Using Bayes' rule to define the value of evidence from syndromic surveillance

Andersson, Mats Gunnar; Faverjon, Céline; Tedder, Flavie; Legrand, Loïc; Leblond, Agnès (2014). Using Bayes' rule to define the value of evidence from syndromic surveillance. PLoS ONE, 9(11), e111335. Public Library of Science 10.1371/journal.pone.0111335

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In this work we propose the adoption of a statistical framework used in the evaluation of forensic evidence as a tool for evaluating and presenting circumstantial "evidence" of a disease outbreak from syndromic surveillance. The basic idea is to exploit the predicted distributions of reported cases to calculate the ratio of the likelihood of observing n cases given an ongoing outbreak over the likelihood of observing n cases given no outbreak. The likelihood ratio defines the Value of Evidence (V). Using Bayes' rule, the prior odds for an ongoing outbreak are multiplied by V to obtain the posterior odds. This approach was applied to time series on the number of horses showing clinical respiratory symptoms or neurological symptoms. The separation between prior beliefs about the probability of an outbreak and the strength of evidence from syndromic surveillance offers a transparent reasoning process suitable for supporting decision makers. The value of evidence can be translated into a verbal statement, as often done in forensics or used for the production of risk maps. Furthermore, a Bayesian approach offers seamless integration of data from syndromic surveillance with results from predictive modeling and with information from other sources such as disease introduction risk assessments.

Item Type:

Journal Article (Original Article)

Division/Institute:

05 Veterinary Medicine > Research Foci > Veterinary Public Health / Herd Health Management
05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH) > Veterinary Public Health Institute
05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH)

UniBE Contributor:

Tedder, Flavie

Subjects:

600 Technology > 630 Agriculture

ISSN:

1932-6203

Publisher:

Public Library of Science

Language:

English

Submitter:

Susanne Agnes Lerch

Date Deposited:

23 Mar 2015 11:31

Last Modified:

05 Dec 2022 14:44

Publisher DOI:

10.1371/journal.pone.0111335

PubMed ID:

25364823

BORIS DOI:

10.7892/boris.65522

URI:

https://boris.unibe.ch/id/eprint/65522

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