Evaluation der Qualität von Meldedaten in der Schweiz

• Forschungsstelle: BLV
• Projektnummer: 1.07.11
• Projekttitel Englisch: Evaluation of the quality of case reporting data in Switzerland

Schlüsselwörter (Englisch)

case reporting, animal movements, cattle, data quality

Kurzbeschreibung (Englisch)

Case reporting is probably the most widely used surveillance approach world-wide due to its relative simple implementation and limited investment costs. However, it is also well documented that case reporting data can potentially be very biased due to limited case detection or low reporting motivation. Many influential factors on the quality of disease reporting have been identified in general. While some of these factors are expected to be constant throughout Switzerland, some may vary depending on region, culture, industry structure, production type etc. This may lead to spurious differences in disease occurrence. One relevant factor is disease awareness. Effectiveness of efforts to increase disease awareness are to date unknown. Differences in disease occurrence may also be due to true heterogeneity of disease frequencies. This may be related to regional differences in animal density, production practices, vector presence and particularly frequency of animal trade.

The goal of this project is to analyse disease reporting pattern using state-of-the art techniques from spatial and spatio-temporal statistics. This will be done both for individual case data and areal data using the number of cases in each spatial unit. Proxies for disease awareness will be included as explanatory variables to explain the spatial and spatio-temporal heterogeneity in disease rates through ecological regression. Additional data on animal movement will be integrated. From a methodological perspective, a major part of the work will be on the application and extension of recently developed numerical techniques to avoid the (potentially large) Monte Carlo error inherent in more standard ways of analysis via Markov chain Monte Carlo (MCMC).

Untersuchte staatliche Massnahme (Deutsch)

Überwachung der Tierseuchen und Zoonosen mittels Meldesystem
TSG Art. 11 (SR 916.40).

Gesetzliche Grundlage der Wirksamkeitsüberprüfung (Deutsch)

TSG Art. 42 (SR 916.40).

Bezug zu den politischen Schwerpunkten des Bundesrates (Deutsch)

Legislaturziele 2007-2011, Art. 11, Ziel 10.

Projektziele (Englisch)

1) To describe patterns in case reporting data (“passive” surveillance) using spatial and spatio-temporal modelling approaches. The RMC technique will be applied and extended in order to analyse case reporting surveillance data from Switzerland and to provide an atlas of case incidence for selected notifiable diseases in Switzerland.

2) To construct animal movement parameters from Tierverkehrsdatenbank (TVB) and to use those parameters as ecological covariates in spatio-temporal analyses of disease occurrence.

3) Synthesis: To develop a model that in consideration of all relevant factors allows the estimation of the sensitivity of case reporting

Expertenbericht/Kurzevaluation (Deutsch)

Selektionssitzung 2006

Beschluss: Annahme (1. Priorität)

Auflagen/Ergänzungen: Bewilligt sind ein PostDoc für 3 Jahre und Sachkosten von Fr. 13'000.—.

Umsetzung: Steigerung Disease Awareness, Vorschriften anpassen oder erlassen, Vollzug verbessern.

Begleitende Expertin: Cornelia Herholz

Weiteres Vorgehen: Projektbeschrieb ausarbeiten bis 31. März 2007.

Publikationssprachen (Deutsch)

Deutsch

Publikationssprachen (Englisch)

Englisch

Publikationen / Ergebnisse (Deutsch)

Schrödle B (2011): Ergebnisse einer räumlichen Analyse von Faktoren aus der Feldstudie econcept. Technical Report. University of Zurich.

 

econcept: Evaluation der Qualitat von Meldedaten in der Schweiz: Teilprojekt: Einflussfaktoren im Meldesystem, Schlussbericht 2. März 2010

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• Schlussbericht [PDF] 696 kB

Publikationen / Ergebnisse (Englisch)

Willgert K, Schrödle B and Schwermer H (2011): Spatial analysis of Bluetongue cases and vaccination of Swiss cattle in 2008 and 2009. Geospatial Health, 5(2), 227-237.

Schrödle B and Held L (2011): A primer on disease mapping and ecological regression using INLA. Computational Statistics, 26(6), 241-258.

Schrödle B, Held L, Riebler A and Danuser J (2011): Using INLA for the evaluation of veterinary surveillance data from Switzerland: A case study. Journal of the Royal Statistical Society, Series C, 60 (2), 261-279. 

Schrödle B, Held L and Rue H (2011): Assessing the impact of network data on the spatio-temporal spread of infectious diseases. Technical Report. University of Zurich. In revision for Biometrics.

Schrödle B and Held L (2010): Spatio-temporal disease mapping using INLA. Environmetrics.  DOI: 10.1002/env.1065.

Held L, Schrödle B and Rue H (2010): Posterior and cross-validatory predictive checks: A comparison of MCMC and INLA. In: Statistical Modelling and Regression Structures - Festschrift in Honour of Ludwig Fahrmeir. Springer, Heidelberg.

 

Schrödle B, Held L and Rue H (2011): Assessing the impact of network data on the spatio-temporal spread of infectious diseases. Technical Report. University of Zurich. In revision for Biometrics. DOI: 10.1111/j.1541-0420.01717.x

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• Datenblatt 1.07.11 [PDF] 44 kB