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Lambert S, Bauzile B, Mugnier A, Durand B, Vergne T, Paul MC. A systematic review of mechanistic models used to study avian influenza virus transmission and control. Vet Res 2023; 54:96. [PMID: 37853425 PMCID: PMC10585835 DOI: 10.1186/s13567-023-01219-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 09/05/2023] [Indexed: 10/20/2023] Open
Abstract
The global spread of avian influenza A viruses in domestic birds is causing increasing socioeconomic devastation. Various mechanistic models have been developed to better understand avian influenza transmission and evaluate the effectiveness of control measures in mitigating the socioeconomic losses caused by these viruses. However, the results of models of avian influenza transmission and control have not yet been subject to a comprehensive review. Such a review could help inform policy makers and guide future modeling work. To help fill this gap, we conducted a systematic review of the mechanistic models that have been applied to field outbreaks. Our three objectives were to: (1) describe the type of models and their epidemiological context, (2) list estimates of commonly used parameters of low pathogenicity and highly pathogenic avian influenza transmission, and (3) review the characteristics of avian influenza transmission and the efficacy of control strategies according to the mechanistic models. We reviewed a total of 46 articles. Of these, 26 articles estimated parameters by fitting the model to data, one evaluated the effectiveness of control strategies, and 19 did both. Values of the between-individual reproduction number ranged widely: from 2.18 to 86 for highly pathogenic avian influenza viruses, and from 4.7 to 45.9 for low pathogenicity avian influenza viruses, depending on epidemiological settings, virus subtypes and host species. Other parameters, such as the durations of the latent and infectious periods, were often taken from the literature, limiting the models' potential insights. Concerning control strategies, many models evaluated culling (n = 15), while vaccination received less attention (n = 6). According to the articles reviewed, optimal control strategies varied between virus subtypes and local conditions, and depended on the overall objective of the intervention. For instance, vaccination was optimal when the objective was to limit the overall number of culled flocks. In contrast, pre-emptive culling was preferred for reducing the size and duration of an epidemic. Early implementation consistently improved the overall efficacy of interventions, highlighting the need for effective surveillance and epidemic preparedness.
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Affiliation(s)
| | - Billy Bauzile
- IHAP, Université de Toulouse, INRAE, ENVT, Toulouse, France
| | | | - Benoit Durand
- Epidemiology Unit, Laboratory for Animal Health, French Agency for Food, Environment and Occupational Health and Safety (ANSES), Paris-Est University, Maisons-Alfort, France
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García García KM, Apolloni A, Giacomini A, Ciss M, Fall M, Marème Gaye A, Arsevska E, Mesdour A, Chevanne E, Rosso F, Cardinale E, Squarzoni Diaw C, Seck I, Lo M, Delabouglise A. Environmental and economic determinants of temporal dynamics of the ruminant movement network of Senegal. Sci Rep 2023; 13:14482. [PMID: 37660087 PMCID: PMC10475130 DOI: 10.1038/s41598-023-40715-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Accepted: 08/16/2023] [Indexed: 09/04/2023] Open
Abstract
Our understanding of the drivers of the temporal dynamics of livestock mobility networks is currently limited, despite their significant implications for the surveillance and control of infectious diseases. We analyzed the effect of time-varying environmental and economic variables-biomass production, rainfall, livestock market prices, and religious calendar on long-distance movements of cattle and small ruminant herds in Senegal in the years 2014 and 2019. We used principal component analysis to explore the variation of the hypothesized explanatory variables in space and time and a generalized additive modelling approach to assess the effect of those variables on the likelihood of herd movement between pairs of administrative units. Contrary to environmental variables, the patterns of variation of market prices show significant differences across locations. The explanatory variables at origin had the highest contribution to the model deviance reduction. Biomass production and rainfall were found to affect the likelihood of herd movement for both species on at least 1 year. Market price at origin had a strong and consistent effect on the departure of small ruminant herds. Our study shows the potential benefits of regular monitoring of market prices for future efforts at forecasting livestock movements and associated sanitary risks.
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Affiliation(s)
| | - Andrea Apolloni
- CIRAD, UMR ASTRE, Montpellier, France
- CIRAD, UMR ASTRE, Univ Montpellier, INRAE, Montpellier, France
| | - Alessandra Giacomini
- CIRAD, UMR ASTRE, Montpellier, France
- CIRAD, UMR ASTRE, Univ Montpellier, INRAE, Montpellier, France
- Department of Biosciences, Swansea University, Swansea, SA2 8PP, UK
| | - Mamadou Ciss
- Institut Sénégalais de Recherches Agricoles/Laboratoire National de l'Elevage et de Recherches Vétérinaires, BP 2057, Dakar-Hann, Sénégal
| | | | | | - Elena Arsevska
- CIRAD, UMR ASTRE, Montpellier, France
- CIRAD, UMR ASTRE, Univ Montpellier, INRAE, Montpellier, France
| | - Asma Mesdour
- CIRAD, UMR ASTRE, Montpellier, France
- CIRAD, UMR ASTRE, Univ Montpellier, INRAE, Montpellier, France
| | - Etienne Chevanne
- Food and Agriculture Organization of the United Nations, The European Commission for the Control of Foot-and-Mouth Disease, Rome, Italy
| | - Fabrizio Rosso
- Food and Agriculture Organization of the United Nations, The European Commission for the Control of Foot-and-Mouth Disease, Rome, Italy
| | - Eric Cardinale
- CIRAD, UMR ASTRE, Montpellier, France
- CIRAD, UMR ASTRE, Univ Montpellier, INRAE, Montpellier, France
| | - Cécile Squarzoni Diaw
- CIRAD, UMR ASTRE, Montpellier, France
- CIRAD, UMR ASTRE, Univ Montpellier, INRAE, Montpellier, France
| | - Ismaila Seck
- Food and Agriculture Organization of the United Nations, One Health and Intelligence and Early Warning Office, Rome, Italy
| | - Mbargou Lo
- Direction des Services Vétérinaires, Dakar, Sénégal
| | - Alexis Delabouglise
- CIRAD, UMR ASTRE, Montpellier, France.
- CIRAD, UMR ASTRE, Univ Montpellier, INRAE, Montpellier, France.
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3
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Kim Y, Nouvellet P, Rogoll L, Staubach C, Schulz K, Sauter-Louis C, Pfeiffer DU, Fournié G. Contrasting seasonality of African swine fever outbreaks and its drivers. Epidemics 2023; 44:100703. [PMID: 37385853 DOI: 10.1016/j.epidem.2023.100703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 05/30/2023] [Accepted: 06/12/2023] [Indexed: 07/01/2023] Open
Abstract
The seasonality of African swine fever (ASF) outbreaks in domestic pigs differs between temperate and subtropical/tropical regions. We hypothesise that variations in the importance of wild boar-to-farm and farm-to-farm transmission routes shape these contrasting patterns, and we emphasise the implications for effective ASF control.
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Affiliation(s)
| | - Pierre Nouvellet
- University of Sussex, Brighton, UK; Imperial College London, London, UK
| | - Lisa Rogoll
- Friedrich-Loeffler-Institut, Greifswald-Insel Riems, Germany
| | | | - Katja Schulz
- Friedrich-Loeffler-Institut, Greifswald-Insel Riems, Germany
| | | | - Dirk Udo Pfeiffer
- The Royal Veterinary College, London, UK; City University of Hong Kong, Hong Kong SAR, Hong Kong
| | - Guillaume Fournié
- The Royal Veterinary College, London, UK; Université de Lyon, INRAE, VetAgro Sup, UMR EPIA, Marcy l'Etoile, France; Université Clermont Auvergne, INRAE, VetAgro Sup, UMR EPIA, Saint-Gènes-Champanelle, France.
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4
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Thi Dien N, Thi Minh Khue N, Etaba A, Fournié G, Huyen LTT, Van Dai N, Tuan HA, Duc DV, Thi Thanh Hoa P, Van Duy N, Ton VD, Alarcon P. Mapping chicken production and distribution networks in Vietnam: An analysis of socio-economic factors and their epidemiological significances. Prev Vet Med 2023; 214:105906. [PMID: 37023633 DOI: 10.1016/j.prevetmed.2023.105906] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 02/22/2023] [Accepted: 03/22/2023] [Indexed: 03/29/2023]
Abstract
The growing chicken industry in Viet Nam has an increasingly important contribution to the country's food security, but its development requires careful planning to prevent disease risks. This study characterizes the chicken production and distribution networks in Vietnam and identifies potential factors that could promote disease emergence and transmission. Qualitative data were collected from interviews with 29 key informants from five stakeholder groups representing the main nodes from chicken production and distribution networks (PDN). Three main networks were identified based on production type: a colored broiler and spent hen network, a white (or exotic) broiler network, and an egg network. Colored chickens and spent hens are the most preferred commodity by vietnamese consumers and their PDN is composed of production units differing in their scale and management and with long distribution chains involving numerous small-scale independent stakeholders. Live bird markets plays a central role in this network, which is driven by consumers' preference for live chickens. The white chicken network presents an important duality, as it is composed of both a large number of independent household farms and traders operating independently with little chain coordination, and of large farms contracted by vertically-integrated companies. The egg PDN was the most organized network, being mostly controlled by large vertically-integrated companies. High level specialization and diversification of stakeholders is found in all three networks. Stakeholders' perceptions of the main factors promoting disease risk along the PDN were the low biosecurity in household farms and live bird markets, mobile traders, the informal slaughter of birds and the management of sick birds. Findings from this study can be used to plan future studies to support food system planners in the development of safer poultry production and distribution in Vietnam.
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Characterisation of chicken farms in Vietnam: a typology of antimicrobial use among different production systems. Prev Vet Med 2022; 208:105731. [DOI: 10.1016/j.prevetmed.2022.105731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 07/08/2022] [Accepted: 07/26/2022] [Indexed: 11/22/2022]
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Chakma S, Osmani MG, Akwar H, Hasan Z, Nasrin T, Karim MR, Samad MA, Giasuddin M, Sly P, Islam Z, Debnath NC, Brum E, Magalhães RS. Risk Areas for Influenza A(H5) Environmental Contamination in Live Bird Markets, Dhaka, Bangladesh. Emerg Infect Dis 2021; 27:2399-2408. [PMID: 34424170 PMCID: PMC8386803 DOI: 10.3201/eid2709.204447] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
We evaluated the presence of influenza A(H5) virus environmental contamination in live bird markets (LBMs) in Dhaka, Bangladesh. By using Bernoulli generalized linear models and multinomial logistic regression models, we quantified LBM-level factors associated with market work zone–specific influenza A(H5) virus contamination patterns. Results showed higher environmental contamination in LBMs that have wholesale and retail operations compared with retail-only markets (relative risk 0.69, 95% 0.51–0.93; p = 0.012) and in March compared with January (relative risk 2.07, 95% CI 1.44–2.96; p<0.001). Influenza A(H5) environmental contamination remains a public health problem in most LBMs in Dhaka, which underscores the need to implement enhanced biosecurity interventions in LBMs in Bangladesh.
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Ding F, Li Y, Huang B, Edwards J, Cai C, Zhang G, Jiang D, Wang Q, Robertson ID. Infection and risk factors of human and avian influenza in pigs in south China. Prev Vet Med 2021; 190:105317. [PMID: 33744674 DOI: 10.1016/j.prevetmed.2021.105317] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 02/09/2021] [Accepted: 03/01/2021] [Indexed: 11/19/2022]
Abstract
The coinfection of swine influenza (SI) strains and avian/human-source influenza strains in piggeries can contribute to the evolution of new influenza viruses with pandemic potential. This study analyzed surveillance data on SI in south China and explored the spatial predictor variables associated with different influenza infection scenarios in counties within the study area. Blood samples were collected from 7670 pigs from 534 pig farms from 2015 to 2017 and tested for evidence of infection with influenza strains from swine, human and avian sources. The herd prevalences for EA H1N1, H1N1pdm09, classic H1N1, HS-like H3N2, seasonal human H1N1 and avian influenza H9N2 were 88.5, 64.5, 60.3, 57.8, 12.9 and 10.3 %, respectively. Anthropogenic factors including detection frequency, chicken density, duck density, pig density and human population density were found to be better predictor variables for three influenza infection scenarios (infection with human strains, infection with avian strains, and coinfection with H9N2 avian strain and at least one swine strain) than were meteorological and geographical factors. Predictive risk maps generated for the four provinces in south China highlighted that the areas with a higher risk of the three infection scenarios were predominantly clustered in the delta area of the Pearl River in Guangdong province and counties surrounding Poyang Lake in Jiangxi province. Identification of higher risk areas can inform targeted surveillance for influenza in humans and pigs, helping public health authorities in designing risk-based SI control strategies to address the pandemic influenza threat in south China.
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Affiliation(s)
- Fangyu Ding
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yin Li
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia; China Animal Health and Epidemiology Center, Qingdao, Shandong, China
| | - Baoxu Huang
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia; China Animal Health and Epidemiology Center, Qingdao, Shandong, China
| | - John Edwards
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia; China Animal Health and Epidemiology Center, Qingdao, Shandong, China
| | - Chang Cai
- Zhejiang Agricultural and Forestry University, Hangzhou, China
| | - Guihong Zhang
- South China Agriculture University, Guangzhou, Guangdong, China
| | - Dong Jiang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China; Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land & Resources, Beijing, 100101, China.
| | - Qian Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Ian D Robertson
- School of Veterinary Medicine, Murdoch University, Perth, WA, Australia; China-Australia Joint Research and Training Centre for Veterinary Epidemiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, Hubei, China.
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Sallam M, Ababneh NA, Dababseh D, Bakri FG, Mahafzah A. Temporal increase in D614G mutation of SARS-CoV-2 in the Middle East and North Africa. Heliyon 2021; 7:e06035. [PMID: 33495741 PMCID: PMC7817394 DOI: 10.1016/j.heliyon.2021.e06035] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 12/06/2020] [Accepted: 01/15/2021] [Indexed: 02/09/2023] Open
Abstract
BACKGROUND Phylogeny construction can help to reveal evolutionary relatedness among molecular sequences. The spike (S) gene of SARS-CoV-2 is the subject of an immune selective pressure which increases the variability in such region. This study aimed to identify mutations in the S gene among SARS-CoV-2 sequences collected in the Middle East and North Africa (MENA), focusing on the D614G mutation, that has a presumed fitness advantage. Another aim was to analyze the S gene sequences phylogenetically. METHODS The SARS-CoV-2 S gene sequences collected in the MENA were retrieved from the GISAID public database, together with its metadata. Mutation analysis was conducted in Molecular Evolutionary Genetics Analysis software. Phylogenetic analysis was done using maximum likelihood (ML) and Bayesian methods. RESULT A total of 553 MENA sequences were analyzed and the most frequent S gene mutations included: D614G = 435, Q677H = 8, and V6F = 5. A significant increase in the proportion of D614G was noticed from (63.0%) in February 2020, to (98.5%) in June 2020 (p < 0.001). Two large phylogenetic clusters were identified via ML analysis, which showed an evidence of inter-country mixing of sequences, which dated back to February 8, 2020 and March 15, 2020 (median estimates). The mean evolutionary rate for SARS-CoV-2 was about 6.5 × 10-3 substitutions/site/year based on large clusters' Bayesian analyses. CONCLUSIONS The D614G mutation appeared to be taking over the COVID-19 infections in the MENA. Bayesian analysis suggested that SARS-CoV-2 might have been circulating in MENA earlier than previously reported.
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Affiliation(s)
- Malik Sallam
- Department of Pathology, Microbiology and Forensic Medicine, School of Medicine, The University of Jordan, Amman, Jordan
- Department of Clinical Laboratories and Forensic Medicine, Jordan University Hospital, Amman, Jordan
- Department of Translational Medicine, Faculty of Medicine, Lund University, Malmö, Sweden
| | - Nidaa A. Ababneh
- Cell Therapy Center (CTC), The University of Jordan, Amman, Jordan
| | - Deema Dababseh
- School of Dentistry, The University of Jordan, Amman, Jordan
| | - Faris G. Bakri
- Department of Internal Medicine, School of Medicine, The University of Jordan, Amman, Jordan
- Department of Internal Medicine, Jordan University Hospital, Amman, Jordan
- Infectious Diseases and Vaccine Center, University of Jordan, Amman, Jordan
| | - Azmi Mahafzah
- Department of Pathology, Microbiology and Forensic Medicine, School of Medicine, The University of Jordan, Amman, Jordan
- Department of Clinical Laboratories and Forensic Medicine, Jordan University Hospital, Amman, Jordan
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Delabouglise A, Thanh NTL, Xuyen HTA, Nguyen-Van-Yen B, Tuyet PN, Lam HM, Boni MF. Poultry farmer response to disease outbreaks in smallholder farming systems in southern Vietnam. eLife 2020; 9:59212. [PMID: 32840482 PMCID: PMC7505654 DOI: 10.7554/elife.59212] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 08/21/2020] [Indexed: 01/24/2023] Open
Abstract
Avian influenza outbreaks have been occurring on smallholder poultry farms in Asia for two decades. Farmer responses to these outbreaks can slow down or accelerate virus transmission. We used a longitudinal survey of 53 small-scale chicken farms in southern Vietnam to investigate the impact of outbreaks with disease-induced mortality on harvest rate, vaccination, and disinfection behaviors. We found that in small broiler flocks (≤16 birds/flock) the estimated probability of harvest was 56% higher when an outbreak occurred, and 214% higher if an outbreak with sudden deaths occurred in the same month. Vaccination and disinfection were strongly and positively correlated with the number of birds. Small-scale farmers – the overwhelming majority of poultry producers in low-income countries – tend to rely on rapid sale of birds to mitigate losses from diseases. As depopulated birds are sent to markets or trading networks, this reactive behavior has the potential to enhance onward transmission. The past few decades have seen the circulation of avian influenza viruses increase in domesticated poultry, regularly creating outbreaks associated with heavy economic loss. In addition, these viruses can sometimes ‘jump’ into humans, potentially allowing new diseases – including pandemics – to emerge. The Mekong river delta, in southern Vietnam, is one of the regions with the highest circulation of avian influenza. There, a large number of farmers practice poultry farming on a small scale, with limited investments in disease prevention such as vaccination or disinfection. Yet, it was unclear how the emergence of an outbreak could change the behavior of farmers. To learn more, Delabouglise et al. monitored 53 poultry farms, with fewer than 1000 chickens per farm, monthly for over a year and a half. In particular, they tracked when outbreaks occurred on each farm, and how farmers reacted. Overall, poultry farms with more than 17 chickens were more likely to vaccinate their animals and use disinfection practices than smaller farms. However, disease outbreaks did not affect vaccination or disinfection practices. When an outbreak occurred, farmers with fewer than 17 chickens tended to sell their animals earlier. For instance, they were 214% more likely to send their animals to market if an outbreak with sudden deaths occurred that month. Even if they do not make as much money selling immature individuals, this strategy may allow them to mitigate economical loss: they can sell animals that may die soon, saving on feeding costs and potentially avoiding further contamination. However, as animals were often sold alive in markets or to itinerant sellers, this practice increases the risk of spreading diseases further along the trade circuits. These data could be most useful to regional animal health authorities, which have detailed knowledge of local farming systems and personal connections in the communities where they work. This can allow them to effect change. They could work with small poultry farmers to encourage them to adopt efficient disease management strategies. Ultimately, this could help control the spread of avian influenza viruses, and potentially help to avoid future pandemics.
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Affiliation(s)
- Alexis Delabouglise
- Center for Infectious Diseases Dynamics, The Pennsylvania State University, University Park, United States.,UMR ASTRE, CIRAD, INRAE, Université de Montpellier, Montpellier, France
| | - Nguyen Thi Le Thanh
- Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
| | - Huynh Thi Ai Xuyen
- Ca Mau sub-Department of Livestock Production and Animal Health, Ca Mau, Viet Nam
| | - Benjamin Nguyen-Van-Yen
- Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam.,École Normale Supérieure, CNRS UMR 8197, Paris, France
| | - Phung Ngoc Tuyet
- Ca Mau sub-Department of Livestock Production and Animal Health, Ca Mau, Viet Nam
| | - Ha Minh Lam
- Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam.,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Maciej F Boni
- Center for Infectious Diseases Dynamics, The Pennsylvania State University, University Park, United States.,Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam.,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
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Knowledge and remaining gaps on the role of animal and human movements in the poultry production and trade networks in the global spread of avian influenza viruses - A scoping review. PLoS One 2020; 15:e0230567. [PMID: 32196515 PMCID: PMC7083317 DOI: 10.1371/journal.pone.0230567] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 03/03/2020] [Indexed: 12/28/2022] Open
Abstract
Poultry production has significantly increased worldwide, along with the number of avian influenza (AI) outbreaks and the potential threat for human pandemic emergence. The role of wild bird movements in this global spread has been extensively studied while the role of animal, human and fomite movement within commercial poultry production and trade networks remains poorly understood. The aim of this work is to better understand these roles in relation to the different routes of AI spread. A scoping literature review was conducted according to the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) using a search algorithm combining twelve domains linked to AI spread and animal/human movements within poultry production and trade networks. Only 28 out of 3,978 articles retrieved dealt especially with the role of animal, human and fomite movements in AI spread within the international trade network (4 articles), the national trade network (8 articles) and the production network (16 articles). While the role of animal movements in AI spread within national trade networks has been largely identified, human and fomite movements have been considered more at risk for AI spread within national production networks. However, the role of these movements has never been demonstrated with field data, and production networks have only been partially studied and never at international level. The complexity of poultry production networks and the limited access to production and trade data are important barriers to this knowledge. There is a need to study the role of animal and human movements within poultry production and trade networks in the global spread of AI in partnership with both public and private actors to fill this gap.
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Delabouglise A, Nguyen-Van-Yen B, Thanh NTL, Xuyen HTA, Tuyet PN, Lam HM, Boni MF. Poultry population dynamics and mortality risks in smallholder farms of the Mekong river delta region. BMC Vet Res 2019; 15:205. [PMID: 31208467 PMCID: PMC6580564 DOI: 10.1186/s12917-019-1949-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Accepted: 06/04/2019] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Poultry farming is widely practiced by rural households in Vietnam and the vast majority of domestic birds are kept on small household farms. However, smallholder poultry production is constrained by several issues such as infectious diseases, including avian influenza viruses whose circulation remains a threat to public health. This observational study describes the demographic structure and dynamics of small-scale poultry farms of the Mekong river delta region. METHOD Fifty three farms were monitored over a 20-month period, with farm sizes, species, age, arrival/departure of poultry, and farm management practices recorded monthly. RESULTS Median flock population sizes were 16 for chickens (IQR: 10-40), 32 for ducks (IQR: 18-101) and 11 for Muscovy ducks (IQR: 7-18); farm size distributions for the three species were heavily right-skewed. Muscovy ducks were kept for long periods and outdoors, while chickens and ducks were farmed indoors or in pens. Ducks had a markedly higher removal rate (broilers: 0.14/week; layer/breeders: 0.05/week) than chickens and Muscovy ducks (broilers: 0.07/week; layer/breeders: 0.01-0.02/week) and a higher degree of specialization resulting in a substantially shorter life span. The rate of mortality due to disease did not differ much among species, with birds being less likely to die from disease at older ages, but frequency of disease symptoms differed by species. Time series of disease-associated mortality were correlated with population size for Muscovy ducks (Kendall's coefficient τ = 0.49, p-value < 0.01) and with frequency of outdoor grazing for ducks (τ = 0.33, p-value = 0.05). CONCLUSION The study highlights some challenges to disease control in small-scale multispecies poultry farms. The rate of interspecific contact and overlap between flocks of different ages is high, making small-scale farms a suitable environment for pathogens circulation. Muscovy ducks are farmed outdoors with little investment in biosecurity and few inter-farm movements. Ducks and chickens are more at-risk of introduction of pathogens through movements of birds from one farm to another. Ducks are farmed in large flocks with high turnover and, as a result, are more vulnerable to disease spread and require a higher vaccination coverage to maintain herd immunity.
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Affiliation(s)
- Alexis Delabouglise
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, Millenium Sciences Complex, Pollock road, University Park, PA, 16802, USA.
| | - Benjamin Nguyen-Van-Yen
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam.,École Normale Supérieure, CNRS UMR 8197, 46 rue d'Ulm, Paris, France
| | - Nguyen Thi Le Thanh
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
| | - Huynh Thi Ai Xuyen
- Ca Mau sub-Department of Livestock Production and Animal Health, Ca Mau, Vietnam
| | - Phung Ngoc Tuyet
- Ca Mau sub-Department of Livestock Production and Animal Health, Ca Mau, Vietnam
| | - Ha Minh Lam
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam.,Center for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Maciej F Boni
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, Millenium Sciences Complex, Pollock road, University Park, PA, 16802, USA.,Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam.,Center for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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A systematic study towards evolutionary and epidemiological dynamics of currently predominant H5 highly pathogenic avian influenza viruses in Vietnam. Sci Rep 2019; 9:7723. [PMID: 31118431 PMCID: PMC6531488 DOI: 10.1038/s41598-019-42638-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Accepted: 03/07/2019] [Indexed: 12/02/2022] Open
Abstract
This study aimed to elucidate virus, host and environmental dynamics of Vietnamese H5 highly pathogenic avian influenza viruses (HPAIVs) during 2014–2017. Epidemiologically, H5 HPAIVs were frequently detected in apparently healthy domestic and Muscovy ducks and therefore these are preferred species for H5 HPAIV detection in active surveillance. Virologically, clade 2.3.2.1c and 2.3.4.4 H5 HPAIVs were predominant and exhibited distinct phylogeographic evolution. Clade 2.3.2.1c viruses clustered phylogenetically in North, Central and South regions, whilst clade 2.3.4.4 viruses only detected in North and Central regions formed small groups. These viruses underwent diverse reassortment with existence of at least 12 genotypes and retained typical avian-specific motifs. These H5 HPAIVs exhibited large antigenic distance from progenitor viruses and commercial vaccines currently used in poultry. Bayesian phylodynamic analysis inferred that clade 2.3.2.1c viruses detected during 2014–2017 were likely descended from homologous clade viruses imported to Vietnam previously and/or preexisting Chinese viruses during 2012–2013. Vietnamese clade 2.3.4.4 viruses closely shared genetic traits with contemporary foreign spillovers, suggesting that there existed multiple transboundary virus dispersals to Vietnam. This study provides insights into the evolution of Vietnamese H5 HPAIVs and highlights the necessity of strengthening control measures such as, preventive surveillance and poultry vaccination.
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13
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Nguyen LT, Stevenson MA, Firestone SM, Sims LD, Chu DH, Nguyen LV, Nguyen TN, Le KT, Isoda N, Matsuno K, Okamatsu M, Kida H, Sakoda Y. Spatiotemporal and risk analysis of H5 highly pathogenic avian influenza in Vietnam, 2014-2017. Prev Vet Med 2019; 178:104678. [PMID: 31113666 DOI: 10.1016/j.prevetmed.2019.04.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 03/10/2019] [Accepted: 04/13/2019] [Indexed: 10/27/2022]
Abstract
The aim of this study was to describe the spatiotemporal distribution of H5 HPAI outbreak reports for the period 2014-2017 and to identify factors associated with H5 HPAI outbreak reports. Throughout the study period, a total of 139 outbreaks of H5 HPAI in poultry were reported, due to either H5N1 (96 outbreaks) or H5N6 (43 outbreaks) subtype viruses. H5N1 HPAI outbreaks occurred in all areas of Vietnam while H5N6 HPAI outbreaks were only reported in the northern and central provinces. We counted the number of H5N1 and H5N6 outbreak report-positive districts per province over the four-year study period and calculated the provincial-level standardized morbidity ratio for H5N1 and H5N6 outbreak reports as the observed number of positive districts divided by the expected number. A mixed-effects, zero-inflated Poisson regression model was developed to identify risk factors for outbreak reports of each H5N1 and H5N6 subtype virus. Spatially correlated and uncorrelated random effects terms were included in this model to identify areas of the country where outbreak reports occurred after known risk factors had been accounted-for. The presence of an outbreak report in a province in the previous 6-12 months increased the provincial level H5N1 outbreak report risk by a factor of 2.42 (95% Bayesian credible interval [CrI] 1.27-4.60) while 1000 bird increases in the density of chickens decreased provincial level H5N6 outbreak report risk by a factor of 0.65 (95% CrI 0.38 to 0.97). We document distinctly different patterns in the spatial and temporal distribution of H5N1 and H5N6 outbreak reports. Most of the variation in H5N1 report risk was accounted-for by the fixed effects included in the zero-inflated Poisson model. In contrast, the amount of unaccounted-for risk in the H5N6 model was substantially greater than the H5N1 model. For H5N6 we recommend that targeted investigations should be carried out in provinces with relatively large spatially correlated random effect terms to identify likely determinants of disease. Similarly, investigations should be carried out in provinces with relatively low spatially correlated random effect terms to identify protective factors for disease and/or reasons for failure to report.
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Affiliation(s)
- Lam Thanh Nguyen
- Laboratory of Microbiology, Department of Disease Control, Graduate School of Veterinary Medicine, Hokkaido University, North 18, West 9, Kita-ku, Sapporo, Hokkaido, 060-0818, Japan; Department of Veterinary Medicine, College of Agriculture, Can Tho University, Campus II, 3/2 Street, Ninh Kieu, Can Tho, Viet Nam
| | - Mark A Stevenson
- Asia-Pacific Centre for Animal Health, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Victoria, 3010, Australia.
| | - Simon M Firestone
- Asia-Pacific Centre for Animal Health, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Victoria, 3010, Australia
| | - Leslie D Sims
- Asia Pacific Veterinary Information Services, Montmorency, Victoria, 3094, Australia
| | - Duc Huy Chu
- Department of Animal Health, Ministry of Agriculture and Rural Development, Ha Noi, Viet Nam
| | - Long Van Nguyen
- Department of Animal Health, Ministry of Agriculture and Rural Development, Ha Noi, Viet Nam
| | - Tien Ngoc Nguyen
- Department of Animal Health, Ministry of Agriculture and Rural Development, Ha Noi, Viet Nam
| | - Kien Trung Le
- Laboratory of Microbiology, Department of Disease Control, Graduate School of Veterinary Medicine, Hokkaido University, North 18, West 9, Kita-ku, Sapporo, Hokkaido, 060-0818, Japan
| | - Norikazu Isoda
- Research Center for Zoonosis Control, Hokkaido University, North 20, West 10, Kita-ku, Sapporo, Hokkaido, 001-0020, Japan; Global Institution for Collaborative Research and Education, Hokkaido University, North 20, West 10, Kita-ku, Sapporo, Hokkaido 001-0020, Japan
| | - Keita Matsuno
- Laboratory of Microbiology, Department of Disease Control, Graduate School of Veterinary Medicine, Hokkaido University, North 18, West 9, Kita-ku, Sapporo, Hokkaido, 060-0818, Japan; Global Institution for Collaborative Research and Education, Hokkaido University, North 20, West 10, Kita-ku, Sapporo, Hokkaido 001-0020, Japan
| | - Masatoshi Okamatsu
- Laboratory of Microbiology, Department of Disease Control, Graduate School of Veterinary Medicine, Hokkaido University, North 18, West 9, Kita-ku, Sapporo, Hokkaido, 060-0818, Japan
| | - Hiroshi Kida
- Research Center for Zoonosis Control, Hokkaido University, North 20, West 10, Kita-ku, Sapporo, Hokkaido, 001-0020, Japan; Global Institution for Collaborative Research and Education, Hokkaido University, North 20, West 10, Kita-ku, Sapporo, Hokkaido 001-0020, Japan
| | - Yoshihiro Sakoda
- Laboratory of Microbiology, Department of Disease Control, Graduate School of Veterinary Medicine, Hokkaido University, North 18, West 9, Kita-ku, Sapporo, Hokkaido, 060-0818, Japan; Global Institution for Collaborative Research and Education, Hokkaido University, North 20, West 10, Kita-ku, Sapporo, Hokkaido 001-0020, Japan.
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14
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Mellor KC, Meyer A, Elkholly DA, Fournié G, Long PT, Inui K, Padungtod P, Gilbert M, Newman SH, Vergne T, Pfeiffer DU, Stevens KB. Comparative Epidemiology of Highly Pathogenic Avian Influenza Virus H5N1 and H5N6 in Vietnamese Live Bird Markets: Spatiotemporal Patterns of Distribution and Risk Factors. Front Vet Sci 2018; 5:51. [PMID: 29675418 PMCID: PMC5896172 DOI: 10.3389/fvets.2018.00051] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Accepted: 02/27/2018] [Indexed: 01/08/2023] Open
Abstract
Highly pathogenic avian influenza (HPAI) H5N1 virus has been circulating in Vietnam since 2003, whilst outbreaks of HPAI H5N6 virus are more recent, having only been reported since 2014. Although the spatial distribution of H5N1 outbreaks and risk factors for virus occurrence has been extensively studied, there have been no comparative studies for H5N6. Data collected through active surveillance of Vietnamese live bird markets (LBMs) between 2011 and 2015 were used to explore and compare the spatiotemporal distributions of H5N1- and H5N6-positive LBMs. Conditional autoregressive models were developed to quantify spatiotemporal associations between agroecological factors and the two HPAI strains using the same set of predictor variables. Unlike H5N1, which exhibited a strong north–south divide, with repeated occurrence in the extreme south of a cluster of high-risk provinces, H5N6 was homogeneously distributed throughout Vietnam. Similarly, different agroecological factors were associated with each strain. Sample collection in the months of January and February and higher average maximum temperature were associated with higher likelihood of H5N1-positive market-day status. The likelihood of market days being positive for H5N6 increased with decreased river density, and with successive Rounds of data collection. This study highlights marked differences in spatial patterns and risk factors for H5N1 and H5N6 in Vietnam, suggesting the need for tailored surveillance and control approaches.
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Affiliation(s)
- Kate C Mellor
- Veterinary Epidemiology, Economics and Public Health Group, Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, United Kingdom
| | - Anne Meyer
- Veterinary Epidemiology, Economics and Public Health Group, Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, United Kingdom
| | - Doaa A Elkholly
- Veterinary Epidemiology, Economics and Public Health Group, Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, United Kingdom
| | - Guillaume Fournié
- Veterinary Epidemiology, Economics and Public Health Group, Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, United Kingdom
| | - Pham T Long
- Department of Animal Health, Ministry of Agriculture and Rural Development, Hanoi, Vietnam
| | - Ken Inui
- Country Office for Vietnam, Food and Agriculture Organization of the United Nations, Hanoi, Vietnam
| | - Pawin Padungtod
- Country Office for Vietnam, Food and Agriculture Organization of the United Nations, Hanoi, Vietnam
| | - Marius Gilbert
- Spatial Epidemiology Laboratory, Université Libre de Bruxelles, Brussels, Belgium
| | - Scott H Newman
- Country Office for Vietnam, Food and Agriculture Organization of the United Nations, Hanoi, Vietnam.,Country Office for Ethiopia, Food and Agriculture Organization of the United Nations, Addis Ababa, Ethiopia
| | - Timothée Vergne
- Veterinary Epidemiology, Economics and Public Health Group, Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, United Kingdom.,Maladies Infectieuses et Vecteurs Ecologie, Génétique, Evolution et Contrôle (MIVEGEC), Institut de Recherche pour le Développement (IRD), Montpellier, France.,UMR 1225 INRA, ENVT Interactions Hôtes - Agents Pathogènes (IHAP), University of Toulouse, Toulouse, France
| | - Dirk U Pfeiffer
- Veterinary Epidemiology, Economics and Public Health Group, Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, United Kingdom.,College of Veterinary Medicine & Life Sciences, City University of Hong Kong, Kowloon, Hong Kong
| | - Kim B Stevens
- Veterinary Epidemiology, Economics and Public Health Group, Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, United Kingdom
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15
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Moyen N, Ahmed G, Gupta S, Tenzin T, Khan R, Khan T, Debnath N, Yamage M, Pfeiffer DU, Fournie G. A large-scale study of a poultry trading network in Bangladesh: implications for control and surveillance of avian influenza viruses. BMC Vet Res 2018; 14:12. [PMID: 29329534 PMCID: PMC5767022 DOI: 10.1186/s12917-018-1331-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Accepted: 01/02/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Since its first report in 2007, avian influenza (AI) has been endemic in Bangladesh. While live poultry marketing is widespread throughout the country and known to influence AI dissemination and persistence, trading patterns have not been described. The aim of this study is to assess poultry trading practices and features of the poultry trading networks which could promote AI spread, and their potential implications for disease control and surveillance. Data on poultry trading practices was collected from 849 poultry traders during a cross-sectional survey in 138 live bird markets (LBMs) across 17 different districts of Bangladesh. The quantity and origins of traded poultry were assessed for each poultry type in surveyed LBMs. The network of contacts between farms and LBMs resulting from commercial movements of live poultry was constructed to assess its connectivity and to identify the key premises influencing it. RESULTS Poultry trading practices varied according to the size of the LBMs and to the type of poultry traded. Industrial broiler chickens, the most commonly traded poultry, were generally sold in LBMs close to their production areas, whereas ducks and backyard chickens were moved over longer distances, and their transport involved several intermediates. The poultry trading network composed of 445 nodes (73.2% were LBMs) was highly connected and disassortative. However, the removal of only 5.6% of the nodes (25 LBMs with the highest betweenness scores), reduced the network's connectedness, and the maximum size of output and input domains by more than 50%. CONCLUSIONS Poultry types need to be discriminated in order to understand the way in which poultry trading networks are shaped, and the level of risk of disease spread that these networks may promote. Knowledge of the network structure could be used to target control and surveillance interventions to a small number of LBMs.
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Affiliation(s)
- N Moyen
- Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hatfield, Hertfordshire, AL9 7TA, UK.
| | - G Ahmed
- Emergency Centre for Transboundary Animal Diseases, Food and Agriculture Organisation of the United Nations, Dhaka, Bangladesh
| | - S Gupta
- School of Veterinary Science, The University of Queensland, Gatton, 4343, Qld, Australia.,Emergency Centre for Transboundary Animal Diseases, Food and Agriculture Organisation of the United Nations, Dhaka, Bangladesh
| | - T Tenzin
- Emergency Centre for Transboundary Animal Diseases, Food and Agriculture Organisation of the United Nations, Dhaka, Bangladesh.,National Centre for Animal Health, Thimphu, Bhutan
| | - R Khan
- Emergency Centre for Transboundary Animal Diseases, Food and Agriculture Organisation of the United Nations, Dhaka, Bangladesh
| | - T Khan
- Emergency Centre for Transboundary Animal Diseases, Food and Agriculture Organisation of the United Nations, Dhaka, Bangladesh
| | - N Debnath
- Emergency Centre for Transboundary Animal Diseases, Food and Agriculture Organisation of the United Nations, Dhaka, Bangladesh
| | - M Yamage
- Emergency Centre for Transboundary Animal Diseases, Food and Agriculture Organisation of the United Nations, Dhaka, Bangladesh
| | - D U Pfeiffer
- Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hatfield, Hertfordshire, AL9 7TA, UK.,College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong
| | - G Fournie
- Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, Hatfield, Hertfordshire, AL9 7TA, UK
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