OASIS: an assessment tool of epidemiological surveillance systems in animal health and food safety

Hendrikx, Pascal; Chazel, Myriam; Moutou, François; Danan, Corinne; Richomme, Céline; Boué, Franck; Souillard, Rozenn; Gauchard, Françoise; Dufour, Barbara

doi:10.1017/s0950268811000161

Cited by 51 publications

(75 citation statements)

References 2 publications

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“…farm, laboratory), they should also be reported to a central database in real-time for data aggregation and analysis or they will have little value for early disease detection. Evaluation for animal health surveillance systems and data exist [96, 97] and should be used to quantify the usefulness of health and production recodring systems at the national level (or whichever level the SyS system is operated at). It is important to recognise that timeliness should not be treated as the be all and end all of SyS.…”

Section: Discussionmentioning

confidence: 99%

Methodological challenges to multivariate syndromic surveillance: a case study using Swiss animal health data

2016

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BackgroundIn an era of ubiquitous electronic collection of animal health data, multivariate surveillance systems (which concurrently monitor several data streams) should have a greater probability of detecting disease events than univariate systems. However, despite their limitations, univariate aberration detection algorithms are used in most active syndromic surveillance (SyS) systems because of their ease of application and interpretation. On the other hand, a stochastic modelling-based approach to multivariate surveillance offers more flexibility, allowing for the retention of historical outbreaks, for overdispersion and for non-stationarity. While such methods are not new, they are yet to be applied to animal health surveillance data. We applied an example of such stochastic model, Held and colleagues’ two-component model, to two multivariate animal health datasets from Switzerland.ResultsIn our first application, multivariate time series of the number of laboratories test requests were derived from Swiss animal diagnostic laboratories. We compare the performance of the two-component model to parallel monitoring using an improved Farrington algorithm and found both methods yield a satisfactorily low false alarm rate. However, the calibration test of the two-component model on the one-step ahead predictions proved satisfactory, making such an approach suitable for outbreak prediction. In our second application, the two-component model was applied to the multivariate time series of the number of cattle abortions and the number of test requests for bovine viral diarrhea (a disease that often results in abortions). We found that there is a two days lagged effect from the number of abortions to the number of test requests. We further compared the joint modelling and univariate modelling of the number of laboratory test requests time series. The joint modelling approach showed evidence of superiority in terms of forecasting abilities.ConclusionsStochastic modelling approaches offer the potential to address more realistic surveillance scenarios through, for example, the inclusion of times series specific parameters, or of covariates known to have an impact on syndrome counts. Nevertheless, many methodological challenges to multivariate surveillance of animal SyS data still remain. Deciding on the amount of corroboration among data streams that is required to escalate into an alert is not a trivial task given the sparse data on the events under consideration (e.g. disease outbreaks).

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Section: Discussionmentioning

confidence: 99%

Methodological challenges to multivariate syndromic surveillance: a case study using Swiss animal health data

2016

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“…Different procedures and sets of criteria have been proposed for the evaluation of surveillance systems (CDC 2001, Hendrikx and others 2011, Drewe and others 2015). Here the authors used an adaptation of the SERVAL system, which was originally proposed for the evaluation of animal health surveillance to ascertain whether a surveillance system is meeting its objectives.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the usefulness at national level of the dairy cattle health and production recording systems in Great Britain

et al. 2015

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“…A recent semi-quantitative method for surveillance evaluation proposed 78 assessment criteria, divided into ten sections, representing the functional parts of a surveillance system and including vector surveillance for VBDs (74). An adaptation of this tool, called SNATrop, was designed to assess national surveillance systems for animal diseases and zoonoses in developing countries (75), allowing assessment of the strengths and weaknesses of the systems and their overall cost.…”

Section: Evaluation Of Surveillance Systems For Vector-borne Diseasementioning

confidence: 99%

Epidemiological surveillance methods for vector-borne diseases

Thompson¹,

Etter²

2015

Rev. Sci. Tech. OIE

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SummaryCompared with many other diseases, the ever-increasing threat of vectorborne diseases (VBDs) represents a great challenge to public and animal health managers. Complex life cycles, changing distribution ranges, a variety of potential vectors and hosts, and the possible role of reservoirs make surveillance for VBDs a grave concern in a changing environment with increasing economic constraints. Surveillance activities may have various specific objectives and may focus on clinical disease, pathogens, vectors, hosts and/or reservoirs, but ultimately such activities should improve our ability to predict, prevent and/or control the diseases concerned. This paper briefly reviews existing and newly developed tools for the surveillance of VBDs. A range of examples, by no means exhaustive, illustrates that VBD surveillance usually involves a combination of methods to achieve its aims, and is best accomplished when these techniques are adapted to the specific environment and constraints of the region. More so than any other diseases, VBDs respect no administrative boundaries; in addition, animal, human and commodity movements are increasing dramatically, with illegal or unknown movements difficult to quantify. Vector-borne disease surveillance therefore becomes a serious issue for local and national organisations and is being conducted more and more at the regional and international level through multidisciplinary networks. With economic and logistical constraints, tools for optimising and evaluating the performance of surveillance systems are essential and examples of recent developments in this area are included. The continuous development of mapping, analytical and modelling tools provides us with an enhanced ability to interpret, visualise and communicate surveillance results. This review also demonstrates the importance of the link between surveillance and research, with interactions and benefits in both directions.

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OASIS: an assessment tool of epidemiological surveillance systems in animal health and food safety

Cited by 51 publications

References 2 publications

Methodological challenges to multivariate syndromic surveillance: a case study using Swiss animal health data

Methodological challenges to multivariate syndromic surveillance: a case study using Swiss animal health data

Evaluation of the usefulness at national level of the dairy cattle health and production recording systems in Great Britain

Epidemiological surveillance methods for vector-borne diseases

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