15
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Estimating the introduction time of highly pathogenic avian influenza into poultry flocks

      research-article

      Read this article at

      ScienceOpenPublisherPMC
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The estimation of farm-specific time windows for the introduction of highly-pathogenic avian influenza (HPAI) virus can be used to increase the efficiency of disease control measures such as contact tracing and may help to identify risk factors for virus introduction. The aims of this research are to (1) develop and test an accurate approach for estimating farm-specific virus introduction windows and (2) evaluate this approach by applying it to 11 outbreaks of HPAI (H5N8) on Dutch commercial poultry farms during the years 2014 and 2016. We used a stochastic simulation model with susceptible, infectious and recovered/removed disease stages to generate distributions for the period from virus introduction to detection. The model was parameterized using data from the literature, except for the within-flock transmission rate, which was estimated from disease-induced mortality data using two newly developed methods that describe HPAI outbreaks using either a deterministic model (A) or a stochastic approach (B). Model testing using simulated outbreaks showed that both method A and B performed well. Application to field data showed that method A could be successfully applied to 8 out of 11 HPAI H5N8 outbreaks and is the most generally applicable one, when data on disease-induced mortality is scarce.

          Related collections

          Most cited references41

          • Record: found
          • Abstract: found
          • Article: not found

          A concordance correlation coefficient to evaluate reproducibility.

          L Lin (1989)
          A new reproducibility index is developed and studied. This index is the correlation between the two readings that fall on the 45 degree line through the origin. It is simple to use and possesses desirable properties. The statistical properties of this estimate can be satisfactorily evaluated using an inverse hyperbolic tangent transformation. A Monte Carlo experiment with 5,000 runs was performed to confirm the estimate's validity. An application using actual data is given.
            • Record: found
            • Abstract: found
            • Article: not found

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

            Approximate Bayesian computation (ABC) methods can be used to evaluate posterior distributions without having to calculate likelihoods. In this paper, we discuss and apply an ABC method based on sequential Monte Carlo (SMC) to estimate parameters of dynamical models. We show that ABC SMC provides 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.
              • Record: found
              • Abstract: found
              • Article: not found

              The Effectiveness of Contact Tracing in Emerging Epidemics

              Background Contact tracing plays an important role in the control of emerging infectious diseases, but little is known yet about its effectiveness. Here we deduce from a generic mathematical model how effectiveness of tracing relates to various aspects of time, such as the course of individual infectivity, the (variability in) time between infection and symptom-based detection, and delays in the tracing process. In addition, the possibility of iteratively tracing of yet asymptomatic infecteds is considered. With these insights we explain why contact tracing was and will be effective for control of smallpox and SARS, only partially effective for foot-and-mouth disease, and likely not effective for influenza. Methods and Findings We investigate contact tracing in a model of an emerging epidemic that is flexible enough to use for most infections. We consider isolation of symptomatic infecteds as the basic scenario, and express effectiveness as the proportion of contacts that need to be traced for a reproduction ratio smaller than 1. We obtain general results for special cases, which are interpreted with respect to the likely success of tracing for influenza, smallpox, SARS, and foot-and-mouth disease epidemics. Conclusions We conclude that (1) there is no general predictive formula for the proportion to be traced as there is for the proportion to be vaccinated; (2) variability in time to detection is favourable for effective tracing; (3) tracing effectiveness need not be sensitive to the duration of the latent period and tracing delays; (4) iterative tracing primarily improves effectiveness when single-step tracing is on the brink of being effective.

                Author and article information

                Contributors
                peter.hobbelen@wur.nl
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                24 July 2020
                24 July 2020
                2020
                : 10
                : 12388
                Affiliations
                [1 ]Wageningen Bioveterinary Research, Houtribweg 39, 8221 RA Lelystad, The Netherlands
                [2 ]ISNI 0000000120346234, GRID grid.5477.1, Department of Farm Animal Health, Faculty of Veterinary Medicine, , Utrecht University, ; Utrecht, The Netherlands
                [3 ]ISNI 0000000090126352, GRID grid.7692.a, Julius Centre for Health Sciences and Primary Care, , University Medical Centre Utrecht, ; Utrecht, The Netherlands
                Author information
                http://orcid.org/0000-0002-2252-9357
                Article
                68623
                10.1038/s41598-020-68623-w
                7381656
                32709965
                3e2d38a2-a97f-49d2-b633-6953fd8fbaae
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 27 March 2019
                : 24 June 2020
                Funding
                Funded by: The Dutch Ministry of Agriculture, Nature and Food Quality
                Award ID: WOT-01-003-068
                Award ID: WOT-01-006-014
                Award ID: WOT-01-001-004
                Award ID: KB-21-006-014
                Award ID: KB-21-006-025
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                viral infection
                Uncategorized
                viral infection

                Comments

                Comment on this article

                Related Documents Log