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

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          Summary

          Mortality data are routinely collected for many livestock and poultry species, and they are often used for epidemiological purposes, including estimating transmission parameters. In this study, we infer transmission rates for African swine fever virus ( ASFV), an important transboundary disease of swine, using mortality data collected from nine pig herds in the Russian Federation with confirmed outbreaks of ASFV. Parameters in a stochastic model for the transmission of ASFV within a herd were estimated using approximate Bayesian computation. Estimates for the basic reproduction number varied amongst herds, ranging from 4.4 to 17.3. This was primarily a consequence of differences in transmission rate (range: 0.7–2.2), but also differences in the mean infectious period (range: 4.5–8.3 days). We also found differences amongst herds in the mean latent period (range: 5.8–9.7 days). Furthermore, our results suggest that ASFV could be circulating in a herd for several weeks before a substantial increase in mortality is observed in a herd, limiting the usefulness of mortality data as a means of early detection of an outbreak. However, our results also show that mortality data are a potential source of data from which to infer transmission parameters, at least for diseases which cause high mortality.

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          Most cited references31

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          Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems

          Approximate Bayesian computation methods can be used to evaluate posterior distributions without having to calculate likelihoods. In this paper we discuss and apply an approximate Bayesian computation (ABC) method based on sequential Monte Carlo (SMC) to estimate parameters of dynamical models. We show that ABC SMC gives information about the inferability of parameters and model sensitivity to changes in parameters, and tends to perform better than other ABC approaches. The algorithm is applied to several well known biological systems, for which parameters and their credible intervals are inferred. Moreover, we develop ABC SMC as a tool for model selection; given a range of different mathematical descriptions, ABC SMC is able to choose the best model using the standard Bayesian model selection apparatus.
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            Epidemiology of African swine fever virus.

            African swine fever virus used to occur primarily in Africa. There had been occasional incursions into Europe or America which apart from the endemic situation on the island of Sardinia always had been successfully controlled. But following an introduction of the virus in 2007, it now has expanded its geographical distribution into Caucasus and Eastern Europe where it has not been controlled, to date. African swine fever affects domestic and wild pig species, and can involve tick vectors. The ability of the virus to survive within a particular ecosystem is defined by the ecology of its wild host populations and the characteristics of livestock production systems, which influence host and vector species densities and interrelationships. African swine fever has high morbidity in naïve pig populations and can result in very high mortality. There is no vaccine or treatment available. Apart from stamping out and movement control, there are no control measures, thereby potentially resulting in extreme losses for producers. Prevention and control of the infection requires good understanding of its epidemiology, so that targeted measures can be instigated. Copyright © 2012 Elsevier B.V. All rights reserved.
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              Pathogenesis of African swine fever in domestic pigs and European wild boar.

              African swine fever (ASF) is among the most important viral diseases that can affect domestic and feral pigs. Both clinical signs and pathomorphological changes vary considerably depending on strain virulence and host factors. Acute infections with highly virulent virus strains lead to a clinical course that resembles a viral haemorrhagic fever that is characterized by pronounced depletion of lymphoid tissues, apoptosis of lymphocyte subsets, and impairment of haemostasis and immune functions. It is generally accepted that most lesions can be attributed to cytokine-mediated interactions triggered by infected and activated monocytes and macrophages, rather than by virus-induced direct cell damage. Nevertheless, most pathogenetic mechanisms are far from being understood. This review summarizes the current knowledge and discusses implications and research gaps. Copyright © 2012 Elsevier B.V. All rights reserved.
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                Author and article information

                Contributors
                simon.gubbins@pirbright.ac.uk
                Journal
                Transbound Emerg Dis
                Transbound Emerg Dis
                10.1111/(ISSN)1865-1682
                TBED
                Transboundary and Emerging Diseases
                John Wiley and Sons Inc. (Hoboken )
                1865-1674
                1865-1682
                09 November 2017
                April 2018
                : 65
                : 2 ( doiID: 10.1111/tbed.2018.65.issue-2 )
                : e264-e271
                Affiliations
                [ 1 ] Veterinary Epidemiology, Economics and Public Health Group Royal Veterinary College Hatfield Hertfordshire UK
                [ 2 ] The Pirbright Institute Pirbright Surrey UK
                [ 3 ] The Roslin Institute University of Edinburgh Roslin Midlothian UK
                [ 4 ] European Food Safety Authority Parma Italy
                [ 5 ] Federal Research Center for Virology and Microbiology Pokrov Russia
                [ 6 ] College of Veterinary Medicine & Life Sciences City University of Hong Kong Kowloon Hong Kong
                [ 7 ]Present address: École Nationale Vétérinaire de Toulouse Toulouse France
                Author notes
                [*] [* ] Correspondence

                S. Gubbins, The Pirbright Institute, Pirbright, Surrey, UK.

                Email: simon.gubbins@ 123456pirbright.ac.uk

                Author information
                http://orcid.org/0000-0003-0538-4173
                Article
                TBED12748
                10.1111/tbed.12748
                5887875
                29120101
                7536b2be-a988-42b5-8df3-7040a5589a9e
                © 2017 The Authors. Transboundary and Emerging Diseases Published by Blackwell Verlag GmbH

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 16 August 2017
                Page count
                Figures: 2, Tables: 1, Pages: 8, Words: 6015
                Funding
                Funded by: Scottish Government Rural and Environment Science and Analytical Services Division (RESAS)
                Funded by: Centre of Expertise on Animal Disease Outbreaks (EPIC)
                Funded by: Biotechnology and Biological Sciences Research Council
                Award ID: BBS/E/I/00001717
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                tbed12748
                April 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.3.3 mode:remove_FC converted:28.03.2018

                Infectious disease & Microbiology
                approximate bayesian computation,disease control,epidemiology,modelling,mortality data,pigs

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