Literature DB >> 21081252

Using mortality data for early detection of Classical Swine Fever in The Netherlands.

J A Backer1, H Brouwer, G van Schaik, H J W van Roermund.   

Abstract

Early detection of the introduction of an infectious livestock disease is of great importance to limit the potential extent of an outbreak. Classical Swine Fever (CSF) often causes non-specific clinical signs, which can take considerable time to be detected. Currently, the disease can be detected by three main routes, that are all triggered by clinical signs. To improve the early detection of CSF an additional program, based on mortality data, aims to routinely perform PCR tests on ear notch samples from herds with a high(er) mortality. To assess the effectiveness of this new early detection system, we have developed a stochastic model that describes the virus transmission within a pig herd, the development of disease in infected animals and the different early detection programs. As virus transmission and mortality (by CSF and by other causes) are different for finishing pigs, piglets and sows, a distinction is made between these pig categories. The model is applied to an extensive database that contains all unique pig herds in The Netherlands, their herd sizes and their mortality reports over the CSF-free period 2001-2005. Results from the simulations suggest that the new early detection system is not effective in piglet sections, due to the high mortality from non-CSF causes, nor in sow sections, due to the low CSF-mortality. In finishing herds, the model predicts that the new early detection system can improve the detection time by two days, from 38 (27-53) days to 36 (24-51) days after virus introduction, when assuming a moderately virulent virus strain causing a 50% CSF mortality. For this result up to 5 ear notch samples per herd from 8 (0-13) finishing herds must be tested every workday. Detecting a source herd two days earlier could considerably reduce the number of initially infected herds. However, considering the variation in outcome and the uncertainty in some model assumptions, this two-day gain in detection time is too small to demonstrate a substantial effect of the new early detection system based on mortality data. But when the alertness of herd-owners and veterinarians diminishes during long CSF-free periods, the new early detection system might gain in effectiveness.
Copyright © 2010 Elsevier B.V. All rights reserved.

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Year:  2011        PMID: 21081252     DOI: 10.1016/j.prevetmed.2010.10.008

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


  7 in total

1.  Exploring the surveillance potential of mortality data: nine years of bovine fallen stock data collected in Catalonia (Spain).

Authors:  Anna Alba; Fernanda C Dórea; Lucas Arinero; Javier Sanchez; Ruben Cordón; Pere Puig; Crawford W Revie
Journal:  PLoS One       Date:  2015-04-15       Impact factor: 3.240

2.  Vulnerability of the British swine industry to classical swine fever.

Authors:  Thibaud Porphyre; Carla Correia-Gomes; Margo E Chase-Topping; Kokouvi Gamado; Harriet K Auty; Ian Hutchinson; Aaron Reeves; George J Gunn; Mark E J Woolhouse
Journal:  Sci Rep       Date:  2017-02-22       Impact factor: 4.379

3.  Inferring within-herd transmission parameters for African swine fever virus using mortality data from outbreaks in the Russian Federation.

Authors:  C Guinat; T Porphyre; A Gogin; L Dixon; D U Pfeiffer; S Gubbins
Journal:  Transbound Emerg Dis       Date:  2017-11-09       Impact factor: 5.005

4.  Outcomes From Using Mortality, Antimicrobial Consumption, and Vaccine Use Data for Monitoring Endemic Diseases in Danish Swine Herds.

Authors:  Ana Carolina Lopes Antunes; Vibeke Frøkjær Jensen; Nils Toft
Journal:  Front Vet Sci       Date:  2019-02-22

5.  Unweaving tangled mortality and antibiotic consumption data to detect disease outbreaks - Peaks, growths, and foresight in swine production.

Authors:  Ana Carolina Lopes Antunes; Vibeke Frøkjær Jensen; Dan Jensen
Journal:  PLoS One       Date:  2019-10-09       Impact factor: 3.240

6.  Improving the Utility of Voluntary Ovine Fallen Stock Collection and Laboratory Diagnostic Submission Data for Animal Health Surveillance Purposes: A Development Cycle.

Authors:  Sue C Tongue; Jude I Eze; Carla Correia-Gomes; Franz Brülisauer; George J Gunn
Journal:  Front Vet Sci       Date:  2020-01-24

Review 7.  Transboundary Animal Diseases, an Overview of 17 Diseases with Potential for Global Spread and Serious Consequences.

Authors:  Elizabeth A Clemmons; Kendra J Alfson; John W Dutton
Journal:  Animals (Basel)       Date:  2021-07-08       Impact factor: 2.752

  7 in total

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