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Amenu K, McIntyre KM, Moje N, Knight-Jones T, Rushton J, Grace D. Approaches for disease prioritization and decision-making in animal health, 2000-2021: a structured scoping review. Front Vet Sci 2023; 10:1231711. [PMID: 37876628 PMCID: PMC10593474 DOI: 10.3389/fvets.2023.1231711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/06/2023] [Indexed: 10/26/2023] Open
Abstract
This scoping review identifies and describes the methods used to prioritize diseases for resource allocation across disease control, surveillance, and research and the methods used generally in decision-making on animal health policy. Three electronic databases (Medline/PubMed, Embase, and CAB Abstracts) were searched for articles from 2000 to 2021. Searches identified 6, 395 articles after de-duplication, with an additional 64 articles added manually. A total of 6, 460 articles were imported to online document review management software (sysrev.com) for screening. Based on inclusion and exclusion criteria, 532 articles passed the first screening, and after a second round of screening, 336 articles were recommended for full review. A total of 40 articles were removed after data extraction. Another 11 articles were added, having been obtained from cross-citations of already identified articles, providing a total of 307 articles to be considered in the scoping review. The results show that the main methods used for disease prioritization were based on economic analysis, multi-criteria evaluation, risk assessment, simple ranking, spatial risk mapping, and simulation modeling. Disease prioritization was performed to aid in decision-making related to various categories: (1) disease control, prevention, or eradication strategies, (2) general organizational strategy, (3) identification of high-risk areas or populations, (4) assessment of risk of disease introduction or occurrence, (5) disease surveillance, and (6) research priority setting. Of the articles included in data extraction, 50.5% had a national focus, 12.3% were local, 11.9% were regional, 6.5% were sub-national, and 3.9% were global. In 15.2% of the articles, the geographic focus was not specified. The scoping review revealed the lack of comprehensive, integrated, and mutually compatible approaches to disease prioritization and decision support tools for animal health. We recommend that future studies should focus on creating comprehensive and harmonized frameworks describing methods for disease prioritization and decision-making tools in animal health.
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Affiliation(s)
- Kebede Amenu
- Global Burden of Animal Diseases (GBADs) Programme, University of Liverpool, Liverpool, United Kingdom
- Department of Microbiology, Immunology and Veterinary, Public Health, College of Veterinary Medicine and Agriculture, Addis Ababa University, Bishoftu, Ethiopia
- Animal and Human Health Program, International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia
| | - K. Marie McIntyre
- Global Burden of Animal Diseases (GBADs) Programme, University of Liverpool, Liverpool, United Kingdom
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom
- Modelling, Evidence and Policy Group, School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Nebyou Moje
- Department of Biomedical Sciences, College of Veterinary Medicine and Agriculture, Addis Ababa University, Bishoftu, Ethiopia
| | - Theodore Knight-Jones
- Global Burden of Animal Diseases (GBADs) Programme, University of Liverpool, Liverpool, United Kingdom
- Animal and Human Health Program, International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia
| | - Jonathan Rushton
- Global Burden of Animal Diseases (GBADs) Programme, University of Liverpool, Liverpool, United Kingdom
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Delia Grace
- Global Burden of Animal Diseases (GBADs) Programme, University of Liverpool, Liverpool, United Kingdom
- Food and Markets Department, Natural Resources Institute, University of Greenwich, London, United Kingdom
- Animal and Human Health Program, International Livestock Research Institute (ILRI), Nairobi, Kenya
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Boden LA, Voas S, Mellor D, Auty H. EPIC, Scottish Government's Centre of Expertise in Animal Disease Outbreaks: A Model for Provision of Risk-Based Evidence to Policy. Front Vet Sci 2020; 7:119. [PMID: 32211431 PMCID: PMC7066993 DOI: 10.3389/fvets.2020.00119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 02/18/2020] [Indexed: 11/16/2022] Open
Abstract
EPIC, Scottish Government's Centre of Expertise on Animal Disease Outbreaks, offers a successful and innovative model for provision of scientific advice and analysis to policy-makers in Scotland. In this paper, we describe EPIC's remit and operations, and reflect on three case studies which illustrate how the Centre of Expertise Model provides risk-based evidence through rapid access to emergency advice and analyses, estimating disease risks and improving disease detection, assessing different disease control options, and improving future risk resilience. The successes and challenges faced by EPIC and its members offer useful lessons for animal health researchers and authorities, working in contingency planning for animal health security in other countries.
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Affiliation(s)
- Lisa A Boden
- Global Academy of Agriculture and Food Security, The Royal (Dick) School of Veterinary Studies and The Roslin Institute, Midlothian, United Kingdom
| | - Sheila Voas
- Animal Health and Welfare Division, Scottish Government, Edinburgh, United Kingdom
| | - Dominic Mellor
- School of Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Harriet Auty
- Epidemiology Research Unit, Scotland's Rural College (SRUC), Inverness, United Kingdom
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Souley Kouato B, De Clercq K, Abatih E, Dal Pozzo F, King DP, Thys E, Marichatou H, Saegerman C. Review of epidemiological risk models for foot-and-mouth disease: Implications for prevention strategies with a focus on Africa. PLoS One 2018; 13:e0208296. [PMID: 30543641 PMCID: PMC6292601 DOI: 10.1371/journal.pone.0208296] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2016] [Accepted: 11/15/2018] [Indexed: 11/18/2022] Open
Abstract
Foot-and-mouth disease (FMD) is a highly infectious transboundary disease that affects domestic and wild cloven-hoofed animal species. The aim of this review was to identify and critically assess some modelling techniques for FMD that are well supported by scientific evidence from the literature with a focus on their use in African countries where the disease remains enzootic. In particular, this study attempted to provide a synopsis of the relative strengths and weaknesses of these models and their relevance to FMD prevention policies. A literature search was conducted to identify quantitative and qualitative risk assessments for FMD, including studies that describe FMD risk factor modelling and spatiotemporal analysis. A description of retrieved papers and a critical assessment of the modelling methods, main findings and their limitations were performed. Different types of models have been used depending on the purpose of the study and the nature of available data. The most frequently identified factors associated with the risk of FMD occurrence were the movement (especially uncontrolled animal movement) and the mixing of animals around water and grazing points. Based on the qualitative and quantitative risk assessment studies, the critical pathway analysis showed that the overall risk of FMDV entering a given country is low. However, in some cases, this risk can be elevated, especially when illegal importation of meat and the movement of terrestrial livestock are involved. Depending on the approach used, these studies highlight shortcomings associated with the application of models and the lack of reliable data from endemic settings. Therefore, the development and application of specific models for use in FMD endemic countries including Africa is encouraged.
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Affiliation(s)
- Bachir Souley Kouato
- Research Unit in Epidemiology and Risk Analysis Applied to Veterinary Sciences (UREAR-ULiège), Fundamental and Applied Research for Animals & Health (FARAH) Centre, Faculty of Veterinary Medicine, University of Liege, Liege, Belgium
- Institut National de la Recherche Agronomique du Niger (INRAN), Niamey, Niger
| | - Kris De Clercq
- Operational Directorate Viral Diseases, Unit Vesicular and Exotic Diseases, Veterinary and Agrochemical Research Centre (CODA-CERVA), Brussels, Belgium
| | - Emmanuel Abatih
- Department of Mathematics, Computer Sciences and Statistics, University of Gent, Krijgslaan Gent, Belgium
| | - Fabiana Dal Pozzo
- Research Unit in Epidemiology and Risk Analysis Applied to Veterinary Sciences (UREAR-ULiège), Fundamental and Applied Research for Animals & Health (FARAH) Centre, Faculty of Veterinary Medicine, University of Liege, Liege, Belgium
| | - Donald P. King
- The Pirbright Institute, Ash Road, Pirbright, Surrey, United Kingdom
| | - Eric Thys
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Hamani Marichatou
- Université Abdou Moumouni de Niamey, Faculté d'Agronomie, Niamey, Niger
| | - Claude Saegerman
- Research Unit in Epidemiology and Risk Analysis Applied to Veterinary Sciences (UREAR-ULiège), Fundamental and Applied Research for Animals & Health (FARAH) Centre, Faculty of Veterinary Medicine, University of Liege, Liege, Belgium
- * E-mail:
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Hollings T, Robinson A, van Andel M, Jewell C, Burgman M. Species distribution models: A comparison of statistical approaches for livestock and disease epidemics. PLoS One 2017; 12:e0183626. [PMID: 28837685 PMCID: PMC5570337 DOI: 10.1371/journal.pone.0183626] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Accepted: 08/01/2017] [Indexed: 11/28/2022] Open
Abstract
In livestock industries, reliable up-to-date spatial distribution and abundance records for animals and farms are critical for governments to manage and respond to risks. Yet few, if any, countries can afford to maintain comprehensive, up-to-date agricultural census data. Statistical modelling can be used as a proxy for such data but comparative modelling studies have rarely been undertaken for livestock populations. Widespread species, including livestock, can be difficult to model effectively due to complex spatial distributions that do not respond predictably to environmental gradients. We assessed three machine learning species distribution models (SDM) for their capacity to estimate national-level farm animal population numbers within property boundaries: boosted regression trees (BRT), random forests (RF) and K-nearest neighbour (K-NN). The models were built from a commercial livestock database and environmental and socio-economic predictor data for New Zealand. We used two spatial data stratifications to test (i) support for decision making in an emergency response situation, and (ii) the ability for the models to predict to new geographic regions. The performance of the three model types varied substantially, but the best performing models showed very high accuracy. BRTs had the best performance overall, but RF performed equally well or better in many simulations; RFs were superior at predicting livestock numbers for all but very large commercial farms. K-NN performed poorly relative to both RF and BRT in all simulations. The predictions of both multi species and single species models for farms and within hypothetical quarantine zones were very close to observed data. These models are generally applicable for livestock estimation with broad applications in disease risk modelling, biosecurity, policy and planning.
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Affiliation(s)
- Tracey Hollings
- Centre of Excellence for Biosecurity Risk Analysis, University of Melbourne, Melbourne, Australia
| | - Andrew Robinson
- Centre of Excellence for Biosecurity Risk Analysis, University of Melbourne, Melbourne, Australia
| | - Mary van Andel
- Ministry for Primary Industries, Wellington, New Zealand
| | - Chris Jewell
- Department of Health and Medicine, Lancaster University, Lancaster, United Kingdom
| | - Mark Burgman
- Centre of Excellence for Biosecurity Risk Analysis, University of Melbourne, Melbourne, Australia
- Centre for Environmental Policy, Imperial College, London, United Kingdom
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Modeling the impact of vaccination control strategies on a foot and mouth disease outbreak in the Central United States. Prev Vet Med 2014; 117:487-504. [DOI: 10.1016/j.prevetmed.2014.10.005] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2014] [Revised: 10/01/2014] [Accepted: 10/04/2014] [Indexed: 11/19/2022]
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Yoon H, Yoon SS, Kim H, Kim YJ, Kim B, Wee SH. Estimation of the Infection Window for the 2010/2011 Korean Foot-and-Mouth Disease Outbreak. Osong Public Health Res Perspect 2013; 4:127-32. [PMID: 24159543 PMCID: PMC3787534 DOI: 10.1016/j.phrp.2013.04.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2013] [Revised: 03/25/2013] [Accepted: 04/16/2013] [Indexed: 11/24/2022] Open
Abstract
Objectives This study aims to develop a method for calculating infection time lines for disease outbreaks on farms was developed using the 2010/2011 foot-and-mouth disease (FMD) epidemic in the Republic of Korea. Methods Data on farm demography, the detection date of FMD, the clinical history for the manifestation of lesions, the presence of antibodies against FMD virus (including antibodies against the structural and nonstructural proteins of serotype O), vaccination status (O1 Manisa strain), the number of reactors and information on the slaughter of infected animals were utilized in this method. Results Based on estimates of the most likely infection date, a cumulative detection probability that an infected farm would be identified on a specific day was determined. Peak infection was observed between late December and early January, but peak detection occurred in mid-January. The early detection probability was highest for pigs, followed by cattle (dairy, then beef) and small ruminants. Nearly 90% of the infected pig farms were detected by Day 11 post-infection while 13 days were required for detection for both dairy and beef cattle farms, and 21 days were necessary for small ruminant (goat and deer) farms. On average, 8.1 ± 3.1 days passed prior to detecting the presence of FMD virus on a farm. The interval between infection and detection of FMD was inversely associated with the intensity of farming. Conclusion The results of our study emphasize the importance of intensive clinical inspection, which is the quickest method of detecting FMD infection and minimizing the damage caused by an epidemic.
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Affiliation(s)
- Hachung Yoon
- Veterinary Epidemiology Division, Animal and Plant Quarantine Agency, Anyang, Korea
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Tildesley MJ, Volkova VV, Woolhouse ME. Potential for epidemic take-off from the primary outbreak farm via livestock movements. BMC Vet Res 2011; 7:76. [PMID: 22115121 PMCID: PMC3264511 DOI: 10.1186/1746-6148-7-76] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2010] [Accepted: 11/24/2011] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND We consider the potential for infection to spread in a farm population from the primary outbreak farm via livestock movements prior to disease detection. We analyse how this depends on the time of the year infection occurs, the species transmitting, the length of infectious period on the primary outbreak farm, location of the primary outbreak, and whether a livestock market becomes involved. We consider short infectious periods of 1 week, 2 weeks and 4 weeks, characteristic of acute contagious livestock diseases. The analysis is based on farms in Scotland from 1 January 2003 to 31 July 2007. RESULTS The proportion of primary outbreaks from which an acute contagious disease would spread via movement of livestock is generally low, but exhibits distinct annual cyclicity with peaks in May and August. The distance that livestock are moved varies similarly: at the time of the year when the potential for spread via movements is highest, the geographical spread via movements is largest. The seasonal patterns for cattle differ from those for sheep whilst there is no obvious seasonality for pigs. When spread via movements does occur, there is a high risk of infection reaching a livestock market; infection of markets can amplify disease spread. The proportion of primary outbreaks that would spread infection via livestock movements varies significantly between geographical regions. CONCLUSIONS In this paper we introduce a set-up for analysis of movement data that allows for a generalized assessment of the risk associated with infection spreading from a primary outbreak farm via livestock movements, applying this to Scotland, we assess how this risk depends upon the time of the year, species transmitting, location of the farm and other factors.
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Affiliation(s)
- Michael J Tildesley
- Centre for Immunity, Infection and Evolution, School of Biological Sciences, University of Edinburgh, Ashworth Laboratories, Kings Buildings, West Mains Road, Edinburgh, EH9 3JT, UK.
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Peiso OO, Bronsvoort BMDC, Handel IG, Volkova VV. A review of exotic animal disease in Great Britain and in Scotland specifically between 1938 and 2007. PLoS One 2011; 6:e22066. [PMID: 21818292 PMCID: PMC3144883 DOI: 10.1371/journal.pone.0022066] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2010] [Accepted: 06/16/2011] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Incursions of contagious diseases of livestock into disease-free zones are inevitable as long as the diseases persist elsewhere in the world. Knowledge of where, when and how incursions have occurred helps assess the risks, and regionalize preventative and reactive measures. METHODOLOGY Based on reports of British governmental veterinary services, we review occurrence of the former OIE List A diseases, and of Aujeszky's disease, anthrax and bovine tuberculosis (bTB) in farm-animals in Great Britain (GB) between 1938 and 2007. We estimate incidence of each disease on GB agricultural holdings and fraction of susceptible farm-animals culled to control the disease each year. We then consider the frequency and incidence of the diseases in Scotland alone. The limitations of available data on historical disease occurrence and denominator populations are detailed in Text S2. CONCLUSIONS The numbers of livestock and poultry farmed in GB grew over the years 1938-2007; the number of agricultural holdings decreased. An amalgamation of production on larger holdings took place from the 1940s to the 1980s. The maximum annual incidence of a reviewed disease in GB 1938-2007 was reported for bTB, 1.69% of holdings in 1961. This was followed by Newcastle disease, 1.50% of holdings in 1971, and classical swine fever, 1.09% of holdings in 1940. The largest fractional cull of susceptible livestock in a single year in each of the four decades 1950s-1980s was due to a viral disease primarily affecting swine. During the periods 1938-1949 and 2000-2007 this was due to outbreaks of foot and mouth disease. In the absence of incursions of the former OIE List A diseases in the 1990s, this was due to bTB. Over the 70 years, the diseases were reported with lower frequency and lower annual incidence in Scotland, as compared to when these statistics are considered for GB as a whole.
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Affiliation(s)
- Onneile O. Peiso
- Epidemiology Group, School of Biological Sciences, Centre for Infectious Diseases, University of Edinburgh, Edinburgh, United Kingdom
| | - Barend M. de C. Bronsvoort
- Epidemiology, Economics and Risk Assessment (EERA) Group, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Roslin, Midlothian, United Kingdom
| | - Ian G. Handel
- Epidemiology, Economics and Risk Assessment (EERA) Group, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Roslin, Midlothian, United Kingdom
| | - Victoriya V. Volkova
- Epidemiology Group, School of Biological Sciences, Centre for Infectious Diseases, University of Edinburgh, Edinburgh, United Kingdom
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