodology to public health

The pandemic of new coronavirus disease COVID-19 is threatening our health, economy and life style. Collaborations across countries and sectors as a One Health World could be a milestone.

We propose a general protocol, for setting timely active random surveillance of COVID-19, at the human community level, with systematic repeated detection efforts. Strengths and limitations are discussed.

If considered applicable by public health, the protocol could evaluate the status of COVID-19 epidemics consistently and objectively.

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A base protocol is proposed for setting active random surveillance of COVID-19.

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The protocol is based on widely known veterinary surveillance methodologies.

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By applying the protocol, COVID-19 epidemics could be consistently assessed.

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The protocol could be a milestone in the battle against the pandemic.

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Authorities could consider if the protocol is applicable for public health.

A description and qualitative comparison of the elements of heterogeneous bovine viral diarrhea control programs that influence confidence of freedom

For endemic infections in cattle that are not regulated at the European Union level, such as bovine viral diarrhea virus (BVDV), European Member States have implemented control or eradication programs (CEP) tailored to their specific situations. Different methods are used to assign infection-free status in CEP; therefore, the confidence of freedom associated with the "free" status generated by different CEP are difficult to compare, creating problems for the safe trade of cattle between territories. Safe trade would be facilitated with an output-based framework that enables a transparent and standardized comparison of confidence of freedom for CEP across herds, regions, or countries. The current paper represents the first step toward development of such a framework by seeking to describe and qualitatively compare elements of CEP that contribute to confidence of freedom. For this work, BVDV was used as a case study. We qualitatively compared heterogeneous BVDV CEP in 6 European countries: Germany, France, Ireland, the Netherlands, Sweden, and Scotland. Information about BVDV CEP that were in place in 2017 and factors influencing the risk of introduction and transmission of BVDV (the context) were collected using an existing tool, with modifications to collect information about aspects of control and context. For the 6 participating countries, we ranked all individual elements of the CEP and their contexts that could influence the probability that cattle from a herd categorized as BVDV-free are truly free from infection. Many differences in the context and design of BVDV CEP were found. As examples, CEP were either mandatory or voluntary, resulting in variation in risks from neighboring herds, and risk factors such as cattle density and the number of imported cattle varied greatly between territories. Differences were also found in both testing protocols and definitions of freedom from disease. The observed heterogeneity in both the context and CEP design will create difficulties when comparing different CEP in terms of confidence of freedom from infection. These results highlight the need for a standardized practical methodology to objectively and quantitatively determine confidence of freedom resulting from different CEP around the world.

Evaluation of the English bovine brucellosis surveillance system considering probability of disease introduction and non-random sampling

The English surveillance system for bovine brucellosis was evaluated. The confidence in detecting at least one infected herd in the local population (surveillance system sensitivity or SSe), and the confidence in freedom from disease (PFree) adjusted (PFreeAdj) for the probability of disease introduction from abroad by imported animals (PIntro), were estimated for quarterly surveillance periods of 2016; because dairy herds were tested quarterly on bulk tank milk (BTM) with an antibody indirect ELISA. A stochastic model was developed and six surveillance components (representing also the local population strata), were evaluated. All English herds and their relative risk (RRs) of infection within each stratum were considered. The importance of each component was assessed using actual national data, which reflected non-random sampling. The contribution of the abortions testing was assessed with particular focus, because a decline in statutory submissions was observed in recent years. Beef herds without submissions (B-NoTest herds) at the laboratories were still considered as a population stratum, where infected cattle could be imported. Additionally, we evaluated the importance of different hypothetical design between-herds prevalence (Ph) values, at which the country could be classified as "infected". The potential negative effect on SSe due to the dilution of antibodies when individual samples are pooled within BTM and tested by the milk iELISA, was also investigated. The quarterly median SSe and PFreeAdj were both ≥ 95 % if at least four (0.008 %) herds were infected in the country due to independent import events. The system appeared able to substantiate Official Brucellosis Free (OBF) status frequently (on quarterly basis) using Ph=0.2 % (EU legislation). The component based only on BTM testing (M herds) showed the highest sensitivity; while the surveillance components based on abortions or post import calving (PIC) testing, had very low sensitivity at the (considered) Ph values lower than 0.2 %. In contrast, at Ph = 0.2 %, components based on abortion testing had median sensitivity between 91.3 % and 99.9 %, and the dilution effect on BTM testing did not change remarkably the SSe and PFreeAdj. When Ph was set to 1-2 infected herds (0.002-0.004 %), these were usually allocated by the model within the B-NoTest stratum (the largest stratum) and SSe reduced. Thus, if policy considers necessary increasing the SSe for low Phs (system's optimization as an early warning system); the cost efficiency of active risk based surveillance in beef herds (considering imports) could be investigated in the future.

Assessment of bovine tuberculosis surveillance effectiveness in French wildlife: An operational approach

Bovine tuberculosis (bTB) is a chronic, zoonotic, bacterial disease mostly caused by Mycobacterium bovis, which can affect both domestic and wild species. France was officially declared bTB-free in 2001 but faced since 2004 an increase of the prevalence in cattle. Since 2001, bTB has been detected in several wild species: red deer (Cervus elaphus), roe deer (Capreolus capreolus), wild boar (Sus scrofa) and badger (Meles meles). Infected wild species constitute a major threat, because they may contribute to the maintenance of the infection in cattle and prevent eradication. In 2011, a surveillance system, Sylvatub, was implemented nationwide, to monitor the epidemiological status of bTB in mainland France. Our objective in this study was to assess the effectiveness of one of Sylvatub's passive surveillance system components (SSCs), which is based on the visual inspection of hunted animals (wild boars, red and roe deer) throughout mainland France. The following effectiveness criteria were evaluated: individual-level and component group-level positive and negative predictive values, and individual-level and component group-level probabilities of type I error ("false-positive" error) and type II error ("false-negative" error). These criteria were estimated quantitatively, at the scale of the département (a French administrative area of similar size to a county), with a stochastic scenario tree model. Individual negative predictive values were high, whereas individual positive predictive values were poor, whatever the species considered, and the training of hunters did not improve these effectiveness criteria sufficiently. The individual-level probability of type I error was relatively low, but the individual-level probability of type II error was generally high and was therefore an issue. However, increasing the proportion of trained hunters decreased this probability effectively. At group level, the size of the population surveyed had a marked impact on the effectiveness criteria: both the component group-level negative predictive value and the component group-level probability of type II error decreased rapidly with increasing population size. The conclusions drawn from such rationale may directly benefit stakeholders and actors in the field in their day to day practice of the surveillance processes. Thus, the assessment method used in this article presents the advantage of being operational, as well as being applicable to any surveillance system.

Cost-effectiveness of two different protocols for animal tracing investigations of bovine tuberculosis outbreaks in France

In the French bovine tuberculosis (bTB) surveillance program, tracing-on and back investigations have a major importance as, in 2016, they represented about 21 % of the detected outbreaks. Building on our previous work on the other surveillance system components (Poirier et al., 2019), we evaluated for the first time the sensitivity and the cost of the two existing protocols of bTB's tracing-on investigations trough scenario tree modelling with a stochastic approach. We used French databases (national database for bovine identification and database recording all bTB surveillance and control results) and direct and indirect costs collected in a previous study. These assessments allowed us to calculate the cost-effectiveness index (cost/sensitivity) of each tracing-on protocol. In the first protocol (trace-and-cull protocol), the animal(s) linking the farm to an outbreak are systematically culled for bacteriology, PCR and histology testing. In the second protocol (trace-and-test protocol), the traced animal is culled only if it had non-negative result to an intradermal cervical comparative tuberculin test (ICCT). We estimated herd sensitivity of the two tracing-on protocols for 12 herd types defined by their production type, size and herd turnover. For the trace-and-cull protocol, mean herd sensitivity was estimated between 67.3 % [66.8-67.7]_{CI95 %} and 89.2 % [88.7-89.7]_{CI95 %} and between 51.2 % [50.8-51.5]_{CI95 %} and 73.1 % [72.6-73.6]_{CI95 %} for the trace-and-test protocol, depending on herd type. The trace-and-cull protocol was between 278 €/herd and 717 €/herd more expensive than the trace-and-test protocol, depending on herd type. Regardless of herd type, the trace-and-cull protocol had the smaller cost/sensitivity ratio and was therefore the most cost-effective protocol. That work showed that systematically culling traced animals to perform bacteriology and PCR on them (trace-and-cull protocol) is associated with a better herd sensitivity and is more cost-effective for all herd types. That is consistent with French veterinary authorities' recommendations but does not account for sociological aspects such as the bond between the farmer and his animals. Yet, cost-effectiveness difference was minor in small dairy and beef herds with a low turnover, suggesting the protocol could be chosen depending on the epidemiological context in those herds.

Integrating data of veterinarians' practices in assessing the cost effectiveness of three components of the bovine tuberculosis surveillance system by intradermal tuberculin testing in French cattle farms through a scenario-tree approach

Disease surveillance systems' effectiveness relies on participants following prescribed practices. We developed a general method to improve a previous cost-effectiveness evaluation of three French screening program protocols for bovine tuberculosis (bTB) to account for the practices of participants by scenario tree modelling. This method relies on: 1) semi-directive interviews of participants to identify the variability of practices and potentially influential factors, and to understand the sociological context; 2) a quantitative survey, based on multiple-choice questions, to quantify various practices and identify significantly influential factors by multivariable regression analyses; 3) addition of the scenario-tree nodes corresponding to the practices and their influential factors and configuration of the new limbs according to the data of the quantitative survey. We used this approach to integrate data concerning veterinary practices and identify some failures to conform to regulatory guidelines regarding intradermal cervical comparative tuberculin test (SICCT) (testing and notification of non-negative results). Such nonconformities appeared to be mainly caused by cattle restraint issues and the perception of veterinarians of the bTB control program. Indeed, their perception of that program significantly influenced veterinarians' practices. We modelled the influence of the SICCT practices on the SICCT results. The incorporation of these data led to a major decrease of the herd sensitivity estimations relative to the previous assessments that did not incorporate data of practices (15% to 42% decrease). This result shows the important impact of veterinarians' practices and their influencing factors (such as perception of the bTB control program) on the effectiveness of the surveillance system.

Assessment of the sensitivity of the bovine tuberculosis eradication program in a high prevalence region of Spain using scenario tree modeling

In spite of the efforts invested to eradicate bovine tuberculosis (bTB) in cattle, the disease is still present in several developed countries, including Spain. Among the factors related with disease persistence in high prevalence areas, the lack of sensitivity of the screening test for detection of infected herds [single intradermal tuberculin (SIT) test] can play a major role. Here, a scenario tree model mimicking the diagnostic test scheme in place in the region of Castilla y Leon (Spain) was developed to estimate the probability of detecting bTB in an infected-non detected officially tuberculosis free (OTF) herd (herd sensitivity, HSe). In order to do so the probability of detecting at least one positive animal in the SIT test with/without post-mortem (detection of lesions and culture) confirmation in an infected herd was estimated using Monte Carlo simulation through @RISK (Palisade Co, NY, USA). Uncertainty on the accuracy of the diagnostic tests was introduced in the model using distributions based on the literature. The performance of the model was evaluated by comparing the predicted number of SIT/post-mortem positive animals in infected herds with those observed in newly detected bTB-infected herds in the region in 2011-2015. The estimated HSe of the SIT test was 76.2% (95% probability interval: 19.8-97.6). According to the model, bTB infection would be then confirmed through culture in 65.3% (95% PI: 50.0-82.3) of the herds detected through the SIT test, so that overall the proportion of infected-non detected OTF herds in which the infection could be confirmed after the initial SIT test was 49.6% (95% PI: 9.75-80.3). The predicted HSe of both SIT test and culture was directly correlated with herd size. Results from the model suggest a moderate but highly variable HSe of the current surveillance system in place for bTB detection in OTF herds located in high prevalence areas, that could be maximized by performing multiple tests within a year as indicated in the Spanish eradication program (with a median SIT HSe of 87% when two consecutive tests were considered). In addition, these results highlight the usefulness of performing subsequent SIT tests to rule out infection in SIT-positive herds even when the causative agent cannot be isolated.

Strategies for the Global Eradication of Peste des Petits Ruminants: An Argument for the Use of Guerrilla Rather Than Trench Warfare

Many historical disease eradication campaigns have been characterized by large-scale mobilization and long-term campaigns of mass vaccination. As the duration of a program increases, the total cost also increases, but the effectiveness and sustainability decrease, sometimes resulting in premature loss of stakeholder support, field team fatigue, and failure or major set-backs. In contrast to this trench warfare approach, this paper proposes an eradication strategy modeled on guerrilla tactics: use exceptionally good, locally relevant and timely intelligence; strike rapidly and effectively in small areas; achieve your goals; and keep moving. For peste des petits ruminants eradication, this means a shift away from long-term mass vaccination, focusing instead on addressing some of the challenges that have plagued previous eradication programs: ineffective surveillance and movement management. Recent developments in surveillance have shown that it is now feasible to capture information about almost all cases of disease, all movements and all control activities, from the entire population in real time. Developing powerful, effective and sustainable surveillance systems is an essential prerequisite for rapid, affordable PPR eradication. PPR can be rapidly eliminated from small populations by achieving very high levels of vaccination coverage for only a short period. The key challenge is then to prevent the re-introduction of disease as immunity wanes, and to respond rapidly and effectively in the case of further local outbreaks. A comprehensive understanding of movement patterns and their drivers will allow rapid progressive eradication to be implemented. The population can be divided into manageably small units, targeted sequentially for high-coverage short-duration vaccination, then moving to the next unit based on the distribution of disease and the direction of animal flow. This approach optimizes the use of available resources, and minimizes the challenge and disruption of managing retrograde movement from infected to uninfected areas. High levels of community engagement are required to achieve the quality of surveillance, movement management and rapid response necessary for success. Traditionally, long-term vaccination has been used to first eliminate the virus from a population, and then to protect it against re-introduction of the disease. Under the guerrilla strategy, continuous real-time information, not long-term vaccination, is the main tool for disease eradication.