Literature DB >> 18440660

Evaluation of surveillance strategies for bovine brucellosis in Japan using a simulation model.

Takehisa Yamamoto1, Toshiyuki Tsutsui, Akiko Nishiguchi, Sota Kobayashi.   

Abstract

Bovine brucellosis is caused by Brucella abortus and induces abortions in female cattle, with other cattle at risk of infection from the aborted fetus or contaminated placenta. In Japan, the number of cases has dramatically reduced due to national surveillance and eradication strategies. Bovine brucellosis is now believed to be eradicated in Japan. Here, we examine the surveillance strategies currently in place for early detection of infected cattle in the event of a future reintroduction of the disease. We compared current serological surveillance for the dairy population with bulk-milk surveillance and abortion surveillance, and used time to detection as the main criterion of surveillance efficacy. A stochastic individual-based model (IBM) was developed to simulate disease transmission within and between farms. Using outputs from the transmission model, a comparison of surveillance strategies was simulated. For evaluation of the robustness of the parameter values used in the transmission model, a sensitivity analysis was conducted. For the purpose of evaluating the direct costs of each surveillance strategy, the annual number of samples to be tested and the annual number of farms to be visited were estimated. Our results indicated that current serological surveillance with 60-month test intervals is not effective enough for rapid detection of a brucellosis outbreak. Bulk-milk surveillance appeared the most effective method based on the early detection of infected cows and a reduced number of samples required. The time to detection for abortion surveillance was greater than that of bulk-milk surveillance but varied widely depending on the reported ratio of abortions. Results from the surveillance model were consistent when alternative scenarios were applied to the transmission model. Although our model cannot exactly replicate an actual brucellosis outbreak, or the results of surveillance, our results may help decision-makers to choose the most effective surveillance strategy.

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Year:  2008        PMID: 18440660     DOI: 10.1016/j.prevetmed.2008.03.004

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  12 in total

1.  Seroepidemiology of bovine brucellosis in Colombia's preeminent dairy region, and its potential public health impact.

Authors:  Olga Lucia Herrán Ramirez; Huarrisson Azevedo Santos; Ingrid Lorena Jaramillo Delgado; Isabele da Costa Angelo
Journal:  Braz J Microbiol       Date:  2020-09-12       Impact factor: 2.476

2.  Why do farmers and veterinarians not report all bovine abortions, as requested by the clinical brucellosis surveillance system in France?

Authors:  Anne Bronner; Viviane Hénaux; Nicolas Fortané; Pascal Hendrikx; Didier Calavas
Journal:  BMC Vet Res       Date:  2014-04-24       Impact factor: 2.741

3.  Optimizing the precision of case fatality ratio estimates under the surveillance pyramid approach.

Authors:  Camille Pelat; Neil M Ferguson; Peter J White; Carrie Reed; Lyn Finelli; Simon Cauchemez; Christophe Fraser
Journal:  Am J Epidemiol       Date:  2014-09-25       Impact factor: 4.897

4.  Devising an indicator to detect mid-term abortions in dairy cattle: a first step towards syndromic surveillance of abortive diseases.

Authors:  Anne Bronner; Eric Morignat; Viviane Hénaux; Aurélien Madouasse; Emilie Gay; Didier Calavas
Journal:  PLoS One       Date:  2015-03-06       Impact factor: 3.240

5.  Circulating Strains of Brucella abortus in Cattle in Santo Domingo De Los Tsáchilas Province - Ecuador.

Authors:  Richar Ivan Rodríguez-Hidalgo; Javier Contreras-Zamora; Washington Benitez Ortiz; Karina Guerrero-Viracocha; Holger Salcan-Guaman; Elizabeth Minda; Lenin Ron Garrido
Journal:  Front Public Health       Date:  2015-03-10

6.  Modelling Seasonal Brucellosis Epidemics in Bayingolin Mongol Autonomous Prefecture of Xinjiang, China, 2010-2014.

Authors:  Pengwei Lou; Lei Wang; Xueliang Zhang; Jiabo Xu; Kai Wang
Journal:  Biomed Res Int       Date:  2016-10-30       Impact factor: 3.411

7.  Development of a forecasting model for brucellosis spreading in the Italian cattle trade network aimed to prioritise the field interventions.

Authors:  L Savini; L Candeloro; A Conte; F De Massis; A Giovannini
Journal:  PLoS One       Date:  2017-06-27       Impact factor: 3.240

Review 8.  Disease prediction models and operational readiness.

Authors:  Courtney D Corley; Laura L Pullum; David M Hartley; Corey Benedum; Christine Noonan; Peter M Rabinowitz; Mary J Lancaster
Journal:  PLoS One       Date:  2014-03-19       Impact factor: 3.240

9.  Systems approaches to animal disease surveillance and resource allocation: methodological frameworks for behavioral analysis.

Authors:  Karl M Rich; Matthew J Denwood; Alistair W Stott; Dominic J Mellor; Stuart W J Reid; George J Gunn
Journal:  PLoS One       Date:  2013-11-29       Impact factor: 3.240

10.  Evaluation of the cost-effectiveness of bovine brucellosis surveillance in a disease-free country using stochastic scenario tree modelling.

Authors:  Viviane Hénaux; Didier Calavas
Journal:  PLoS One       Date:  2017-08-31       Impact factor: 3.240

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