Effectiveness and Cost Efficiency of Different Surveillance Components for Proving Freedom and Early Detection of Disease: Bluetongue Serotype 8 in Cattle as Case Study for Belgium, France and the Netherlands

Current practice and future directions in syndromic surveillance for animal health: A scoping review and analysis

Syndromic surveillance, the monitoring of non-specific indicators or symptoms, is a powerful tool for monitoring health or well-being. We conducted a scoping review to provide an up-to-date, global overview of syndromic surveillance for animal health, focusing on variation between animal sectors (livestock, companion, and wildlife), geography, indicators, data providers, and One Health approaches. We searched the Scopus and PubMed databases for articles describing or using data from syndromic surveillance systems or testing the potential of a data set or method for syndromic surveillance and supplemented this information with gray literature to determine further development of systems. We identified 126 syndromic surveillance systems from 165 articles. Most systems (n = 84, 67 %) were in the proof-of-concept phase, while only 25 (20 %) were established operational systems. These were mostly run by governments (n = 15, 58 %), as well as nonprofits (n = 4, 15 %), and academic institutions (n = 3, 12 %). The majority of systems monitored livestock (n = 89, 71 %); just over half were located in Europe (n = 64, 51 %) and a further 28 % (n = 35) in North America. Only eight systems (6 %) monitored multiple animal sectors. Twelve systems (10 %) used a One Health approach, linking data or surveillance concerning the same threat in humans and any animal sector. The most common data collectors were private veterinarians (n = 35, 28 %) and animals' owners (n = 29, 23 %); the most commonly used indicators were mortality (n = 52, 41 %), general illness (n = 36, 29 %), and reproductive symptoms (n = 31, 25 %). While syndromic surveillance for animals continues to develop, there is still a gap between research and implementation. However, even established systems are vulnerable to lack of continued funding and support. By compiling and analyzing this data, we highlight developments in syndromic surveillance for animals as well as differences in practices between sectors and regions of the world.

The use of scenario tree models in support of animal health surveillance: A scoping review

BACKGROUND

Scenario tree modelling is a well-known method used to evaluate the confidence of freedom from infection or to assess the sensitivity of a surveillance system in detecting an infection at a certain design prevalence. It facilitates the use of data from various sources and the inclusion of risk factors into calculations, while still obtaining quantitative estimates of surveillance sensitivity and probability of freedom.

OBJECTIVES

We conducted a scoping review to identify scenario tree models (STMs) applied to assess freedom from infection in veterinary medicine, characterize their use, parameterisation, reporting and potential limitations.

ELIGIBILITY CRITERIA

We included published scientific articles and grey literature that were a) neither reviews nor expert opinions, b) aimed to assess freedom from infection, provided methods to assess it, or aimed to estimate the sensitivity of a surveillance program for early detection of an infection at a design prevalence, c) targeted infection in animals and d) used scenario tree modelling. The search covered documents published between January 2006 and August 2021.

DESIGN

Several search methods were used to retrieve scientific articles and grey literature relevant to the subject. The search strategy included searching in scientific databases and/or grey literature repositories, contacting experts across the world that previously worked with STMs and retrieving citations from relevant reviews.

RESULTS AND DISCUSSION

Four hundred twenty-four distinct documents were retrieved with our search string. After screening, data was extracted from 99 documents representing 67 projects. Forty different animal diseases were modelled with STMs, the most represented being infections with tuberculous Mycobacterium sp., Avian Influenza A virus and Brucella sp. STMs were mostly used for diseases of cattle, swine and wild mammals. Results showed that STMs were used in a large variety of studies, are very versatile and were used in disparate frameworks. However, we also found that studies are not reported in a standardized way and often lack important information. This makes results hard to interpret, compare and reproduce. Additionally, we identified common assumptions and misconceptions, the most important ones regarding sensitivity and specificity, which could have an impact on the results of the studies using STMs.

CONCLUSION

We recommend the elaboration of internationally agreed guidelines about how to report results from STMs in a uniform manner. Such guidelines should include information on the study setting, procedures and analyses, but also on how the results could be interpreted concerning freedom from infection.

Exploring Options for Syndromic Surveillance in Aquaculture: Outbreak Detection of Salmon Pancreas Disease Using Production Data from Norwegian Farms

Syndromic surveillance (SyS) is an important tool for early warning and monitoring of health in human and animal populations, but its use in aquaculture has been limited. Our study objective was to design a SyS system for Atlantic salmon aquaculture and to evaluate its performance in detecting pancreas disease (PD) outbreaks caused by salmonid alphaviruses on farms. We defined SyS outbreak alarms as cases where monthly farm mortality exceeded predefined cutoffs or deviated significantly from expected values based on predictive generalized linear models. These models were trained for each salmon production area in Norway, using data from 2014 to 2017. The outcome variable was fish mortality per farm-month, and input variables were production and environmental predictors, as well as an offset for the number of fish at risk. We also added autoregressive components to explain temporal dependency within fish cohorts. Subsequently, data from 2018 to 2021 was used to parameterize and validate the SyS system's performance against the current national PD surveillance program, which relies on routine farm-screening tests using molecular techniques and reports of clinical findings. The study covered 19,119 farm-months, involving 1,618 fish cohorts. The performance of our SyS system varied across production areas, with sensitivity ranging from 80.5% to 87.4% and a false alarm rate of 45.3%-53.2%. The absence of alarms was usually observed in farms that were truly negative for PD, i.e., a negative predictive value range of 81.2%-94.0%. The median time for alarms being raised was either in the same month as the current PD surveillance program or 1 month prior or after it. Our results indicate that the SyS system is a valuable tool for monitoring mortality on salmon farms, but alarms are unspecific if evaluated against an individual disease (PD). Increasing the frequency and granularity of mortality reporting might improve the SyS system's performance.

A framework for evaluating health system surveillance sensitivity to support public health decision-making for malaria elimination: a case study from Indonesia

Background

The effectiveness of a surveillance system to detect infections in the population is paramount when confirming elimination. Estimating the sensitivity of a surveillance system requires identifying key steps in the care-seeking cascade, from initial infection to confirmed diagnosis, and quantifying the probability of appropriate action at each stage. Using malaria as an example, a framework was developed to estimate the sensitivity of key components of the malaria surveillance cascade.

Methods

Parameters to quantify the sensitivity of the surveillance system were derived from monthly malaria case data over a period of 36 months and semi-quantitative surveys in 46 health facilities on Java Island, Indonesia. Parameters were informed by the collected empirical data and estimated by modelling the flow of an infected individual through the system using a Bayesian framework. A model-driven health system survey was designed to collect empirical data to inform parameter estimates in the surveillance cascade.

Results

Heterogeneity across health facilities was observed in the estimated probability of care-seeking (range = 0.01–0.21, mean ± sd = 0.09 ± 0.05) and testing for malaria (range = 0.00–1.00, mean ± sd = 0.16 ± 0.29). Care-seeking was higher at facilities regularly providing antimalarial drugs (Odds Ratio [OR] = 2.98, 95% Credible Intervals [CI]: 1.54–3.16). Predictably, the availability of functioning microscopy equipment was associated with increased odds of being tested for malaria (OR = 7.33, 95% CI = 20.61).

Conclusions

The methods for estimating facility-level malaria surveillance sensitivity presented here can help provide a benchmark for what constitutes a strong system. The proposed approach also enables programs to identify components of the health system that can be improved to strengthen surveillance and support public-health decision-making.

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.

Bluetongue Disease Control in Northern Ireland During 2017 and 2018

Since the emergence of bluetongue virus in central and northern Europe in 2006, Northern Ireland's (NI) surveillance programme has evolved to include the use of risk assessments and simulation models to monitor the risk of bluetongue incursion. Livestock production is of high economic importance to NI as it exports approximately 75% of its agricultural produce. Its surveillance programme is designed to enable effective mitigation measures to be identified to minimize disease risk, and to provide additional assurances to protect NI's export markets in the European Union (EU) and third countries. Active surveillance employs an atmospheric dispersion model to assess the likelihood of wind-borne midge transfer from Great Britain (GB) to NI and to identify high risk areas. In these areas, the number of cattle tested for bluetongue is proportionally increased. Targeted surveillance is directed to ruminants imported from restricted countries and regions at risk of bluetongue. Targeted surveillance on high risk imports assists in early detection of disease as, despite all controls and preventive measures, legally imported animals may still carry the virus. In November 2018, a bluetongue-positive heifer was imported into NI. A case specific risk assessment was commissioned to estimate the likelihood of spread of bluetongue as a result of this incursion. November is the tail end of the midges' active period and therefore there was considerable uncertainty pertaining to the survival of midges inside a cattle shed and the potential for incubation of the virus in the vectors. An evidenced-based approach was adopted where temperature and midge abundance was monitored in order to minimize uncertainty and give an accurate estimate of the likelihood of virus spread to other animals following the arrival of the positive heifer. The heifer was destroyed and the evidence indicated that the risk of successful completion of the extrinsic cycle within the local midge population was negligible. This paper describes NI's surveillance programme between January 2017 and December 2018 and the case of a positive imported animal into the country. The importance of effective surveillance in early detection of threats and the usefulness of risk assessments is highlighted through the case study.

Effectiveness and cost-benefit study to encourage herd owners in a cost sharing vaccination programme against bluetongue serotype-8 in Belgium

Bluetongue (BT) is a ruminant viral infectious disease transmitted by Culicoides spp. midges. In 2006, when bluetongue virus serotype 8 (BTV-8) appeared for the first time in Northern Europe, it rapidly spread and infected a large proportion of animals. BThas a significant economic impact due to a direct effect on animal health and to an indirect effect in disrupting international trade of animals and animal products. In spring 2008, a compulsory subsidized vaccination programme in Europe resulted in a drastic decrease in the number of reported cases. However, due to the turn-over of the population, without a continuous vaccination programme, the animal population was becoming progressively susceptible. Vaccination would enable Belgium to maintain its status of freedom from infection of BTV-8 that could possibly be re-introduced. Subsidizing it could be an incentive to convince more farmers to vaccinate. To finance this programme, both decision-makers and stakeholders need to be persuaded by the effectiveness and the cost-benefit of vaccination. The study evaluated the effectiveness of vaccination against BTV-8 in Belgium. The change in serology which has shown the effectiveness of the vaccine to induce antibody production has been significantly associated with the time between the first injection and the sampling date and the number of injections of the primo-vaccination. This study also clearly confirms the benefit of vaccination by reducing economic impact of treatment and production losses, especially in dairy cattle. Based on a participating epidemiological approach, a national voluntary and subsidized vaccination was accepted, and permitted Belgium to vaccinate more than 9,000 herds in 1 month. Because this mass vaccination occurred before the vector season, it probably helped Belgium remain free from BTV-8.

Sampling Methodology to Maximize the Efficient Use of National Abattoir Surveillance: Using Archived Sera to Substantiate Freedom From Bluetongue Virus Infection in Ireland

In recent years, there has been increasing recognition of the value of multiple data sources available to fulfill surveillance objectives, and the use of these has been applied to address many questions relating to animal health surveillance. In Ireland, we face a slightly different problem, namely, best use of an existing surveillance resource (serological samples collected over many years from cull cows at slaughter), which has been used to substantiate freedom from Brucella abortus following its successful eradication in 2009. In this study, we evaluate a sampling methodology to use this resource to substantiate freedom from bluetongue virus (BTV) infection. An examination of the degree to which cull cows were resident in the same herd throughout the midge biting season showed that, of 50,640 samples collected between 17 October and 23 December 2016, 80.2% were from animals resident in the same herd between 01 April 2016 and 2 months prior to their slaughter date, 74.1% for 1 month prior, 70.1% for 2 weeks prior, 66.4% for 1 week prior, and 56.4% up to 1 day prior to slaughter. An examination was made of the degree to which individual samples within the same 88-well frozen storage block came from geographically clustered herds, whether from a concentration of animals from the same herd in a single block, or from clustering around the slaughterhouse where the samples were taken. On the basis of these analyses, a sampling strategy was derived aimed at minimizing the number of storage blocks which needed to be thawed, whilst ensuring a large enough and representative sample, geographically stratified according to the bovine population of 51 squares, each 45 × 45 km, covering the entirety of Ireland. None of the 503 samples tested were positive for BTV, providing reassurance of national BTV freedom. More broadly, the study demonstrates the use of abattoir-based serological samples collected for one large scale surveillance programme in surveillance for other bovine infections.

Active animal health surveillance in European Union Member States: gaps and opportunities

Animal health surveillance enables the detection and control of animal diseases including zoonoses. Under the EU-FP7 project RISKSUR, a survey was conducted in 11 EU Member States and Switzerland to describe active surveillance components in 2011 managed by the public or private sector and identify gaps and opportunities. Information was collected about hazard, target population, geographical focus, legal obligation, management, surveillance design, risk-based sampling, and multi-hazard surveillance. Two countries were excluded due to incompleteness of data. Most of the 664 components targeted cattle (26·7%), pigs (17·5%) or poultry (16·0%). The most common surveillance objectives were demonstrating freedom from disease (43·8%) and case detection (26·8%). Over half of components applied risk-based sampling (57·1%), but mainly focused on a single population stratum (targeted risk-based) rather than differentiating between risk levels of different strata (stratified risk-based). About a third of components were multi-hazard (37·3%). Both risk-based sampling and multi-hazard surveillance were used more frequently in privately funded components. The study identified several gaps (e.g. lack of systematic documentation, inconsistent application of terminology) and opportunities (e.g. stratified risk-based sampling). The greater flexibility provided by the new EU Animal Health Law means that systematic evaluation of surveillance alternatives will be required to optimize cost-effectiveness.