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      The Influence of Between-Farm Distance and Farm Size on the Spread of Classical Swine Fever during the 1997–1998 Epidemic in The Netherlands

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          Abstract

          As the size of livestock farms in The Netherlands is on the increase for economic reasons, an important question is how disease introduction risks and risks of onward transmission scale with farm size (i.e. with the number of animals on the farm). Here we use the epidemic data of the 1997–1998 epidemic of Classical Swine Fever (CSF) Virus in The Netherlands to address this question for CSF risks. This dataset is one of the most powerful ones statistically as in this epidemic a total of 428 pig farms where infected, with the majority of farm sizes ranging between 27 and 1750 pigs, including piglets. We have extended the earlier models for the transmission risk as a function of between-farm distance, by adding two factors. These factors describe the effect of farm size on the susceptibility of a ‘receiving’ farm and on the infectivity of a ‘sending’ farm (or ‘source’ farm), respectively. Using the best-fitting model, we show that the size of a farm has a significant influence on both farm-level susceptibility and infectivity for CSF. Although larger farms are both more susceptible to CSF and, when infected, more infectious to other farms than smaller farms, the increase is less than linear. The higher the farm size, the smaller the effect of increments of farm size on the susceptibility and infectivity of a farm. Because of changes in the Dutch pig farming characteristics, a straightforward extrapolation of the observed farm size dependencies from 1997/1998 to present times would not be justified. However, based on our results one may expect that also for the current pig farming characteristics in The Netherlands, farm susceptibility and infectivity depend non-linearly on farm size, with some saturation effect for relatively large farm sizes.

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          The classical swine fever epidemic 1997-1998 in The Netherlands: descriptive epidemiology.

          The objective of this paper is to describe the severe epidemic of classical swine fever (CSF) in The Netherlands in 1997-1998 under a policy of non-vaccination, intensive surveillance, pre-emptive slaughter and stamping out in an area which has one of the highest pig and herd densities in Europe. The primary outbreak was detected on 4 February 1997 on a mixed sow and finishing pig herd. A total of 429 outbreaks was observed during the epidemic, and approximately 700,000 pigs from these herds were slaughtered. Among these outbreaks were two artificial insemination centres, which resulted in a CSF-suspect declaration of 1680 pig herds (mainly located in the southern part of The Netherlands). The time between introduction of CSF virus (CSFV) into the country and diagnosis of CSF in the primary outbreak was estimated to be approximately 6 weeks. It is presumed that CSFV was spread from The Netherlands to Italy and Spain via shipment of infected piglets in the beginning of February 1997, before the establishment of a total stand-still of transportation. In June 1997, CSFV is presumed to be introduced into Belgium from The Netherlands. Pre-emptive slaughter of herds that had been in contact with infected herds or were located in close vicinity of infected herds, was carried out around the first two outbreaks. However, this policy was not further exercised till mid-April 1997, when pre-emptive slaughter became a standard operational procedure for the rest of the epidemic. In total, 1286 pig herds were pre-emptively slaughtered. (approximately 1.1 million pigs). A total of 44 outbreaks (10%) was detected via pre-emptive slaughter. When there were clinical signs, the observed symptoms in infected herds were mainly atypical: fever, apathy, ataxia or a combination of these signs. In 322 out of 429 outbreaks (75%), detection was bases on clinical signs observed: 32% was detected by the farmer, 25% by the veterinary practitioner, 10% of the outbreaks by tracing teams and 8% by screening teams of the veterinary authorities. In 76% of the outbreaks detected by clinical signs, the farmer reported to have seen clinical symptoms for less than 1 week before diagnosis, in 22% for 1-4 weeks before diagnosis, and in 4 herds (1%) the farmer reported to have seen clinical symptoms for more than 4 weeks before diagnosis. Transportation lorries played a major role in the transmission of CSFV before the primary outbreak was diagnosed. It is estimated that approximately 39 herds were already infected before the first measures of the eradication campaign came into force. After the first measures to stop the spread of CSFV had been implemented, the distribution of the most likely routes of transmission markedly changed. In most outbreaks, a neighbourhood infection was indicated. Basically, there were two reasons for this catastrophe. Firstly, there was the extent of the period between introduction of the virus in the region and detection of the first outbreak. As a result, CSFV had opportunities to spread from one herd to another during this period. Secondly, the measures initially taken did not prove sufficient in the swine- and herd-dense region involved.
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            Rate of inter-herd transmission of classical swine fever virus by different types of contact during the 1997-8 epidemic in The Netherlands.

            In this study we quantified the rate at which classical swine fever had been transmitted by several different types of inter-herd contact during the 1997-8 epidemic in The Netherlands. During that epidemic 428 CSFV-infected pig herds were detected, 403 of which were include in this study. The estimated rates of transmission were 0.065 per shipment of live pigs, 0.011 per contact by a pig transportation lorry, 0.0068 per person contact, 0.0007 per dose of semen, 0.0065 per contact with a potentially contaminated pig assembly point, 0.027 per week per infected herd within a radius of 500 metres and 0.0078 per week per infected herd at a distance between 500 and 1000 metres. These transmission rates can be used to optimize the strategy to stop future epidemics of CSF in The Netherlands. In addition, the analysis demonstrated in this paper, can be used to quantify CSFV transmission rates from other epidemics.
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              The 1997-1998 epidemic of classical swine fever in the Netherlands.

              In 1997, the pig husbandry in the Netherlands was struck by a severe epidemic of classical swine fever (CSF). During this epidemic 429 CSF-infected herds were depopulated and approximately 1300 herds were slaughtered pre-emptively. In addition millions of pigs of herds not CSF-infected were killed for welfare reasons (over crowding or overweight). In this paper, we describe the course of the epidemic and the measures that were taken to control it. The first outbreak was detected on 4 February 1997 in the pig dense south-eastern part of the Netherlands. We estimate that CSF virus (CSFV) had already been present in the country by that time for 5-7 weeks and that the virus had been introduced into approximately 39 herds before the eradication campaign started. This campaign consisted of stamping-out infected herds, movement restrictions and efforts to diagnose infected herds as soon as possible. However, despite these measures the rate at which new outbreaks were detected continued to rise. The epidemic faded out only upon the implementation of additional measures such as rapid pre-emptive slaughter of herds in contact with or located near infected herds, increased hygienic measures, biweekly screening of all herds by veterinary practitioners, and reduction of the transportation movements for welfare reasons. The last infected herd was depopulated on 6 March 1998.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                18 April 2014
                : 9
                : 4
                : e95278
                Affiliations
                [1]Department of Epidemiology, Crisis organization and Diagnostics, Central Veterinary Institute (CVI) of Wageningen, Lelystad, The Netherlands
                Auburn University, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: RH TJH HJWR. Analyzed the data: GJB RH. Wrote the paper: GJB RH TJH HJWR.

                [¤]

                Current address: Stichting HIV Monitoring, Amsterdam, The Netherlands

                Article
                PONE-D-13-41171
                10.1371/journal.pone.0095278
                3991596
                24748233
                2e364021-f591-4353-b10d-38458fecbfd4
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 October 2013
                : 25 March 2014
                Page count
                Pages: 7
                Funding
                This work is part of BO-Project Maatschappelijk aanvaardbare dierziektebestrijding (BO-08-010-011) and was funded by the Netherlands Ministry for Economic Affairs, Agriculture and Innovation (EL&I). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Agriculture
                Animal Management
                Animal Welfare
                Computational Biology
                Population Modeling
                Infectious Disease Modeling
                Microbiology
                Virology
                Viral Transmission and Infection
                Veterinary Science
                Animal Types
                Large Animals
                Veterinary Diseases
                Veterinary Virology
                Veterinary Medicine
                Livestock Care
                Veterinary Epidemiology
                Computer and Information Sciences
                Computer Modeling
                Geoinformatics
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Biostatistics
                Applied Mathematics

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