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Gilbert W, Marsh TL, Chaters G, Jemberu WT, Bruce M, Steeneveld W, Afonso JS, Huntington B, Rushton J. Quantifying cost of disease in livestock: a new metric for the Global Burden of Animal Diseases. Lancet Planet Health 2024; 8:e309-e317. [PMID: 38729670 DOI: 10.1016/s2542-5196(24)00047-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 02/12/2024] [Accepted: 03/20/2024] [Indexed: 05/12/2024]
Abstract
BACKGROUND Increasing awareness of the environmental and public health impacts of expanding and intensifying animal-based food and farming systems creates discord, with the reliance of much of the world's population on animals for livelihoods and essential nutrition. Increasing the efficiency of food production through improved animal health has been identified as a step towards minimising these negative effects without compromising global food security. The Global Burden of Animal Diseases (GBADs) programme aims to provide data and analytical methods to support positive change in animal health across all livestock and aquaculture animal populations. METHODS In this study, we present a metric that begins the process of disease burden estimation by converting the physical consequences of disease on animal performance to farm-level costs of disease, and calculates a metric termed the Animal Health Loss Envelope (AHLE) via comparison between the status quo and a disease-free ideal. An example calculation of the AHLE metric for meat production from broiler chickens is provided. FINDINGS The AHLE presents the direct financial costs of disease at farm-level for all causes by estimating losses and expenditure in a given farming system. The general specification of the model measures productivity change at farm-level and provides an upper bound on productivity change in the absence of disease. On its own, it gives an indication of the scale of total disease cost at farm-level. INTERPRETATION The AHLE is an essential stepping stone within the GBADs programme because it connects the physical performance of animals in farming systems under different environmental and management conditions and different health states to farm economics. Moving forward, AHLE results will be an important step in calculating the wider monetary consequences of changes in animal health as part of the GBADs programme. FUNDING Bill & Melinda Gates Foundation, the UK Foreign, Commonwealth and Development Office, EU Horizon 2020 Research and Innovation Programme.
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Affiliation(s)
- William Gilbert
- Institute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool, UK.
| | - Thomas L Marsh
- School of Economic Sciences and Paul G Allen School for Global Health, Washington State University, Pullman, WA, USA
| | - Gemma Chaters
- Institute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - Wudu T Jemberu
- International Livestock Research Institute, Addis Ababa, Ethiopia; College of Veterinary Medicine and Animal Sciences, University of Gondar, Gondar, Ethiopia
| | - Mieghan Bruce
- School of Veterinary Medicine, Centre for Biosecurity and One Health, Murdoch University, Murdoch, WA, Australia
| | - Wilma Steeneveld
- Department of Population Health Sciences, Farm Animal Health section, Faculty of Veterinary Medicine, Utrecht University, Utrecht, Netherlands
| | - Joao S Afonso
- Institute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - Benjamin Huntington
- Institute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool, UK; Pengwern Animal Health, Wallasey Village, UK
| | - Jonathan Rushton
- Institute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool, UK
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Grace D, Amenu K, Daborn CJ, Knight-Jones T, Huntington B, Young S, Poole J, Rushton J. Current and potential use of animal disease data by stakeholders in the global south and north. Prev Vet Med 2024; 226:106189. [PMID: 38547559 DOI: 10.1016/j.prevetmed.2024.106189] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 02/16/2024] [Accepted: 03/18/2024] [Indexed: 04/13/2024]
Abstract
What cannot be measured will not be managed. The Global Burden of Animal Diseases (GBADs) will generate information on animal disease burdens by species, production system, type and gender of farmer and consumer, geographical region, and time period. To understand the demand for burden of animal disease (BAD) data and how end-users might benefit from this, we reviewed the literature on animal diseases prioritisation processes (ADPP) and conducted a survey of BAD information users. The survey covered their current use of data and prioritizations as well as their needs for different, more, and better information. We identified representative (geography, sector, species) BAD experts from the authors' networks and publicly available documents and e-mailed 1485 experts. Of 791 experts successfully contacted, 271 responded (34% response rate), and 185 complete and valid responses were obtained. Most respondents came from the public sector followed by academia/research, and most were affiliated to institutions in low- and middle-income countries (LMICs). Of the six ADPPs commonly featured in literature, only three were recognised by more than 40% of experts. An additional 23 ADPPs were used. Awareness of ADDPs varied significantly by respondents. Respondents ranked animal disease priorities. We used exploded logit to combine first, second and third disease priorities to better understand prioritzation and their determinants. Expert priorities differed significantly from priorities identified by the ADDPs, and also from the priorities stated veterinary services as reported in a survey for a World Organisation of Animal Health (WOAH) technical item. Respondents identified 15 different uses of BAD data. The most common use was presenting evidence (publications, official reports, followed by disease management, policy development and proposal writing). Few used disease data for prioritzation or resource allocation, fewer routinely used economic data for decision making, and less than half were aware of the use of decision support tools (DSTs). Nearly all respondents considered current BAD metrics inadequate, most considered animal health information insufficiently available and not evidence-based, and most expressed concerns that decision-making processes related to animal health lacked transparency and fairness. Cluster analysis suggested three clusters of BAD users and will inform DSTs to help them better meet their specific objectives. We conclude that there is a lack of satisfaction with current BAD information, and with existing ADDPs, contributing to sub-optimal decision making. Improved BAD data would have multiple uses by different stakeholders leading to better evidenced decisions and policies; moreover, clients will need support (including DSTs) to optimally use BAD information.
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Affiliation(s)
- Delia Grace
- Natural Resources Institute, Central Avenue, Chatham Maritime, Kent ME4 4TB, UK; International Livestock Research Institute, Bole, Addis Ababa, Ethiopia.
| | - Kebede Amenu
- International Livestock Research Institute, Bole, Addis Ababa, Ethiopia
| | | | | | | | - Stephen Young
- Natural Resources Institute, Central Avenue, Chatham Maritime, Kent ME4 4TB, UK
| | - Jane Poole
- International Livestock Research Institute, Nairobi, Kenya
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Li Y, McIntyre KM, Rasmussen P, Gilbert W, Chaters G, Raymond K, Jemberu WT, Larkins A, Patterson GT, Kwok S, Kappes AJ, Mayberry D, Schrobback P, Acosta MH, Stacey DA, Huntington B, Bruce M, Knight-Jones T, Rushton J. Rationalising development of classification systems describing livestock production systems for disease burden analysis within the Global Burden of Animal Diseases programme. Res Vet Sci 2024; 168:105102. [PMID: 38215653 DOI: 10.1016/j.rvsc.2023.105102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/05/2023] [Accepted: 11/27/2023] [Indexed: 01/14/2024]
Abstract
The heterogeneity that exists across the global spectrum of livestock production means that livestock productivity, efficiency, health expenditure and health outcomes vary across production systems. To ensure that burden of disease estimates are specific to the represented livestock population and people reliant upon them, livestock populations need to be systematically classified into different types of production system, reflective of the heterogeneity across production systems. This paper explores the data currently available of livestock production system classifications and animal health through a scoping review as a foundation for the development of a framework that facilitates more specific estimates of livestock disease burdens. A top-down framework to classification is outlined based on a systematic review of existing classification methods and provides a basis for simple grouping of livestock at global scale. The proposed top-down classification framework, which is dominated by commodity focus of production along with intensity of resource use, may have less relevance at the sub-national level in some jurisdictions and will need to be informed and adapted with information on how countries themselves categorize livestock and their production systems. The findings in this study provide a foundation for analysing animal health burdens across a broad level of production systems. The developed framework will fill a major gap in how livestock production and health are currently approached and analysed.
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Affiliation(s)
- Yin Li
- Global Burden of Animal Diseases (GBADs) Programme; Commonwealth Scientific and Industrial Research Organization, Agriculture and Food, 4067 Brisbane, Australia; School of Veterinary Medicine and Centre for Biosecurity and One Health, Harry Butler Institute, Murdoch University, Australia.
| | - K Marie McIntyre
- Global Burden of Animal Diseases (GBADs) Programme; School of Natural and Environmental Sciences, Newcastle University, UK; Institute of Infection and Global Health, University of Liverpool, IC2 Building, 146 Brownlow Hill, Liverpool L3 5RF, UK
| | - Philip Rasmussen
- Department of Veterinary and Animal Sciences, Section for Animal Welfare and Disease Control, University of Copenhagen, Copenhagen, Denmark; Section for Epidemiology, University of Zurich, Zurich, Switzerland
| | - William Gilbert
- Global Burden of Animal Diseases (GBADs) Programme; Institute of Infection and Global Health, University of Liverpool, IC2 Building, 146 Brownlow Hill, Liverpool L3 5RF, UK
| | - Gemma Chaters
- Global Burden of Animal Diseases (GBADs) Programme; Institute of Infection and Global Health, University of Liverpool, IC2 Building, 146 Brownlow Hill, Liverpool L3 5RF, UK
| | - Kassy Raymond
- Global Burden of Animal Diseases (GBADs) Programme; School of Computer Science, University of Guelph, Canada
| | - Wudu T Jemberu
- Global Burden of Animal Diseases (GBADs) Programme; International Livestock Research Institute, P O Box 5689, Addis Ababa, Ethiopia; University of Gondar, P. O. Box 196, Gondar, Ethiopia
| | - Andrew Larkins
- Global Burden of Animal Diseases (GBADs) Programme; School of Veterinary Medicine and Centre for Biosecurity and One Health, Harry Butler Institute, Murdoch University, Australia
| | - Grace T Patterson
- Global Burden of Animal Diseases (GBADs) Programme; School of Computer Science, University of Guelph, Canada
| | - Stephen Kwok
- Global Burden of Animal Diseases (GBADs) Programme; School of Veterinary Medicine and Centre for Biosecurity and One Health, Harry Butler Institute, Murdoch University, Australia
| | - Alexander James Kappes
- Global Burden of Animal Diseases (GBADs) Programme; School of Economic Sciences & Paul G. Allen School for Global Health, Washington State University, USA
| | - Dianne Mayberry
- Global Burden of Animal Diseases (GBADs) Programme; Commonwealth Scientific and Industrial Research Organization, Agriculture and Food, 4067 Brisbane, Australia
| | - Peggy Schrobback
- Global Burden of Animal Diseases (GBADs) Programme; Commonwealth Scientific and Industrial Research Organization, Agriculture and Food, 4067 Brisbane, Australia
| | - Mario Herrero Acosta
- College of Agriculture and Life Sciences, Cornell University, 250C Warren Hall, Ithaca, NY 14853, USA
| | - Deborah A Stacey
- Global Burden of Animal Diseases (GBADs) Programme; School of Computer Science, University of Guelph, Canada
| | - Benjamin Huntington
- Global Burden of Animal Diseases (GBADs) Programme; Institute of Infection and Global Health, University of Liverpool, IC2 Building, 146 Brownlow Hill, Liverpool L3 5RF, UK
| | - Mieghan Bruce
- Global Burden of Animal Diseases (GBADs) Programme; School of Veterinary Medicine and Centre for Biosecurity and One Health, Harry Butler Institute, Murdoch University, Australia
| | - Theodore Knight-Jones
- Global Burden of Animal Diseases (GBADs) Programme; International Livestock Research Institute, P O Box 5689, Addis Ababa, Ethiopia
| | - Jonathan Rushton
- Global Burden of Animal Diseases (GBADs) Programme; Institute of Infection and Global Health, University of Liverpool, IC2 Building, 146 Brownlow Hill, Liverpool L3 5RF, UK
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Bernardo TM, Rushton J, Huntington B, Stacey DA, Raymond K, Bensassi N, Patterson GT. Informatics progress of the Global Burden of Animal Diseases programme towards data for One Health. REV SCI TECH OIE 2023; 42:218-229. [PMID: 37232302 DOI: 10.20506/rst.42.3365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
The Global Burden of Animal Diseases (GBADs) programme will provide data-driven evidence that policy-makers can use to evaluate options, inform decisions, and measure the success of animal health and welfare interventions. The GBADs' Informatics team is developing a transparent process for identifying, analysing, visualising and sharing data to calculate livestock disease burdens and drive models and dashboards. These data can be combined with data on other global burdens (human health, crop loss, foodborne diseases) to provide a comprehensive range of information on One Health, required to address such issues as antimicrobial resistance and climate change. The programme began by gathering open data from international organisations (which are undergoing their own digital transformations). Efforts to achieve an accurate estimate of livestock numbers revealed problems in finding, accessing and reconciling data from different sources over time. Ontologies and graph databases are being developed to bridge data silos and improve the findability and interoperability of data. Dashboards, data stories, a documentation website and a Data Governance Handbook explain GBADs data, now available through an application programming interface. Sharing data quality assessments builds trust in such data, encouraging their application to livestock and One Health issues. Animal welfare data present a particular challenge, as much of this information is held privately and discussions continue regarding which data are the most relevant. Accurate livestock numbers are an essential input for calculating biomass, which subsequently feeds into calculations of antimicrobial use and climate change. The GBADs data are also essential to at least eight of the United Nations Sustainable Development Goals.
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Huntington B, Bernardo TM, Bondad-Reantaso M, Bruce M, Devleesschauwer B, Gilbert W, Grace D, Havelaar A, Herrero M, Marsh TL, Mesenhowski S, Pendell D, Pigott D, Shaw AP, Stacey D, Stone M, Torgerson P, Watkins K, Wieland B, Rushton J. Global Burden of Animal Diseases: a novel approach to understanding and managing disease in livestock and aquaculture. REV SCI TECH OIE 2021; 40:567-584. [PMID: 34542092 DOI: 10.20506/rst.40.2.3246] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Investments in animal health and Veterinary Services can have a measurable impact on the health of people and the environment. These investments require a baseline metric that describes the burden of animal health and welfare in order to justify and prioritise resource allocation and from which to measure the impact of interventions. This paper is part of a process of scientific enquiry in which problems are identified and solutions sought in an inclusive way. It poses the broad question: what should a system to measure the animal disease burden on society look like and what value would it add? Moreover, it aims to do this in such a way as to be accessible by a wide audience, who are encouraged to engage in this debate. Given that farmed animals, including those raised by poor smallholders, are an economic entity, this system should be based on economic principles. These poor farmers are negatively impacted by disparities in animal health technology, which can be addressed through a mixture of supply-led and demand-driven interventions, reinforcing the relevance of targeted financial support from government and non-governmental organisations. The Global Burden of Animal Diseases (GBADs) Programme will glean existing data to measure animal health losses within carefully characterised production systems. Consistent and transparent attribution of animal health losses will enable meaningful comparisons of the animal disease burden to be made between diseases, production systems and countries, and will show how it is apportioned by people's socio-economic status and gender. The GBADs Programme will produce a cloud-based knowledge engine and data portal, through which users will access burden metrics and associated visualisations, support for decisionmaking in the form of future animal health scenarios, and the outputs of wider economic modelling. The vision of GBADs, strengthening the food system for the benefit of society and the environment, is an example of One Health thinking in action.
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Buzdugan SN, Alarcon P, Huntington B, Rushton J, Blake DP, Guitian J. Enhancing the value of meat inspection records for broiler health and welfare surveillance: longitudinal detection of relational patterns. BMC Vet Res 2021; 17:278. [PMID: 34407823 PMCID: PMC8371771 DOI: 10.1186/s12917-021-02970-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 07/20/2021] [Indexed: 11/10/2022] Open
Abstract
Background Abattoir data are under-used for surveillance. Nationwide surveillance could benefit from using data on meat inspection findings, but several limitations need to be overcome. At the producer level, interpretation of meat inspection findings is a notable opportunity for surveillance with relevance to animal health and welfare. In this study, we propose that discovery and monitoring of relational patterns between condemnation conditions co-present in broiler batches at meat inspection can provide valuable information for surveillance of farmed animal health and welfare. Results Great Britain (GB)-based integrator meat inspection records for 14,045 broiler batches slaughtered in nine, four monthly intervals were assessed for the presence of surveillance indicators relevant to broiler health and welfare. K-means and correlation-based hierarchical clustering, and association rules analyses were performed to identify relational patterns in the data. Incidence of condemnation showed seasonal and temporal variation, which was detected by association rules analysis. Syndrome-related and non-specific relational patterns were detected in some months of meat inspection records. A potentially syndromic cluster was identified in May 2016 consisting of infection-related conditions: pericarditis, perihepatitis, peritonitis, and abnormal colour. Non-specific trends were identified in some months as an unusual combination of condemnation reasons in broiler batches. Conclusions We conclude that the detection of relational patterns in meat inspection records could provide producer-level surveillance indicators with relevance to broiler chicken health and welfare.
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Affiliation(s)
- S N Buzdugan
- Veterinary Epidemiology, Economics and Public Health Group, Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead Lane, Hertfordshire, AL9 7TA, North Mymms, UK.
| | - P Alarcon
- Veterinary Epidemiology, Economics and Public Health Group, Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead Lane, Hertfordshire, AL9 7TA, North Mymms, UK
| | - B Huntington
- Liverpool Science Park, Innovation Centre 2, 146 Brownlow Hill, L3 5RF, Liverpool, UK
| | - J Rushton
- Epidemiology and Population Health, Liverpool University, Brownlow Hill, L69 7ZX, Liverpool, UK
| | - D P Blake
- Pathobiology and Population Sciences, Royal Veterinary College, North Mymms, UK
| | - J Guitian
- Veterinary Epidemiology, Economics and Public Health Group, Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead Lane, Hertfordshire, AL9 7TA, North Mymms, UK
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Rushton J, Huntington B, Gilbert W, Herrero M, Torgerson PR, Shaw APM, Bruce M, Marsh TL, Pendell DL, Bernardo TM, Stacey D, Grace D, Watkins K, Bondad-Reantaso M, Devleesschauwer B, Pigott DM, Stone M, Mesenhowski S. Roll-out of the Global Burden of Animal Diseases programme. Lancet 2021; 397:1045-1046. [PMID: 33549170 DOI: 10.1016/s0140-6736(21)00189-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 01/21/2021] [Indexed: 12/19/2022]
Affiliation(s)
- J Rushton
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool L3 5RF, UK.
| | - B Huntington
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool L3 5RF, UK; Pengwern Animal Health Ltd, Wallasey Village, UK
| | - W Gilbert
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool L3 5RF, UK
| | - M Herrero
- CSIRO Agriculture and Food, St Lucia, QLD, Australia
| | - P R Torgerson
- Section of Epidemiology, Vetsuisse Faculty, University of Zurich, Zürich, Switzerland
| | - A P M Shaw
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool L3 5RF, UK; A P Consultants, Andover, UK
| | - M Bruce
- School of Veterinary Medicine, Centre for Animal Production and Health, Murdoch University, Murdoch, WA, Australia
| | - T L Marsh
- Paul G Allen School for Global Animal Health, Allen Center, School of Economic Sciences, Washington State University, WA, USA
| | - D L Pendell
- Department of Agricultural Economics, Kansas State University, Manhattan, KS, USA
| | - T M Bernardo
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - D Stacey
- School of Computer Science, University of Guelph, Guelph, ON, Canada
| | - D Grace
- Food and Markets Department, Natural Resources Institute, Faculty of Engineering and Science, University of Greenwich, Chatham Maritime, UK; International Livestock Research Institute, Nairobi, Kenya
| | - K Watkins
- FoodFirst LLC, Indianapolis, IN, USA
| | - M Bondad-Reantaso
- Fisheries Division, Food and Agriculture Organization of the United Nations, Rome, Italy
| | | | - D M Pigott
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - M Stone
- OIE World Organisation for Animal Health, Paris, France
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Buzdugan SN, Chang YM, Huntington B, Rushton J, Guitian J, Alarcon P, Blake DP. Identification of production chain risk factors for slaughterhouse condemnation of broiler chickens'. Prev Vet Med 2020; 181:105036. [PMID: 32505027 DOI: 10.1016/j.prevetmed.2020.105036] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 05/03/2020] [Accepted: 05/14/2020] [Indexed: 10/24/2022]
Abstract
Slaughterhouse condemnation of broiler chickens results from identification of polymorphic pathological conditions during meat inspection from arrival and on the slaughter line. While conditions that result in condemnation are multifactorial, identification of factors that are common for a number of categories could be valuable for developing strategies to reduce total condemnation. This study aimed to identify those condemnation categories that were most common in batches of broiler chickens and to determine and compare associated risk factors. In the first step, retrospective meat inspection records for 55,918 broiler batches from one large broiler integrator for 2015-2017 were used for association rules analysis. Results identified a network of nine associated condemnation categories: whole carcass condemnation for ascites, abnormal colour, perihepatitis, cellulitis, hard breast, tumours and dead on arrival, and liver only and heart only most often associated with hepatitis and pericarditis, respectively. Secondly, a longitudinal study collected data on 109 explanatory variables from broiler parental flocks to slaughterhouse characteristics between January 2015 and December 2017. Condemnation outcome data were obtained from meat inspection records for 539 broiler batches participating in the study. Parental flock-, rearing farm-, shed- and transport-level risk factors were assessed for each outcome using mixed-effects multivariable Poisson regression including shed and farm as random effects. A Poisson regression tree method was used as the first step to identify variables most relevant for analysis and comparison across the outcomes. No single production factor was associated with all nine of the condemnation outcomes investigated in this study, although some were shared across multiple outcomes: age of parental flock at time of lay, flock-level Campylobacter spp. frequency, broiler chick weight at seven days of age, weight at slaughter, type of broiler removal (i.e. thinning, final depopulation), catcher team, number of birds per transport crate, slaughterhouse shift number, and type of slaughterhouse line. Broiler chickens removed during final depopulation were at greatest risk of condemnation. Condemnation rates for cellulitis and tumours were found to be higher in broilers inspected by night shift at the slaughterhouse. Discovery of an apparent protective effect of a higher number of broilers per transport crate was unexpected. These findings provide information for the broiler industry on production chain factors that might be amenable to targeted intervention to improve future efforts for control of condemnation.
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Affiliation(s)
- S N Buzdugan
- Veterinary Epidemiology, Economics and Public Health Group, Royal Veterinary College, Hawkshead Lane, Hatfield, Hertfordshire, AL9 7TA, UK.
| | - Y M Chang
- Research Support Office, Royal Veterinary College, Royal College Street, NW1 0TU, UK
| | - B Huntington
- Liverpool Science Park, Innovation Centre 2, 146 Brownlow Hill, Liverpool, L3 5RF, UK
| | - J Rushton
- Epidemiology and Population-Health, Liverpool University, Brownlow Hill, Liverpool, L69 7ZX, UK
| | - J Guitian
- Veterinary Epidemiology, Economics and Public Health Group, Royal Veterinary College, Hawkshead Lane, Hatfield, Hertfordshire, AL9 7TA, UK
| | - P Alarcon
- Veterinary Epidemiology, Economics and Public Health Group, Royal Veterinary College, Hawkshead Lane, Hatfield, Hertfordshire, AL9 7TA, UK
| | - D P Blake
- Pathobiology and Population Sciences, Royal Veterinary College, Hawkshead Lane, Hatfield, Hertfordshire, AL9 7TA, UK
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