Simulation analyses to evaluate alternative control strategies for the 2002 foot-and-mouth disease outbreak in the Republic of Korea

Yoon, Hachung; Wee, Sung‐Hwan; Stevenson, M.A.; O’Leary, B.D.; Morris, Roger S.; Hwang, I.-J.; Park, C.-K.; Stern, M.W.

doi:10.1016/j.prevetmed.2005.12.002

Cited by 46 publications

(33 citation statements)

References 10 publications

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“…The output of ISP can include information on the number of farms infected, detected, culled, vaccinated or located in a restriction zone over time. ISP has been used to simulate the spread and control of CSF virus in Denmark (Boklund et al., ) and Belgium (Ribbens, ; Ribbens et al., ), PRRS virus in NZ (Neumann et al., ) and FMD virus in South Korea (Yoon et al., ) and Spain (Martínez‐López et al., ).…”

Section: Model Descriptionmentioning

confidence: 99%

Economic Analysis of HPAI Control in the Netherlands I: Epidemiological Modelling to Support Economic Analysis

Longworth

Mourits

Saatkamp

2012

Transbound Emerg Dis

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Economic analysis of control strategies for contagious diseases is a necessity in the development of contingency plans. Economic impacts arising from epidemics such as highly pathogenic avian influenza (HPAI) consist of direct costs (DC), direct consequential costs (DCC), indirect consequential costs (ICC) and aftermath costs (AC). Epidemiological models to support economic analysis need to provide adequate outputs for these critical economic parameters. Of particular importance for DCC, ICC and AC is the spatial production structure of a region. Spatial simulation models are therefore particularly suited for economic analysis; however, they often require a large number of parameters. The aims of this study are (i) to provide an economic rationale of epidemiological modelling in general, (ii) to provide a transparent description of the parameterization of a spatially based epidemiological model for the analysis of HPAI control in the Netherlands and (iii) to discuss the validity and usefulness of this model for subsequent economic analysis. In the model, HPAI virus transmission occurs via local spread and animal movements. Control mechanisms include surveillance and tracing, movement restrictions and depopulation. Sensitivity analysis of key parameters indicated that the epidemiological outputs with the largest influence on the economic impacts (i.e. epidemic duration and number of farms in the movement restriction zone) were more robust than less influential indicators (i.e. number of infected farms). Economically relevant outputs for strategy comparison were most sensitive to the relative role of the different transmission parameters. The default simulation and results of the sensitivity analysis were consistent with the general outcomes of known HPAI models. Comparison was, however, limited due to the absence of some economically relevant outputs. It was concluded that the model creates economically relevant, adequate and credible output for subsequent use in economic analysis. A detailed economic analysis is presented in a subsequent article.

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Section: Model Descriptionmentioning

confidence: 99%

Economic Analysis of HPAI Control in the Netherlands I: Epidemiological Modelling to Support Economic Analysis

Longworth

Mourits

Saatkamp

2012

Transbound Emerg Dis

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“…In the case of FMD, the most likely time of infection can be estimated on the basis of the oldest clinical lesion in the herd. Such estimations have been used to construct transmission pathways [13,14], understand the pattern of virus excretion [15,16], assess the efficacy of control measures [17], simulate modeling programs [18], and identify the risk factors associated with disease transmission [19]. However, the use of clinical signs is not always feasible because the manifestation of clinical signs is not always obvious; symptoms are less clear in sheep, goats, and deer, for example, than in pigs and cattle [3].…”

Section: Discussionmentioning

confidence: 99%

Estimation of the Infection Window for the 2010/2011 Korean Foot-and-Mouth Disease Outbreak

Yoon

Kim

et al. 2013

Osong Public Health and Research Perspectives

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ObjectivesThis study aims to develop a method for calculating infection time lines for disease outbreaks on farms was developed using the 2010/2011 foot-and-mouth disease (FMD) epidemic in the Republic of Korea.MethodsData on farm demography, the detection date of FMD, the clinical history for the manifestation of lesions, the presence of antibodies against FMD virus (including antibodies against the structural and nonstructural proteins of serotype O), vaccination status (O1 Manisa strain), the number of reactors and information on the slaughter of infected animals were utilized in this method.ResultsBased on estimates of the most likely infection date, a cumulative detection probability that an infected farm would be identified on a specific day was determined. Peak infection was observed between late December and early January, but peak detection occurred in mid-January. The early detection probability was highest for pigs, followed by cattle (dairy, then beef) and small ruminants. Nearly 90% of the infected pig farms were detected by Day 11 post-infection while 13 days were required for detection for both dairy and beef cattle farms, and 21 days were necessary for small ruminant (goat and deer) farms. On average, 8.1 ± 3.1 days passed prior to detecting the presence of FMD virus on a farm. The interval between infection and detection of FMD was inversely associated with the intensity of farming.ConclusionThe results of our study emphasize the importance of intensive clinical inspection, which is the quickest method of detecting FMD infection and minimizing the damage caused by an epidemic.

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“…During the last decade, ISP has been used to simulate the veterinary impact of various epizootic diseases, for instance foot‐and‐mouth disease in the Republic of Korea (Yoon et al., ), CSF in Belgium (Ribbens, ) and Denmark (Boklund et al., ) and avian influenza in NL (Longworth et al., ,b). The suitability of ISP has been extensively discussed by Longworth et al.…”

Section: Methodsmentioning

confidence: 99%

Simulation of Cross-border Impacts Resulting from Classical Swine Fever Epidemics within the Netherlands and Germany

Hop

Mourits

Saatkamp

2014

Transbound Emerg Dis

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The cross-border region of the Netherlands (NL) and the two German states of North Rhine Westphalia (NRW) and Lower Saxony (LS) is a large and highly integrated livestock production area. This region increasingly develops towards a single epidemiological area in which disease introduction is a shared veterinary and, consequently, economic risk. The objectives of this study were to examine classical swine fever (CSF) control strategies' veterinary and direct economic impacts for NL, NRW and LS given the current production structure and to analyse CSF's cross-border causes and impacts within the NL-NRW-LS region. The course of the epidemic was simulated by the use of InterSpread Plus, whereas economic analysis was restricted to calculating disease control costs and costs directly resulting from the control measures applied. Three veterinary control strategies were considered: a strategy based on the minimum EU requirements, a vaccination and a depopulation strategy based on NL and GER's contingency plans. Regardless of the veterinary control strategy, simulated outbreak sizes and durations for 2010 were much smaller than those simulated previously, using data from over 10 years ago. For example, worst-case outbreaks (50th percentile) in NL resulted in 30-40 infected farms and lasted for two to four and a half months; associated direct costs and direct consequential costs ranged from €24.7 to 28.6 million and €11.7 to 26.7 million, respectively. Both vaccination and depopulation strategies were efficient in controlling outbreaks, especially large outbreaks, whereas the EU minimum strategy was especially deficient in controlling worst-case outbreaks. Both vaccination and depopulation strategies resulted in low direct costs and direct consequential costs. The probability of cross-border disease spread was relatively low, and cross-border spread resulted in small, short outbreaks in neighbouring countries. Few opportunities for further cross-border harmonization and collaboration were identified, including the implementation of cross-border regions (free and diseased regions regardless of the border) in case of outbreaks within close proximity of the border, and more and quicker sharing of information across the border. It was expected, however, that collaboration to mitigate the market effects of an epidemic will create more opportunities to lower the impact of CSF outbreaks in a cross-border context.

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Simulation analyses to evaluate alternative control strategies for the 2002 foot-and-mouth disease outbreak in the Republic of Korea

Cited by 46 publications

References 10 publications

Economic Analysis of HPAI Control in the Netherlands I: Epidemiological Modelling to Support Economic Analysis

Economic Analysis of HPAI Control in the Netherlands I: Epidemiological Modelling to Support Economic Analysis

Estimation of the Infection Window for the 2010/2011 Korean Foot-and-Mouth Disease Outbreak

Simulation of Cross-border Impacts Resulting from Classical Swine Fever Epidemics within the Netherlands and Germany

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