title: Epidemiological modelling for the assessment of bovine tuberculosis surveillance in the dairy farm network in Emilia-Romagna (Italy).
abstract: Assessing the performance of a surveillance system for infectious diseases of domestic animals is a challenging task for health authorities. Therefore, it is important to assess what strategy is the most effective in identifying the onset of an epidemic and in minimizing the number of infected farms. The aim of the present work was to evaluate the performance of the bovine tuberculosis (bTB) surveillance system in the network of dairy farms in the Emilia-Romagna (ER) Region, Italy. A bTB-free Region since 2007, ER implements an integrated surveillance strategy based on three components, namely routine on-farm tuberculin skin-testing performed every 3 years, tuberculin skin-testing of cattle exchanged between farms, and post-mortem inspection at slaughterhouses. We assessed the effectiveness of surveillance by means of a stochastic network model of both within-farm and between-farm bTB dynamics calibrated on data available for ER dairy farms. Epidemic dynamics were simulated for five scenarios: the current ER surveillance system, a no surveillance scenario that we used as the benchmark to characterize epidemic dynamics, three additional scenarios in which one of the surveillance components was removed at a time so as to outline its significance in detecting the infection. For each scenario we ran Monte Carlo simulations of bTB epidemics following the random introduction of an infected individual in the network. System performances were assessed through the comparative analysis of a number of statistics, including the time required for epidemic detection and the total number of infected farms during the epidemic. Our analysis showed that slaughterhouse inspection is the most effective surveillance component in reducing the time for disease detection, while routine surveillance in reducing the number of multi-farms epidemics. On the other hand, testing exchanged cattle improved the performance of the surveillance system only marginally.
authors.affiliation: Dipartimento di Bioscienze, Università di Parma, Parco Area delle Scienze 11/A, I-43124 Parma, Italy. Electronic address: gianluigi.rossi@nemo.unipr.it.
authors.forename: Gianluigi
authors.initials: G
authors.lastname: Rossi
authors.affiliation: Stanford University, Hopkins Marine Station, Pacific Grove, CA 93950, USA.
authors.forename: Giulio A
authors.initials: GA
authors.lastname: De Leo
authors.affiliation: Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia-Romagna, Via dei Mercati, 13/A, Parma I-43122, Italy.
authors.forename: Stefano
authors.initials: S
authors.lastname: Pongolini
authors.affiliation: Servizio Veterinario e Igiene Alimenti Assessorato Politiche per la Salute Regione Emilia-Romagna, Viale Aldo Moro 21, Bologna I-40127, Italy.
authors.forename: Silvano
authors.initials: S
authors.lastname: Natalini
authors.affiliation: Center for Stock Assessment Research, Department of Applied Mathematics and Statistics, University of California, Santa Cruz, CA 95064, USA; Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via Ponzio 34/5, I-20133 Milan, Italy.
authors.forename: Simone
authors.initials: S
authors.lastname: Vincenzi
authors.affiliation: Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia-Romagna, Via dei Mercati, 13/A, Parma I-43122, Italy; Department of Biodiversity and Molecular Ecology, Research and Innovation Centre - Fondazione Edmund Mach, San Michele all'Adige, Trento, Italy.
authors.forename: Luca
authors.initials: L
authors.lastname: Bolzoni
mesh_terms: D000383:Agriculture / Q000706:statistics & numerical data*; D000818:Animals; D002417:Cattle; D058872:Epidemics / Q000706:statistics & numerical data*; D006801:Humans; D007558:Italy / Q000453:epidemiology; D015233:Models, Statistical; D011159:Population Surveillance / Q000379:methods*; D014380:Tuberculosis, Bovine / Q000453:epidemiology*
keywords: Bovine tuberculosis; Disease surveillance; Epidemiological model; Network model; SEI model