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van Schaik G, Hostens M, Faverjon C, Jensen DB, Kristensen AR, Ezanno P, Frössling J, Dórea F, Jensen BB, Carmo LP, Steeneveld W, Rushton J, Gilbert W, Bearth A, Siegrist M, Kaler J, Ripperger J, Siehler J, de Wit S, Garcia-Morante B, Segalés J, Pardon B, Bokma J, Nielen M. The DECIDE project: from surveillance data to decision-support for farmers and veterinarians. OPEN RESEARCH EUROPE 2023; 3:82. [PMID: 38778904 PMCID: PMC11109551 DOI: 10.12688/openreseurope.15988.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 05/10/2023] [Indexed: 05/25/2024]
Abstract
Farmers, veterinarians and other animal health managers in the livestock sector are currently missing sufficient information on prevalence and burden of contagious endemic animal diseases. They need adequate tools for risk assessment and prioritization of control measures for these diseases. The DECIDE project develops data-driven decision-support tools, which present (i) robust and early signals of disease emergence and options for diagnostic confirmation; and (ii) options for controlling the disease along with their implications in terms of disease spread, economic burden and animal welfare. DECIDE focuses on respiratory and gastro-intestinal syndromes in the three most important terrestrial livestock species (pigs, poultry, cattle) and on reduced growth and mortality in two of the most important aquaculture species (salmon and trout). For each of these, we (i) identify the stakeholder needs; (ii) determine the burden of disease and costs of control measures; (iii) develop data sharing frameworks based on federated data access and meta-information sharing; (iv) build multivariate and multi-level models for creating early warning systems; and (v) rank interventions based on multiple criteria. Together, all of this forms decision-support tools to be integrated in existing farm management systems wherever possible and to be evaluated in several pilot implementations in farms across Europe. The results of DECIDE lead to improved use of surveillance data and evidence-based decisions on disease control. Improved disease control is essential for a sustainable food chain in Europe with increased animal health and welfare and that protects human health.
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Affiliation(s)
- Gerdien van Schaik
- Department of Population Health Sciences, Universiteit Utrecht, Utrecht, 3508TD, The Netherlands
- Royal GD, Deventer, The Netherlands
| | - Miel Hostens
- Department of Population Health Sciences, Universiteit Utrecht, Utrecht, 3508TD, The Netherlands
- Laboratory for Animal Nutrition and Animal Product Quality (Lanupro), Department of Animal Sciences and Aquatic Ecology, Ghent University, Gent, Belgium
| | | | - Dan B. Jensen
- Department of Veterinary and Animal Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anders R. Kristensen
- Department of Veterinary and Animal Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Jenny Frössling
- Department of Disease Control and Epidemiology, National Veterinary Institute, Uppsala, Sweden
| | - Fernanda Dórea
- Department of Disease Control and Epidemiology, National Veterinary Institute, Uppsala, Sweden
| | - Britt-Bang Jensen
- Section for Epidemiology, Norwegian Veterinary Institute, Oslo, Norway
| | - Luis Pedro Carmo
- Section for Epidemiology, Norwegian Veterinary Institute, Oslo, Norway
| | - Wilma Steeneveld
- Department of Population Health Sciences, Universiteit Utrecht, Utrecht, 3508TD, The Netherlands
| | - Jonathan Rushton
- Institute of Infection and Global Health, University of Liverpool, Liverpool, England, UK
| | - William Gilbert
- Institute of Infection and Global Health, University of Liverpool, Liverpool, England, UK
| | - Angela Bearth
- Department of Health Sciences and Technology, Eidgenossische Technische Hochschule Zurich, Zürich, Zurich, Switzerland
| | - Michael Siegrist
- Department of Health Sciences and Technology, Eidgenossische Technische Hochschule Zurich, Zürich, Zurich, Switzerland
| | - Jasmeet Kaler
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, England, UK
| | | | | | - Sjaak de Wit
- Department of Population Health Sciences, Universiteit Utrecht, Utrecht, 3508TD, The Netherlands
- Royal GD, Deventer, The Netherlands
| | - Beatriz Garcia-Morante
- IRTA Programes de Sanitat i Benestar Animals, Centre de Recerca en Sanitat Animal (CReSA), Universitat Autonoma de Barcelona, Barcelona, Catalonia, Spain
- Unitat Mixta d'Investigació IRTA-UAB en Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Universitat Autonoma de Barcelona, Barcelona, Catalonia, Spain
| | - Joaquim Segalés
- IRTA Programes de Sanitat i Benestar Animals, Centre de Recerca en Sanitat Animal (CReSA), Universitat Autonoma de Barcelona, Barcelona, Catalonia, Spain
- OIE Collaborating Centre for the Research and Control of Emerging and Re-Emerging Swine Diseases in Europe (IRTA-CReSA), Barcelona, Spain
- Departament de Sanitat i Anatomia Animals, Facultat de Veterinària, UAB, Universitat Autonoma de Barcelona, Barcelona, Catalonia, Spain
| | - Bart Pardon
- Department of Internal Medicine, Reproduction and Population Medicine, Ghent University, Gent, Belgium
| | - Jade Bokma
- Department of Internal Medicine, Reproduction and Population Medicine, Ghent University, Gent, Belgium
| | - Mirjam Nielen
- Department of Population Health Sciences, Universiteit Utrecht, Utrecht, 3508TD, The Netherlands
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McManus R, Boden LA, Weir W, Viora L, Barker R, Kim Y, McBride P, Yang S. Thermography for disease detection in livestock: A scoping review. Front Vet Sci 2022; 9:965622. [PMID: 36016809 PMCID: PMC9395652 DOI: 10.3389/fvets.2022.965622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 07/15/2022] [Indexed: 11/21/2022] Open
Abstract
Infra-red thermography (IRT) offers potential opportunities as a tool for disease detection in livestock. Despite considerable research in this area, there are no common standards or protocols for managing IRT parameters in animal disease detection research. In this review, we investigate parameters that are essential to the progression of this tool and make recommendations for their use based on the literature found and the veterinary thermography guidelines from the American Academy of Thermology. We analyzed a defined set of 109 articles concerned with the use of IRT in livestock related to disease and from these articles, parameters for accurate IRT were identified and sorted into the fields of camera-, animal- or environment-related categories to assess the practices of each article in reporting parameters. This review demonstrates the inconsistencies in practice across peer-reviewed articles and reveals that some important parameters are completely unreported while others are incorrectly captured and/or under-represented in the literature. Further to this, our review highlights the lack of measured emissivity values for live animals in multiple species. We present guidelines for the standards of parameters that should be used and reported in future experiments and discuss potential opportunities and challenges associated with using IRT for disease detection in livestock.
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Affiliation(s)
- Rosemary McManus
- Division of Pathology, Public Health and Disease Investigation, School of Veterinary Medicine, College of Medical Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Lisa A. Boden
- Global Academy of Agriculture and Food Systems, The Royal (Dick) School of Veterinary Studies, The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - William Weir
- Division of Pathology, Public Health and Disease Investigation, School of Veterinary Medicine, College of Medical Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Lorenzo Viora
- Scottish Centre for Production Animal Health and Food Safety, School of Veterinary Medicine, College of Medical Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Robert Barker
- School of Physical Sciences, University of Kent, Canterbury, United Kingdom
| | - Yunhyong Kim
- Information Studies Department, School of Humanities, University of Glasgow, Glasgow, United Kingdom
| | - Pauline McBride
- School of Law, University of Glasgow, Glasgow, United Kingdom
| | - Shufan Yang
- School of Computing, Edinburgh Napier University, Edinburgh, United Kingdom
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Dórea FC, Revie CW. Data-Driven Surveillance: Effective Collection, Integration, and Interpretation of Data to Support Decision Making. Front Vet Sci 2021; 8:633977. [PMID: 33778039 PMCID: PMC7994248 DOI: 10.3389/fvets.2021.633977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 02/18/2021] [Indexed: 11/20/2022] Open
Abstract
The biggest change brought about by the “era of big data” to health in general, and epidemiology in particular, relates arguably not to the volume of data encountered, but to its variety. An increasing number of new data sources, including many not originally collected for health purposes, are now being used for epidemiological inference and contextualization. Combining evidence from multiple data sources presents significant challenges, but discussions around this subject often confuse issues of data access and privacy, with the actual technical challenges of data integration and interoperability. We review some of the opportunities for connecting data, generating information, and supporting decision-making across the increasingly complex “variety” dimension of data in population health, to enable data-driven surveillance to go beyond simple signal detection and support an expanded set of surveillance goals.
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Affiliation(s)
- Fernanda C Dórea
- Department of Disease Control and Epidemiology, National Veterinary Institute, Uppsala, Sweden
| | - Crawford W Revie
- Computer and Information Sciences, University of Strathclyde, Glasgow, United Kingdom
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