title: A rationale to unify measurements of effectiveness for animal health surveillance.
abstract: Surveillance systems produce data which, once analysed and interpreted, support decisions regarding disease management. While several performance measures for surveillance are in use, no theoretical framework has been proposed yet with a rationale for defining and estimating effectiveness measures of surveillance systems in a generic way. An effective surveillance system is a system whose data collection, analysis and interpretation processes lead to decisions that are appropriate given the true disease status of the target population. Accordingly, we developed a framework accounting for sampling, testing and data interpretation processes, to depict in a probabilistic way the direction and magnitude of the discrepancy between "decisions that would be made if the true state of a population was known" and the "decisions that are actually made upon the analysis and interpretation of surveillance data". The proposed framework provides a theoretical basis for standardised quantitative evaluation of the effectiveness of surveillance systems. We illustrate such approaches using hypothetical surveillance systems aimed at monitoring the prevalence of an endemic disease and at detecting an emerging disease as early as possible and with an empirical case study on a passive surveillance system aiming at detecting cases of Highly Pathogenic Avian Influenza cases in Vietnamese poultry.
authors.affiliation: UPR AGIRs, Animal and Integrate Risk Management, International Research Center in Agriculture for Development (CIRAD), TA C 22/E Campus International Baillarguet, 34398 Montpellier Cedex 5, France. Electronic address: Vladimir.grosbois@cirad.fr.
authors.forename: Vladimir
authors.initials: V
authors.lastname: Grosbois
authors.affiliation: Veterinary Epidemiology, Economics and Public Health, The Royal Veterinary College, Hawkshead Lane, North Mymms, Hatfield, Herts AL9 7TA, United Kingdom.
authors.forename: Barbara
authors.initials: B
authors.lastname: Häsler
authors.affiliation: UPR AGIRs, Animal and Integrate Risk Management, International Research Center in Agriculture for Development (CIRAD), TA C 22/E Campus International Baillarguet, 34398 Montpellier Cedex 5, France.
authors.forename: Marisa
authors.initials: M
authors.lastname: Peyre
authors.affiliation: Center for Interdisciplinary Research on Rural Development, Vietnam National University of Agriculture, Trau Quy, Gia Lam, Hanoi, Viet Nam.
authors.forename: Dao Thi
authors.initials: DT
authors.lastname: Hiep
authors.affiliation: Veterinary Epidemiology, Economics and Public Health, The Royal Veterinary College, Hawkshead Lane, North Mymms, Hatfield, Herts AL9 7TA, United Kingdom.
authors.forename: Timothée
authors.initials: T
authors.lastname: Vergne
mesh_terms: D000820:Animal Diseases / Q000453:epidemiology*; D000818:Animals; D011159:Population Surveillance / Q000379:methods; D015995:Prevalence; D015397:Program Evaluation / Q000379:methods / Q000592:standards
keywords: Decision making; Disease surveillance; Intervention; Type I error; Type II error