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Andraud M, Rose N. Modelling infectious viral diseases in swine populations: a state of the art. Porcine Health Manag 2020; 6:22. [PMID: 32843990 PMCID: PMC7439688 DOI: 10.1186/s40813-020-00160-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 06/25/2020] [Indexed: 02/06/2023] Open
Abstract
Mathematical modelling is nowadays a pivotal tool for infectious diseases studies, completing regular biological investigations. The rapid growth of computer technology allowed for development of computational tools to address biological issues that could not be unravelled in the past. The global understanding of viral disease dynamics requires to account for all interactions at all levels, from within-host to between-herd, to have all the keys for development of control measures. A literature review was performed to disentangle modelling frameworks according to their major objectives and methodologies. One hundred and seventeen articles published between 1994 and 2020 were found to meet our inclusion criteria, which were defined to target papers representative of studies dealing with models of viral infection dynamics in pigs. A first descriptive analysis, using bibliometric indexes, permitted to identify keywords strongly related to the study scopes. Modelling studies were focused on particular infectious agents, with a shared objective: to better understand the viral dynamics for appropriate control measure adaptation. In a second step, selected papers were analysed to disentangle the modelling structures according to the objectives of the studies. The system representation was highly dependent on the nature of the pathogens. Enzootic viruses, such as swine influenza or porcine reproductive and respiratory syndrome, were generally investigated at the herd scale to analyse the impact of husbandry practices and prophylactic measures on infection dynamics. Epizootic agents (classical swine fever, foot-and-mouth disease or African swine fever viruses) were mostly studied using spatio-temporal simulation tools, to investigate the efficiency of surveillance and control protocols, which are predetermined for regulated diseases. A huge effort was made on model parameterization through the development of specific studies and methodologies insuring the robustness of parameter values to feed simulation tools. Integrative modelling frameworks, from within-host to spatio-temporal models, is clearly on the way. This would allow to capture the complexity of individual biological variabilities and to assess their consequences on the whole system at the population level. This would offer the opportunity to test and evaluate in silico the efficiency of possible control measures targeting specific epidemiological units, from hosts to herds, either individually or through their contact networks. Such decision support tools represent a strength for stakeholders to help mitigating infectious diseases dynamics and limiting economic consequences.
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Affiliation(s)
- M. Andraud
- Anses, French Agency for Food, Environmental and Occupational Health & Safety, Ploufragan-Plouzané-Niort Laboratory, Epidemiology, Health and Welfare research unit, F22440 Ploufragan, France
| | - N. Rose
- Anses, French Agency for Food, Environmental and Occupational Health & Safety, Ploufragan-Plouzané-Niort Laboratory, Epidemiology, Health and Welfare research unit, F22440 Ploufragan, France
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2
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Porphyre T, Correia-Gomes C, Chase-Topping ME, Gamado K, Auty HK, Hutchinson I, Reeves A, Gunn GJ, Woolhouse MEJ. Vulnerability of the British swine industry to classical swine fever. Sci Rep 2017; 7:42992. [PMID: 28225040 PMCID: PMC5320472 DOI: 10.1038/srep42992] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2016] [Accepted: 01/18/2017] [Indexed: 12/03/2022] Open
Abstract
Classical swine fever (CSF) is a notifiable, highly contagious viral disease of swine which results in severe welfare and economic consequences in affected countries. To improve preparedness, it is critical to have some understanding of how CSF would spread should it be introduced. Based on the data recorded during the 2000 epidemic of CSF in Great Britain (GB), a spatially explicit, premises-based model was developed to explore the risk of CSF spread in GB. We found that large outbreaks of CSF would be rare and generated from a limited number of areas in GB. Despite the consistently low vulnerability of the British swine industry to large CSF outbreaks, we identified concerns with respect to the role played by the non-commercial sector of the industry. The model further revealed how various epidemiological features may influence the spread of CSF in GB, highlighting the importance of between-farm biosecurity in preventing widespread dissemination of the virus. Knowledge of factors affecting the risk of spread are key components for surveillance planning and resource allocation, and this work provides a valuable stepping stone in guiding policy on CSF surveillance and control in GB.
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Affiliation(s)
- Thibaud Porphyre
- Epidemiology Research Group, Centre for Immunity, Infection and Evolution, University of Edinburgh, Edinburgh, Scotland, UK
| | - Carla Correia-Gomes
- Epidemiology Research Unit, Future Farming Systems, Scotland's Rural College, Inverness, Scotland, UK
| | - Margo E Chase-Topping
- Epidemiology Research Group, Centre for Immunity, Infection and Evolution, University of Edinburgh, Edinburgh, Scotland, UK
| | - Kokouvi Gamado
- Biomathematics &Statistics Scotland, Edinburgh, Scotland, UK
| | - Harriet K Auty
- Epidemiology Research Unit, Future Farming Systems, Scotland's Rural College, Inverness, Scotland, UK
| | - Ian Hutchinson
- Epidemiology Research Unit, Future Farming Systems, Scotland's Rural College, Inverness, Scotland, UK
| | - Aaron Reeves
- Epidemiology Research Unit, Future Farming Systems, Scotland's Rural College, Inverness, Scotland, UK
| | - George J Gunn
- Epidemiology Research Unit, Future Farming Systems, Scotland's Rural College, Inverness, Scotland, UK
| | - Mark E J Woolhouse
- Epidemiology Research Group, Centre for Immunity, Infection and Evolution, University of Edinburgh, Edinburgh, Scotland, UK
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Yadav S, Olynk Widmar NJ, Weng HY. Modeling Classical Swine Fever Outbreak-Related Outcomes. Front Vet Sci 2016; 3:7. [PMID: 26870741 PMCID: PMC4737915 DOI: 10.3389/fvets.2016.00007] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2015] [Accepted: 01/20/2016] [Indexed: 11/24/2022] Open
Abstract
The study was carried out to estimate classical swine fever (CSF) outbreak-related outcomes, such as epidemic duration and number of infected, vaccinated, and depopulated premises, using defined most likely CSF outbreak scenarios. Risk metrics were established using empirical data to select the most likely CSF outbreak scenarios in Indiana. These scenarios were simulated using a stochastic between-premises disease spread model to estimate outbreak-related outcomes. A total of 19 single-site (i.e., with one index premises at the onset of an outbreak) and 15 multiple-site (i.e., with more than one index premises at the onset of an outbreak) outbreak scenarios of CSF were selected using the risk metrics. The number of index premises in the multiple-site outbreak scenarios ranged from 4 to 32. The multiple-site outbreak scenarios were further classified into clustered (N = 6) and non-clustered (N = 9) groups. The estimated median (5th, 95th percentiles) epidemic duration (days) was 224 (24, 343) in the single-site and was 190 (157, 251) and 210 (167, 302) in the clustered and non-clustered multiple-site outbreak scenarios, respectively. The median (5th, 95th percentiles) number of infected premises was 323 (0, 488) in the single-site outbreak scenarios and was 529 (395, 662) and 465 (295, 640) in the clustered and non-clustered multiple-site outbreak scenarios, respectively. Both the number and spatial distributions of the index premises affected the outcome estimates. The results also showed the importance of implementing vaccinations to accommodate depopulation in the CSF outbreak controls. The use of routinely collected surveillance data in the risk metrics and disease spread model allows end users to generate timely outbreak-related information based on the initial outbreak’s characteristics. Swine producers can use this information to make an informed decision on the management of swine operations and continuity of business, so that potential losses could be minimized during a CSF outbreak. Government authorities might use the information to make emergency preparedness plans for CSF outbreak control.
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Affiliation(s)
- Shankar Yadav
- Department of Comparative Pathobiology, Purdue University , West Lafayette, IN , USA
| | | | - Hsin-Yi Weng
- Department of Comparative Pathobiology, Purdue University , West Lafayette, IN , USA
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Probert WJM, Shea K, Fonnesbeck CJ, Runge MC, Carpenter TE, Dürr S, Garner MG, Harvey N, Stevenson MA, Webb CT, Werkman M, Tildesley MJ, Ferrari MJ. Decision-making for foot-and-mouth disease control: Objectives matter. Epidemics 2015; 15:10-9. [PMID: 27266845 DOI: 10.1016/j.epidem.2015.11.002] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2015] [Revised: 11/03/2015] [Accepted: 11/25/2015] [Indexed: 11/18/2022] Open
Abstract
Formal decision-analytic methods can be used to frame disease control problems, the first step of which is to define a clear and specific objective. We demonstrate the imperative of framing clearly-defined management objectives in finding optimal control actions for control of disease outbreaks. We illustrate an analysis that can be applied rapidly at the start of an outbreak when there are multiple stakeholders involved with potentially multiple objectives, and when there are also multiple disease models upon which to compare control actions. The output of our analysis frames subsequent discourse between policy-makers, modellers and other stakeholders, by highlighting areas of discord among different management objectives and also among different models used in the analysis. We illustrate this approach in the context of a hypothetical foot-and-mouth disease (FMD) outbreak in Cumbria, UK using outputs from five rigorously-studied simulation models of FMD spread. We present both relative rankings and relative performance of controls within each model and across a range of objectives. Results illustrate how control actions change across both the base metric used to measure management success and across the statistic used to rank control actions according to said metric. This work represents a first step towards reconciling the extensive modelling work on disease control problems with frameworks for structured decision making.
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Affiliation(s)
- William J M Probert
- Center for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, University Park, PA, United States; Department of Biology and Intercollege Graduate Degree Program in Ecology, 208 Mueller Laboratory, The Pennsylvania State University, University Park, PA, United States; School of Veterinary Medicine and Science, University of Nottingham, Leicestershire LE12 5RD, United Kingdom.
| | - Katriona Shea
- Center for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, University Park, PA, United States; Department of Biology and Intercollege Graduate Degree Program in Ecology, 208 Mueller Laboratory, The Pennsylvania State University, University Park, PA, United States
| | | | - Michael C Runge
- US Geological Survey, Patuxent Wildlife Research Center, 12100 Beech Forest Rd, Laurel, MD, United States
| | - Tim E Carpenter
- EpiCentre, Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Palmerston North, New Zealand
| | - Salome Dürr
- Veterinary Public Health Institute, University of Bern, Bern, Switzerland
| | - M Graeme Garner
- Animal Health Policy Branch, Australian Government, Department of Agriculture, GPO Box 858, Canberra 2601, ACT, Australia
| | - Neil Harvey
- Department of Computing and Information Science, University of Guelph, Guelph, ON, Canada N1G 2W1
| | - Mark A Stevenson
- Faculty of Veterinary Science, University of Melbourne, Melbourne, VIC, Australia
| | - Colleen T Webb
- Department of Biology, Colorado State University, Fort Collins, CO, United States
| | - Marleen Werkman
- Central Veterinary Institute, Wageningen University and Research Centre, Houtribweg 39, 8221 RA Lelystad, The Netherlands; School of Veterinary Medicine and Science, University of Nottingham, Leicestershire LE12 5RD, United Kingdom
| | - Michael J Tildesley
- School of Veterinary Medicine and Science, University of Nottingham, Leicestershire LE12 5RD, United Kingdom
| | - Matthew J Ferrari
- Center for Infectious Disease Dynamics, Department of Biology, Eberly College of Science, The Pennsylvania State University, University Park, PA, United States
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Molecular characterization of E2 glycoprotein of classical swine fever virus: adaptation and propagation in porcine kidney cells. In Vitro Cell Dev Biol Anim 2015; 51:441-6. [DOI: 10.1007/s11626-014-9859-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2014] [Accepted: 12/14/2014] [Indexed: 10/24/2022]
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6
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Weesendorp E, Backer J, Loeffen W. Quantification of different classical swine fever virus transmission routes within a single compartment. Vet Microbiol 2014; 174:353-361. [DOI: 10.1016/j.vetmic.2014.10.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2014] [Revised: 10/24/2014] [Accepted: 10/27/2014] [Indexed: 11/25/2022]
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7
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Guo X, Claassen GDH, Oude Lansink AGJM, Loeffen W, Saatkamp HW. Economic Analysis of Classical Swine Fever Surveillance in the Netherlands. Transbound Emerg Dis 2014; 63:296-313. [DOI: 10.1111/tbed.12274] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2014] [Indexed: 11/30/2022]
Affiliation(s)
- X. Guo
- Business Economics Group; Department of Social Sciences; Wageningen University; Wageningen The Netherlands
| | - G. D. H. Claassen
- Operations Research and Logistics Group; Department of Social Sciences; Wageningen University; Wageningen The Netherlands
| | - A. G. J. M. Oude Lansink
- Business Economics Group; Department of Social Sciences; Wageningen University; Wageningen The Netherlands
| | - W. Loeffen
- Virology Department; Central Veterinary Institute of Wageningen UR (CVI); Lelystad The Netherlands
| | - H. W. Saatkamp
- Business Economics Group; Department of Social Sciences; Wageningen University; Wageningen The Netherlands
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Guo X, Claassen G, Oude Lansink A, Saatkamp H. A conceptual framework for economic optimization of single hazard surveillance in livestock production chains. Prev Vet Med 2014; 114:188-200. [DOI: 10.1016/j.prevetmed.2014.02.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2013] [Revised: 01/23/2014] [Accepted: 02/05/2014] [Indexed: 10/25/2022]
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9
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Boender GJ, van den Hengel R, Roermund HJWV, Hagenaars TJ. The influence of between-farm distance and farm size on the spread of classical swine fever during the 1997-1998 epidemic in The Netherlands. PLoS One 2014; 9:e95278. [PMID: 24748233 PMCID: PMC3991596 DOI: 10.1371/journal.pone.0095278] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2013] [Accepted: 03/25/2014] [Indexed: 11/18/2022] Open
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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Affiliation(s)
- Gert Jan Boender
- Department of Epidemiology, Crisis organization and Diagnostics, Central Veterinary Institute (CVI) of Wageningen, Lelystad, The Netherlands
- * E-mail:
| | - Rob van den Hengel
- Department of Epidemiology, Crisis organization and Diagnostics, Central Veterinary Institute (CVI) of Wageningen, Lelystad, The Netherlands
| | - Herman J. W. van. Roermund
- Department of Epidemiology, Crisis organization and Diagnostics, Central Veterinary Institute (CVI) of Wageningen, Lelystad, The Netherlands
| | - Thomas J. Hagenaars
- Department of Epidemiology, Crisis organization and Diagnostics, Central Veterinary Institute (CVI) of Wageningen, Lelystad, The Netherlands
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10
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Pongsumpun P, Tang IM. Dynamics of a new strain of the H1N1 influenza A virus incorporating the effects of repetitive contacts. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2014; 2014:487974. [PMID: 24744816 PMCID: PMC3973015 DOI: 10.1155/2014/487974] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2013] [Revised: 12/22/2013] [Accepted: 01/01/2014] [Indexed: 11/18/2022]
Abstract
The respiratory disease caused by the Influenza A Virus is occurring worldwide. The transmission for new strain of the H1N1 Influenza A virus is studied by formulating a SEIQR (susceptible, exposed, infected, quarantine, and recovered) model to describe its spread. In the present model, we have assumed that a fraction of the infected population will die from the disease. This changes the mathematical equations governing the transmission. The effect of repetitive contact is also included in the model. Analysis of the model by using standard dynamical modeling method is given. Conditions for the stability of equilibrium state are given. Numerical solutions are presented for different values of parameters. It is found that increasing the amount of repetitive contacts leads to a decrease in the peak numbers of exposed and infectious humans. A stability analysis shows that the solutions are robust.
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Affiliation(s)
- Puntani Pongsumpun
- Department of Mathematics, Faculty of Science, King Mongkut's Institute of Technology Ladkrabang, Chalongkrung Road, Ladkrabang, Bangkok 10520, Thailand
| | - I-Ming Tang
- Department of Mathematics, Faculty of Science, Silpakorn University, Nakhon Pathom 73000, Thailand
- Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
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11
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The potential of antiviral agents to control classical swine fever: a modelling study. Antiviral Res 2013; 99:245-50. [PMID: 23827097 DOI: 10.1016/j.antiviral.2013.06.013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2013] [Revised: 06/20/2013] [Accepted: 06/21/2013] [Indexed: 11/20/2022]
Abstract
Classical swine fever (CSF) represents a continuous threat to pig populations that are free of disease without vaccination. When CSF virus is introduced, the minimal control strategy imposed by the EU is often insufficient to mitigate the epidemic. Additional measures such as preemptive culling encounter ethical objections, whereas emergency vaccination leads to prolonged export restrictions. Antiviral agents, however, provide instantaneous protection without inducing an antibody response. The use of antiviral agents to contain CSF epidemics is studied with a model describing within- and between-herd virus transmission. Epidemics are simulated in a densely populated livestock area in The Netherlands, with farms of varying sizes and pig types (finishers, piglets and sows). Our results show that vaccination and/or antiviral treatment in a 2 km radius around an infected herd is more effective than preemptive culling in a 1 km radius. However, the instantaneous but temporary protection provided by antiviral treatment is slightly less effective than the delayed but long-lasting protection offered by vaccination. Therefore, the most effective control strategy is to vaccinate animals when allowed (finishers and piglets) and to treat with antiviral agents when vaccination is prohibited (sows). As independent control measure, antiviral treatment in a 1 km radius presents an elevated risk of epidemics running out of control. A 2 km control radius largely eliminates this risk.
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12
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Evaluation of control and surveillance strategies for classical swine fever using a simulation model. Prev Vet Med 2012; 108:73-84. [PMID: 22858424 DOI: 10.1016/j.prevetmed.2012.07.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2011] [Revised: 07/06/2012] [Accepted: 07/07/2012] [Indexed: 11/23/2022]
Abstract
Classical swine fever (CSF) outbreaks can cause enormous losses in naïve pig populations. How to best minimize the economic damage and number of culled animals caused by CSF is therefore an important research area. The baseline CSF control strategy in the European Union and Switzerland consists of culling all animals in infected herds, movement restrictions for animals, material and people within a given distance to the infected herd and epidemiological tracing of transmission contacts. Additional disease control measures such as pre-emptive culling or vaccination have been recommended based on the results from several simulation models; however, these models were parameterized for areas with high animal densities. The objective of this study was to explore whether pre-emptive culling and emergency vaccination should also be recommended in low- to moderate-density areas such as Switzerland. Additionally, we studied the influence of initial outbreak conditions on outbreak severity to improve the efficiency of disease prevention and surveillance. A spatial, stochastic, individual-animal-based simulation model using all registered Swiss pig premises in 2009 (n=9770) was implemented to quantify these relationships. The model simulates within-herd and between-herd transmission (direct and indirect contacts and local area spread). By varying the four parameters (a) control measures, (b) index herd type (breeding, fattening, weaning or mixed herd), (c) detection delay for secondary cases during an outbreak and (d) contact tracing probability, 112 distinct scenarios were simulated. To assess the impact of scenarios on outbreak severity, daily transmission rates were compared between scenarios. Compared with the baseline strategy (stamping out and movement restrictions) vaccination and pre-emptive culling neither reduced outbreak size nor duration. Outbreaks starting in a herd with weaning piglets or fattening pigs caused higher losses regarding to the number of culled premises and were longer lasting than those starting in the two other index herd types. Similarly, larger transmission rates were estimated for these index herd type outbreaks. A longer detection delay resulted in more culled premises and longer duration and better transmission tracing increased the number of short outbreaks. Based on the simulation results, baseline control strategies seem sufficient to control CSF in low-medium animal-dense areas. Early detection of outbreaks is crucial and risk-based surveillance should be focused on weaning piglet and fattening pig premises.
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Backer JA, Brouwer H, van Schaik G, van Roermund HJW. Using mortality data for early detection of Classical Swine Fever in The Netherlands. Prev Vet Med 2011; 99:38-47. [PMID: 21081252 DOI: 10.1016/j.prevetmed.2010.10.008] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2009] [Revised: 10/14/2010] [Accepted: 10/16/2010] [Indexed: 10/18/2022]
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.
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Affiliation(s)
- J A Backer
- Department of Epidemiology, Crisis & Diagnostics, Central Veterinary Institute of Wageningen UR, Lelystad, The Netherlands.
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14
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Management and control program for suppression and eradication of classical swine fever in Serbia. ACTA VET-BEOGRAD 2011. [DOI: 10.2298/avb1103295n] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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15
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Stegeman A, Bouma A, de Jong MCM. Use of epidemiologic models in the control of highly pathogenic avian influenza. Avian Dis 2010; 54:707-12. [PMID: 20521719 DOI: 10.1637/8821-040209-review.1] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
In the past decades, mathematical models have become more and more accepted as a tool to develop surveillance programs and to evaluate the efficacy of intervention measures for the control of infectious diseases such as highly pathogenic avian influenza. Predictive models are used to simulate the effect of various control measures on the course of an epidemic; analytical models are used to analyze data from outbreaks or from experiments. A key parameter in both types of models is the reproductive ratio, which indicates whether virus can be transmitted in the population, resulting in an epidemic, or not. Parameters obtained from real data using the analytical models can subsequently be used in predictive models to evaluate control strategies or surveillance programs. Examples of the use of these models are described here.
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Affiliation(s)
- Arjan Stegeman
- Faculty of Veterinary Medicine, Department of Farm Animal Health, Utrecht University, Yalelaan 7, 3584 CL, Utrecht, The Netherlands.
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Spekreijse D, Bouma A, Stegeman JA, Koch G, de Jong MCM. The effect of inoculation dose of a highly pathogenic avian influenza virus strain H5N1 on the infectiousness of chickens. Vet Microbiol 2010; 147:59-66. [PMID: 20619974 DOI: 10.1016/j.vetmic.2010.06.012] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2010] [Revised: 06/01/2010] [Accepted: 06/14/2010] [Indexed: 11/27/2022]
Abstract
Highly pathogenic avian influenza is of major concern for the poultry industry, as the virus can spread rapidly in and between flocks, causing high mortality and severe economic losses. The aim of this study was to determine the probability of infection and to determine dose-dependent virus transmission (direct transmission) for various inoculation doses. Two transmission experiments with pair-wise housed layer type chickens were performed, in which one bird per pair was inoculated with an HPAI H5N1 virus and the other contact-exposed. Various inoculation doses were used to determine the susceptibility (ID(50)), and possible relation between ID(50), and infectiousness, expressed as the amount of virus shedding and the probability of contact birds becoming infected. The infectious H5N1 dose (CID(50)) in this study was an estimated 10(2.5) egg infectious dose (EID(50))(.) Increasing the dose increased the probability of infection but survival from infection was independent of dose. In addition, increasing the dose decreased the mean latent period in the inoculated chickens significantly. This could be important for determining the time of onset of infection in a flock and thus allowing more accurate identification of the source of infection. Moreover, the amount of virus shed in trachea and cloaca by the inoculated chickens in the time between inoculation and contact infection, also differed between the various dose groups. Despite differences in latent period and virus shedding, the transmission rate parameter β and reproduction ratio R(0) did not differ significantly between the various dose groups. This implies that in this experiment the amount of virus shedding is not a measure to predict transmission or the infectiousness of chickens.
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Affiliation(s)
- D Spekreijse
- Department of Farm Animal Health, Faculty of Veterinary Medicine, University of Utrecht, P.O. Box 80151, 3508 TD Utrecht, The Netherlands.
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Tildesley MJ, Bessell PR, Keeling MJ, Woolhouse MEJ. The role of pre-emptive culling in the control of foot-and-mouth disease. Proc Biol Sci 2009; 276:3239-48. [PMID: 19570791 PMCID: PMC2817163 DOI: 10.1098/rspb.2009.0427] [Citation(s) in RCA: 68] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2009] [Accepted: 06/02/2009] [Indexed: 11/12/2022] Open
Abstract
The 2001 foot-and-mouth disease epidemic was controlled by culling of infectious premises and pre-emptive culling intended to limit the spread of disease. Of the control strategies adopted, routine culling of farms that were contiguous to infected premises caused the most controversy. Here we perform a retrospective analysis of the culling of contiguous premises as performed in 2001 and a simulation study of the effects of this policy on reducing the number of farms affected by disease. Our simulation results support previous studies and show that a national policy of contiguous premises (CPs) culling leads to fewer farms losing livestock. The optimal national policy for controlling the 2001 epidemic is found to be the targeting of all contiguous premises, whereas for localized outbreaks in high animal density regions, more extensive fixed radius ring culling is optimal. Analysis of the 2001 data suggests that the lowest-risk CPs were generally prioritized for culling, however, even in this case, the policy is predicted to be effective. A sensitivity analysis and the development of a spatially heterogeneous policy show that the optimal culling level depends upon the basic reproductive ratio of the infection and the width of the dispersal kernel. These analyses highlight an important and probably quite general result: optimal control is highly dependent upon the distance over which the pathogen can be transmitted, the transmission rate of infection and local demography where the disease is introduced.
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Affiliation(s)
- Michael J Tildesley
- Centre for Infectious Diseases, University of Edinburgh, Ashworth Laboratories, Kings Buildings, Edinburgh EH9 3JT, UK.
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Quantification of horizontal transmission of Salmonella enterica serovar Enteritidis bacteria in pair-housed groups of laying hens. Appl Environ Microbiol 2009; 75:6361-6. [PMID: 19666725 DOI: 10.1128/aem.00961-09] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
An important source of human salmonellosis is the consumption of table eggs contaminated with Salmonella enterica serovar Enteritidis. Optimization of the various surveillance programs currently implemented to reduce human exposure requires knowledge of the dynamics of S. Enteritidis infection within flocks. The aim of this study was to provide parameter estimates for a transmission model of S. Enteritidis in laying-type chicken flocks. An experiment was carried out with 60 pairs of laying hens. Per pair, one hen was inoculated with S. Enteritidis and the other was contact exposed. After inoculation, cloacal swab samples from all hens were collected over 18 days and tested for the presence of S. Enteritidis. On the basis of this test, it was determined if and when each contact-exposed hen became colonized. A transmission model including a latency period of 1 day and a slowly declining infectivity level was fitted. The mean initial transmission rate was estimated to be 0.47 (95% confidence interval [CI], 0.30 to 0.72) per day. The reproduction number R(0), the average number of hens infected by one colonized hen in a susceptible population, was estimated to be 2.8 (95% CI, 1.9 to 4.2). The generation time, the average time between colonization of a "primary" hen and colonization of contact-exposed hens, was estimated to be 7.0 days (95% CI, 5.0 to 11.6 days). Simulations using these parameters showed that a flock of 20,000 hens would reach a maximum colonization level of 92% within 80 days after colonization of the first hen. These results can be used, for example, to evaluate the effectiveness of control and surveillance programs and to optimize these programs in a cost-benefit analysis.
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Animal health safety of fresh meat derived from pigs vaccinated against Classic Swine Fever. EFSA J 2009. [DOI: 10.2903/j.efsa.2009.933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
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Foot and mouth disease virus transmission during the incubation period of the disease in piglets, lambs, calves, and dairy cows. Prev Vet Med 2009; 88:158-63. [DOI: 10.1016/j.prevetmed.2008.09.001] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2008] [Revised: 07/04/2008] [Accepted: 09/01/2008] [Indexed: 11/18/2022]
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Backer JA, Hagenaars TJ, van Roermund HJW, de Jong MCM. Modelling the effectiveness and risks of vaccination strategies to control classical swine fever epidemics. J R Soc Interface 2008; 6:849-61. [PMID: 19054739 DOI: 10.1098/rsif.2008.0408] [Citation(s) in RCA: 52] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
In a recent update of the Dutch contingency plan for controlling outbreaks of classical swine fever (CSF), emergency vaccination is preferred to large-scale pre-emptive culling. This policy change raised two questions: can emergency vaccination be as effective as pre-emptive culling, and what are the implications for showing freedom of infection? Here, we integrate quantitative information available on CSF virus transmission and vaccination effects into a stochastic mathematical model that describes the transmission dynamics at the level of animals, farms and livestock areas. This multilevel approach connects individual-level interventions to large-scale effects. Using this model, we compare the performance of five different control strategies applied to hypothetical CSF epidemics in The Netherlands and, for each of these strategies, we study the properties of three different screening scenarios to show freedom of infection. We find that vaccination in a ring of 2 km radius around a detected infection source is as effective as ring culling in a 1 km radius. Feasible screening scenarios, adapted to the use of emergency vaccination, can reduce the enhanced risks of (initially) undetected farm outbreaks by targeting vaccinated farms. Altogether, our results suggest that emergency vaccination against CSF can be equally effective and safe as pre-emptive culling.
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Affiliation(s)
- Jantien A Backer
- Quantitative Veterinary Epidemiology and Risk Analysis, Division of Virology, Central Veterinary Institute of Wageningen UR, Lelystad, The Netherlands.
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De Vos CJ, Saatkamp HW, Huirne RBM. Cost-effectiveness of measures to prevent classical swine fever introduction into The Netherlands. Prev Vet Med 2005; 70:235-56. [PMID: 15927286 DOI: 10.1016/j.prevetmed.2005.04.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2004] [Revised: 04/13/2005] [Accepted: 04/05/2005] [Indexed: 11/17/2022]
Abstract
Recent history has demonstrated that classical swine fever (CSF) epidemics can incur high economic losses, especially for exporting countries that have densely populated pig areas and apply a strategy of non-vaccination, such as The Netherlands. Introduction of CSF virus (CSFV) remains a continuing threat to the pig production sector in The Netherlands. Reducing the annual probability of CSFV introduction (P(CSFV)) by preventive measures is therefore of utmost importance. The choice of preventive measures depends not only on the achieved reduction of the annual P(CSFV), but also on the expenditures required for implementing these measures. The objective of this study was to explore the cost-effectiveness of tactical measures aimed at the prevention of CSFV introduction into The Netherlands. For this purpose for each measure (i) model calculations were performed with a scenario tree model for CSFV introduction and (ii) its annual cost was estimated. The cost-effectiveness was then determined as the reduction of the annual P(CSFV) achieved by each preventive measure (DeltaP) divided by the annual cost of implementing that measure (DeltaC). The measures analysed reduce the P(CSFV) caused by import or export of pigs. Results showed that separation of national and international transport of pigs is the most cost-effective measure, especially when risk aversion is assumed. Although testing piglets and breeding pigs by a quick and reliable PCR also had a high cost-effectiveness ratio, this measure is not attractive due to the high cost per pig imported. Besides, implementing such a measure is not allowed under current EU law, as it is trade restrictive.
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Affiliation(s)
- C J De Vos
- Business Economics, Department of Social Sciences, Wageningen University, Hollandseweg 1, 6706 KN Wageningen, The Netherlands.
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Klinkenberg D, Nielen M, Mourits MCM, de Jong MCM. The effectiveness of classical swine fever surveillance programmes in The Netherlands. Prev Vet Med 2005; 67:19-37. [PMID: 15698906 DOI: 10.1016/j.prevetmed.2004.10.003] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2004] [Revised: 10/21/2004] [Accepted: 10/21/2004] [Indexed: 11/23/2022]
Abstract
Consequences of classical swine fever (CSF) epidemics depend on the control measures, but also on the number of infected herds at the end of the high-risk period (HRP). Surveillance programmes aim to keep this number as low as possible, so the effectiveness of surveillance programmes can be measured by the number of infected herds at the end of the HRP. In this paper, an evaluation of the effectiveness of the following five Dutch CSF surveillance programmes is presented: (1) routine gross pathology of severely diseased pigs; (2) routine virological tests of tonsils of all pigs, submitted under 1; (3) daily clinical observation by the farmer; (4) periodic clinical inspection by a veterinarian; (5) leucocyte counts in blood samples from diseased animals on a herd where antimicrobial 'group therapy' is started. The evaluation was done by a modelling study, in which virus transmission, disease development, and actions and diagnostic tests in surveillance programmes were simulated. Also, the yearly costs of the programmes were calculated, and direct costs of CSF epidemics were related to the number of infected herds at the end of the HRP. It appeared that the current Dutch surveillance programmes, without the leucocyte counts, keep the number of infected herds at the end of the HRP below 20 with 95% probability. Leaving out the most-expensive programme of periodic inspection (12.5M per year) does not change this result - indicating that (for CSF surveillance) the programme could well be stopped. If the leucocyte programme, which is currently not effective due to the low sample submission rate, optimally were applied, the 95th percentile could be reduced to 10 infected herds. However, whether application is beneficial is unclear, because of uncertainty of the economic benefits due to the many expected false-positive herds each year.
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Affiliation(s)
- D Klinkenberg
- Quantitative Veterinary Epidemiology, Animal Sciences Group, P.O. Box 65, 8200 AB Lelystad, The Netherlands.
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Trapman P, Meester R, Heesterbeek H. A branching model for the spread of infectious animal diseases in varying environments. J Math Biol 2004; 49:553-76. [PMID: 15565446 PMCID: PMC7080114 DOI: 10.1007/s00285-004-0267-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2003] [Revised: 11/14/2003] [Indexed: 11/25/2022]
Abstract
This paper is concerned with a stochastic model, describing outbreaks of infectious diseases that have potentially great animal or human health consequences, and which can result in such severe economic losses that immediate sets of measures need to be taken to curb the spread. During an outbreak of such a disease, the environment that the infectious agent experiences is therefore changing due to the subsequent control measures taken. In our model, we introduce a general branching process in a changing (but not random) environment. With this branching process, we estimate the probability of extinction and the expected number of infected individuals for different control measures. We also use this branching process to calculate the generating function of the number of infected individuals at any given moment. The model and methods are designed using important infections of farmed animals, such as classical swine fever, foot-and-mouth disease and avian influenza as motivating examples, but have a wider application, for example to emerging human infections that lead to strict quarantine of cases and suspected cases (e.g. SARS) and contact and movement restrictions.
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Affiliation(s)
- Pieter Trapman
- Faculty of Veterinary Medicine, Utrecht University, Yalelaan 7, 3584 Utrecht CL, The Netherlands.
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Abstract
There are two types of classical swine fever vaccines available: the classical live and the recently developed E2 subunit vaccines. The live Chinese strain vaccine is the most widely used. After a single vaccination, it confers solid immunity within a few days that appears to persist lifelong. The E2 subunit vaccine induces immunity from approximately 10-14 days after a single vaccination. The immunity may persist for more than a year, but is then not complete. The Chinese strain vaccine may establish a strong herd immunity 1-2 weeks earlier than the E2 vaccine. The ability of the Chinese vaccine strain to prevent congenital infection has not been reported, but the E2 subunit vaccine does not induce complete protection against congenital infection. Immunological mechanisms that underlie the protective immunity are still to be elucidated. Both types of vaccine are considered to be safe. A great advantage of the E2 subunit vaccine is that it allows differentiation of infected pigs from vaccinated pigs and is referred to as a DIVA vaccine. However, the companion diagnostic E(rns) ELISA to actually make that differentiation should be improved. Many approaches to develop novel vaccines have been described, but none of these is likely to result in a new DIVA vaccine reaching the market in the next 5-10 years. Countries where classical swine fever is endemic can best control the infection by systematic vaccination campaigns, accompanied by the normal diagnostic procedures and control measures. Oral vaccination of wild boar may contribute to lowering the incidence of classical swine fever, and consequently diminishing the threat of virus introduction into domestic pigs. Free countries should not vaccinate and should be highly alert to rapidly diagnose any new outbreak. Once a new introduction of classical swine fever virus in dense pig areas has been confirmed, an emergency vaccination programme should be immediately instituted, for maximum benefit. The question is whether the time is ripe to seriously consider global eradication of classical swine fever virus.
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Affiliation(s)
- J T van Oirschot
- Virus Discovery Unit, ID-Lelystad, PO Box 65, 8200 AB, Lelystad, The Netherlands.
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