Monte Carlo simulation of classical swine fever epidemics and control - I. General concepts and description of the model

Institute of Animal Breeding and Husbandry, Christian-Albrechts-University, Hermann-Rodewald-Str. 6, 24118 Kiel, Germany.
Veterinary Microbiology (Impact Factor: 2.51). 08/2005; 108(3-4):187-98. DOI: 10.1016/j.vetmic.2005.04.009
Source: PubMed


A Monte Carlo simulation has been developed to describe the spread of classical swine fever virus between farms within a certain region. The data of the farms can be imported and considered individually. Transmission occurs via the infection routes direct animal and indirect person and vehicle contact, as well as by contaminated sperm and local spread. Parameters, such as incubation period and probability of detection, can be varied by the user and their impact on disease spread can be studied. The control measures stamping-out, movement control and pre-emptive slaughter in circular restriction areas as well as contact tracing can be applied and their effect on disease spread can thus be analysed. The numbers of culled and restricted farms and animals per epidemic and per day within an epidemic, the epidemic duration and the total length of restrictions per restricted farm are given. In an example, simulation runs were performed under the condition of application of all four-control measures. Because no real farm data were available, a test area was generated stochastically with a farm density of 1.3 farms/km(2). The distributions of the number of infected farms per epidemic and the epidemic length are shown.

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    • "As specified in Section 2.3, a contaminated farm is generally detected by the observation of the clinical signs of its pigs (i.e., the farm is in state C f ) [19]. This detection is simulated differently before and after detecting of the first contaminated farm (i.e., the index case): • Before detecting the index case: For each farm in the state C f , the probability of detection per day is modeled by using a Bernoulli distribution with mean 0.03 [15]. • After detecting of the index case: As the awareness of the farmers and private veterinarians increase, the daily probability of detection of a farm in the state C f is increased and is simulated by considering a Bernoulli distribution with mean 0.06 [15]. "
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    ABSTRACT: Classical Swine Fever is a viral disease of pigs that causes severe restrictions on the movement of pigs and pig products in the affected areas. The knowledge of its spread patterns and risk factors would help to implement specific measures for controlling future outbreaks. In this article, we describe in detail a spatial hybrid model, called Be-FAST, based on the combination of a stochastic Individual-Based model (modeling the interactions between the farms, considered as individuals) for between-farm spread with a Susceptible-Infected model for within-farm spread, to simulate the spread of this disease and identify risk zones in a given region. First, we focus on the mathematical formulation of each component of the model. Then, in order to validate Be-FAST, we perform various numerical experiments considering the Spanish province of Segovia. Obtained results are compared with the ones given by two other Individual-Based models and real outbreaks data from Segovia and The Netherlands.
    Annals of Operations Research 08/2014; 219:25-47. DOI:10.1007/s10479-012-1257-4 · 1.22 Impact Factor
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    • "For this increased intra-herd spread, full infectivity of all herds 7 days after infection was assumed (Table 5). Comparable assumptions of high transmission potential of CSFV were made in other CSF simulation models to allow for more obvious differences between control strategies (Karsten et al., 2005). The module allowing airborne (long-distance, winddriven ) transmission was not used as there is no scientific evidence for long-distance airborne spread of CSFV (Dewulf et al., 2000; Ribbens et al., 2004; Boklund et al., 2008). "
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    ABSTRACT: Classical swine fever (CSF) outbreaks may result in huge economic losses to countries with densely populated pig areas (DPLAs). The EU minimum control measures require depopulation of infected farms, movement restrictions, zoning and surveillance (EU Minimum strategy). Emergency vaccination is authorised for DPLAs although the EU Minimum strategy plus culling in a 1-km ring around infected premises is preferred. Nonetheless, vaccination in a 2-km ring has been found equally effective as 1-km ring culling using stochastic modelling. Alternatives control measures (e.g. antiviral agents, in particular small molecule inhibitors of the CSFV replication) are being explored. Hence, the present study was set up to simulate inter-herd CSFV spread when antiviral molecules are supplemented to pig feed in a 1-km ring around infected farms. The effectiveness of the antiviral strategy for containing CSF outbreaks was compared to six other control scenarios including the EU Minimum strategy, the EU preferred policy for DPLAs and the use of 2-km ring vaccination. The InterSpread Plus model was adapted to the 2006 Belgian pig population and outbreak simulations were performed with a fast spreading CSFV strain entering a DPLA in Belgium. Four out of the seven control strategies resulted in outbreaks that were controlled by the end of the simulation period (i.e. 365 days). The distributions of the number of infected herds and the duration of the predicted outbreaks for these four control strategies were not different. This is the first report investigating CSF outbreak containment using antiviral molecules. Although antiviral supplementation was not found to perform any better than some other conventional strategies, such as pre-emptive culling and emergency vaccination, it might be worthwhile considering it further as additional tool in a response to CSF outbreaks.
    Preventive Veterinary Medicine 03/2012; 106(1):34-41. DOI:10.1016/j.prevetmed.2012.03.002 · 2.17 Impact Factor
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    • "Those models intended to simulate the potential spread of CSF into a region in order to identify risk factors, evaluate effective measures to control disease and have a decision support system to better manage real outbreaks. Recently, some models have been developed to simulate the potential spread of CSF into free regions such as Belgium, Germany, Australia and Netherlands [5] [7]. Martinez et al., [9] also described an spatial and stochastic model for Spain by using a commercial available software (InterSpread Plus). "
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    ABSTRACT: Classical swine fever (CSF) is a highly contagious viral disease of pigs and wild boars that causes severe commercial restrictions to the affected countries. The knowledge of spread patterns and risk factors that are involved in the transmission of CSF would help to implement specific measures and to reduce the disease spread in future outbreaks. In this article, we introduce a new spatial hybrid model developed for the spread of CSF. It is based on the combination of a stochastic individual Based model with a Susceptible-Infected model. The coefficients and parameters of the models are estimated using real data.
    Proceedings of the XXI CEDYA, 07/2009: pages 1-8; , ISBN: 978-84-692-6473-7
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