Concepts for risk-based surveillance in the field of veterinary medicine and veterinary public health: Review of current approaches

Stärk, Katharina D.C.; Regula, G.; Hernández, Jorge A.; Knopf, Lea; Fuchs, Klemens; Morris, Roger S.; Davies, Peter

doi:10.1186/1472-6963-6-20

Cited by 257 publications

(194 citation statements)

References 28 publications

Supporting

Mentioning

171

Contrasting

Unclassified

Order By: Relevance

“…But this approach is cost-intensive, especially for rare diseases where a large sample size is required, due to the low expected prevalence. One way of making this approach more efficient is the application of riskbased surveillance by targeting the sampling on high-risk populations in which specific, documented risk factors exist and where the probability of finding cases is highest [16]. Thus, resources can be focused on population strata where the disease to be detected is anticipated to be more common than in a randomly chosen part of the population.…”

Section: Introductionmentioning

confidence: 99%

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

2008

View full text Add to dashboard Cite

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

show abstract

Section: Introductionmentioning

confidence: 99%

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

2008

View full text Add to dashboard Cite

show abstract

“…In the case of classical swine fever clinical symptoms, an elevated fatality in pig herds or routine post-mortem findings raised on abattoirs are examples for such trigger elements, which call for further investigation of the underlying cause Stärk et al, 2006). The advantage of cost-efficiency due to the use of existing networks (animal owners, veterinary practitioners, routine meat inspection on abattoirs) has to be weighed against possible shortcomings in reporting speed and quality.…”

Section: Passive and Active Data Collectionmentioning

confidence: 99%

“…Provided that the risk factors were correctly identified and weighted, targeted surveillance yields a higher sensitivity and predictive value positive for a given sample volume than can be expected from randomly sampling across the whole population (Doherr and Audigé, 2001;Stärk et al, 2006).…”

Section: Targeted-or Risk-based Surveillancementioning

confidence: 99%

Control and eradication of Classic Swine Fever in wild boar

2009

EFSA Journal

View full text Add to dashboard Cite

SummaryClassical swine fever (CSF) is a disease that has been causing major socio-economic damages in the EU during the last decades. Although considerable progress has been made in the eradication and prevention of the disease, the threat for an epidemic still exists.The virus is endemic in the wild boar population of several member states (MS). Wild boar cannot be managed as domestic pigs. Hunting and vaccination have been tentatively used in order to stop transmission by reducing the number of susceptibles. Oral vaccination of wild boar with modified live vaccine based on the C-strain (the only suitable) is used; this vaccine does not allow serological differentiation between vaccinated and infected animals.The aim of the control measures for CSF in wild boar is to reduce the risk of transmission to domestic pigs, to prevent an "endemic phase evolution" or to reduce the endemic phase duration.In order to support and to improve the control and eradication measures as regards CSF in wild boar, EFSA was requested by the Commission to provide scientific advice on the efficacy of the available surveillance, hunting and vaccination measures to control and eradicate CSF in feral pig populations (wild boar), considering the possible use of new diagnostic tests and vaccines.In order to reply to the mandate data were collected from MS through two questionnaires (CSF vaccines, hunting practices and CSF vaccination in wild boar). Data were also extracted from the EU CSF wild boar data base, after requesting permission from the participating MS.Considering that the data received were rather limited and not comparable, the WG decided to use a model in order to fill the gaps in the available knowledge. For the evaluation of the efficacy of CSF control in wild boar a continuous metapopulation compartmental model developed in an EU research project (FP6-5015599-CSFVACCINE&WILDBOAR) was applied.Although the disease manifests in the same manner in both domestic pig and wild boar it is more difficult to identify in wild boar because clinical monitoring of these is hardly possible. Wild boar found dead constitutes the main alert sign of CSF. Hunters and gamekeepers should be instructed to report the finding of each dead wild boar to the competent authority at all times. In case of high-risk situations, a passive surveillance should be complemented by an active serological surveillance. The active sampling of wild boar is not as efficient as in domestic pigs considering that hunting is the sole practical system to obtain samples and that the aim of hunting is quite different.Consequently, the sample size is not controlled by authorities and fits rarely the aim of the survey in terms of detecting the presence of disease at a certain level. In addition, the interpretation of serological results is confounded by maternal derived antibodies (until the 6th month of age), vaccination and the sampling quality.There is no definition at EU level of spatial and temporal units for surveillance, neither for criteria defining a disease free wi...

show abstract

“…Doing so makes available a variety of network analysis methods, which have become very popular (e.g. Stärk et al 2006;Dube et al 2009;Martínez-López et al 2009) and are often referred to as ''social network analysis''.…”

Section: Network Analysis Of Spatiotemporal Datamentioning

confidence: 99%

Reconstructing disease transmission dynamics from animal movements and test data

Enright

O’Hare

2016

Stoch Environ Res Risk Assess

View full text Add to dashboard Cite

Disease outbreaks are often accompanied by a wealth of data, usually in the form of movements, locations and tests. This data is a valuable resource in which data scientists and epidemiologists can reconstruct the transmission pathways and parameters and thus devise control strategies. However, the spatiotemporal data gathered can be both vast whilst at the same time incomplete or contain errors frustrating the effort to accurately model the transmission processes. Fortunately, several techniques exist that can be used to infer the relevant information to help explain these processes. The aim of this article is to provide the reader with a user friendly introduction to the techniques used in dealing with the large datasets that exists in epidemiological and ecological science and the common pitfalls that are to be avoided as well as an introduction to inference techniques for estimating parameter values for mathematical models from spatiotemporal datasets.

show abstract

Concepts for risk-based surveillance in the field of veterinary medicine and veterinary public health: Review of current approaches

Cited by 257 publications

References 28 publications

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

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

Control and eradication of Classic Swine Fever in wild boar

Reconstructing disease transmission dynamics from animal movements and test data

Contact Info

Product

Resources

About