1
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Kirkeby C, Boklund A, Larsen LE, Ward MP. Are all avian influenza outbreaks in poultry the same? The predicted impact of poultry species and virus subtype. Zoonoses Public Health 2024; 71:314-323. [PMID: 38362732 DOI: 10.1111/zph.13116] [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: 04/21/2023] [Revised: 11/15/2023] [Accepted: 01/30/2024] [Indexed: 02/17/2024]
Abstract
AIMS Outbreaks of avian influenza in poultry farms are currently increasing in frequency, with devastating consequences for animal welfare, farmers and supply chains. Some studies have documented the direct spread of the avian influenza virus between farms. Prevention of spread between farms relies on biosecurity surveillance and control measures. However, the evolution of an outbreak on a farm might vary depending on the virus strain and poultry species involved; this would have important implications for surveillance systems, epidemiological investigations and control measures. METHODS AND RESULTS In this study, we utilized existing parameter estimates from the literature to evaluate the predicted course of an epidemic in a standard poultry flock with 10,000 birds. We used a stochastic SEIR simulation model to simulate outbreaks in different species and with different virus subtypes. The simulations predicted large differences in the duration and severity of outbreaks, depending on the virus subtypes. For both turkeys and chickens, outbreaks with HPAI were of shorter duration than outbreaks with LPAI. In outbreaks involving the infection of chickens with different virus subtypes, the shortest epidemic involved H7N7 and HPAIV H5N1 (median duration of 9 and 17 days, respectively) and the longest involved H5N2 (median duration of 68 days). The most severe outbreaks (number of chickens infected) were predicted for H5N1, H7N1 and H7N3 virus subtypes, and the least severe for H5N2 and H7N7, in which outbreaks for the latter subtype were predicted to develop most slowly. CONCLUSIONS These simulation results suggest that surveillance of certain subtypes of avian influenza virus, in chicken flocks in particular, needs to be sensitive and timely if infection is to be detected with sufficient time to implement control measures. The variability in the predictions highlights that avian influenza outbreaks are different in severity, speed and duration, so surveillance and disease response need to be nuanced and fit the specific context of poultry species and virus subtypes.
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Affiliation(s)
- Carsten Kirkeby
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Anette Boklund
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Lars Erik Larsen
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Michael P Ward
- Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, New South Wales, Australia
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2
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Raj S, Alizadeh M, Matsuyama-Kato A, Boodhoo N, Denis MS, Nagy É, Mubareka S, Karimi K, Behboudi S, Sharif S. Efficacy of an inactivated influenza vaccine adjuvanted with Toll-like receptor ligands against transmission of H9N2 avian influenza virus in chickens. Vet Immunol Immunopathol 2024; 268:110715. [PMID: 38219434 DOI: 10.1016/j.vetimm.2024.110715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Revised: 12/27/2023] [Accepted: 01/02/2024] [Indexed: 01/16/2024]
Abstract
Avian influenza viruses (AIV), including the H9N2 subtype, pose a major threat to the poultry industry as well as to human health. Although vaccination provides a protective control measure, its effect on transmission remains uncertain in chickens. The objective of the present study was to investigate the efficacy of beta-propiolactone (BPL) whole inactivated H9N2 virus (WIV) vaccine either alone or in combination with CpG ODN 2007 (CpG), poly(I:C) or AddaVax™ (ADD) to prevent H9N2 AIV transmission in chickens. The seeder chickens (trial 1) and recipient chickens (trial 2) were vaccinated twice with different vaccine formulations. Ten days after secondary vaccination, seeder chickens were infected with H9N2 AIV (trial 1) and co-housed with healthy recipient chickens. In trial 2, the recipient chickens were vaccinated and then exposed to H9N2 AIV-infected seeder chickens. Our results demonstrated that BPL+ CpG and BPL+ poly(I:C) treated chickens exhibited reduced oral and cloacal shedding in both trials post-exposure (PE). The number of H9N2 AIV+ recipient chickens in the BPL+ CpG group (trial 1) was lower than in other vaccinated groups, and the reduction was higher in BPL+ CpG recipient chickens in trial 2. BPL+ CpG vaccinated chickens demonstrated enhanced systemic antibody responses with high IgM and IgY titers with higher rates of seroprotection by day 21 post-primary vaccination (ppv). Additionally, the induction of IFN-γ expression and production was higher in the BPL+ CpG treated chickens. Interleukin (IL)- 2 expression was upregulated in both BPL+ CpG and BPL+ poly(I:C) groups at 12 and 24 hr post-stimulation.
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Affiliation(s)
- Sugandha Raj
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Mohammadali Alizadeh
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Ayumi Matsuyama-Kato
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Nitish Boodhoo
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Myles St Denis
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Éva Nagy
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Samira Mubareka
- Sunnybrook Research Institute, Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Khalil Karimi
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Shahriar Behboudi
- The Pirbright Institute, Pirbright, Woking, Surrey GU24 0NE, United Kingdom
| | - Shayan Sharif
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada.
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3
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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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4
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Raj S, Alizadeh M, Shoojadoost B, Hodgins D, Nagy É, Mubareka S, Karimi K, Behboudi S, Sharif S. Determining the Protective Efficacy of Toll-Like Receptor Ligands to Minimize H9N2 Avian Influenza Virus Transmission in Chickens. Viruses 2023; 15:238. [PMID: 36680279 PMCID: PMC9861619 DOI: 10.3390/v15010238] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 01/10/2023] [Accepted: 01/12/2023] [Indexed: 01/18/2023] Open
Abstract
Low-pathogenicity avian influenza viruses (AIV) of the H9N2 subtype can infect and cause disease in chickens. Little is known about the efficacy of immune-based strategies for reducing the transmission of these viruses. The present study investigated the efficacy of Toll-like receptor (TLR) ligands (CpG ODN 2007 and poly(I:C)) to reduce H9N2 AIV transmission from TLR-treated seeder (trial 1) or inoculated chickens (trial 2) to naive chickens. The results from trial 1 revealed that a low dose of CpG ODN 2007 led to the highest reduction in oral shedding, and a high dose of poly(I:C) was effective at reducing oral and cloacal shedding. Regarding transmission, the recipient chickens exposed to CpG ODN 2007 low-dose-treated seeder chickens showed a maximum reduction in shedding with the lowest number of AIV+ chickens. The results from trial 2 revealed a maximum reduction in oral and cloacal shedding in the poly(I:C) high-dose-treated chickens (recipients), followed by the low-dose CpG ODN 2007 group. In these two groups, the expression of type I interferons (IFNs), protein kinase R (PKR), interferon-induced transmembrane protein 3 (IFITM3), viperin, and (interleukin) IL-1β, IL-8, and 1L-18 was upregulated in the spleen, cecal tonsils and lungs. Hence, TLR ligands can reduce AIV transmission in chickens.
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Affiliation(s)
- Sugandha Raj
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Mohammadali Alizadeh
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
| | | | - Douglas Hodgins
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Éva Nagy
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Samira Mubareka
- Sunnybrook Research Institute, Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Khalil Karimi
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
| | | | - Shayan Sharif
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
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5
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Hayama Y, Sawai K, Yoshinori M, Yamaguchi E, Yamamoto T. Estimation of introduction time window of highly pathogenic avian influenza virus into broiler chicken farms during the 2020 - 2021 winter season outbreak in Japan. Prev Vet Med 2022; 208:105768. [PMID: 36174447 DOI: 10.1016/j.prevetmed.2022.105768] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 08/01/2022] [Accepted: 09/21/2022] [Indexed: 10/31/2022]
Abstract
When an infectious disease occurs in an area, early detection of infected farms is important to respond quickly and contain the outbreak on a small scale. Estimating the time window for the introduction of the infection is important for its prevention and control. The aim of this study was to estimate the farm-specific time window from the introduction of the highly pathogenic avian influenza (HPAI) virus into poultry farms using field data from the HPAI H5N8 outbreak in the 2020-2021 winter season in Japan. Daily mortality data from 12 broiler chicken farms during the outbreak were used for the analysis. A mathematical model (Susceptible-Exposed-Infectious-Removed, SEIR model) was applied to generate the within-flock transmission of HPAI. The model-predicted mortality was fitted to the observed excess mortality data induced by HPAI to estimate the farm-specific transmission rate and the time of virus introduction. The estimated value of the transmission rate in each farm was 1.449 day-1 in median (min: 0.661 day-1, max: 3.387 day-1). The time window from the introduction of the virus to notification in each farm was estimated at 14.0 days in median (min: 8.6 days, max: 24.1 days) in the deterministic model. In addition, in the stochastic model considering the randomness of transmission in the early phase of the outbreak, the upper value of 95 % credible interval of the time window ranged from 12 to 34 days, with a median of 21 days. The results suggest that although one to three weeks had elapsed on most farms until notification after the virus introduction, the time window could exceed three weeks considering the stochasticity of disease transmission. As for the potential farm characteristics affecting within-flock transmission, the transmission rate was smaller (p-value=0.02) and the estimated time window from introduction to notification was longer (p-value=0.02) when birds were older. This study provides reliable information for setting up a tracing period for a potential source farm and enhancing the efforts for early detection.
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Affiliation(s)
- Yoko Hayama
- Division of Transboundary Animal Disease Research, National Institute of Animal Health, National Agriculture and Food Research Organization, Tsukuba, Ibaraki, Japan.
| | - Kotaro Sawai
- Division of Transboundary Animal Disease Research, National Institute of Animal Health, National Agriculture and Food Research Organization, Tsukuba, Ibaraki, Japan
| | - Murato Yoshinori
- Division of Transboundary Animal Disease Research, National Institute of Animal Health, National Agriculture and Food Research Organization, Tsukuba, Ibaraki, Japan
| | - Emi Yamaguchi
- Division of Transboundary Animal Disease Research, National Institute of Animal Health, National Agriculture and Food Research Organization, Tsukuba, Ibaraki, Japan
| | - Takehisa Yamamoto
- Division of Transboundary Animal Disease Research, National Institute of Animal Health, National Agriculture and Food Research Organization, Tsukuba, Ibaraki, Japan
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6
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Simulated Flock-Level Shedding Characteristics of Turkeys in Ten Thousand Bird Houses Infected with H7 Low Pathogenicity Avian Influenza Virus Strains. Viruses 2021; 13:v13122509. [PMID: 34960777 PMCID: PMC8706675 DOI: 10.3390/v13122509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 12/09/2021] [Accepted: 12/10/2021] [Indexed: 12/03/2022] Open
Abstract
Understanding the amount of virus shed at the flock level by birds infected with low pathogenicity avian influenza virus (LPAIV) over time can help inform the type and timing of activities performed in response to a confirmed LPAIV-positive premises. To this end, we developed a mathematical model which allows us to estimate viral shedding by 10,000 turkey toms raised in commercial turkey production in the United States, and infected by H7 LPAIV strains. We simulated the amount of virus shed orally and from the cloaca over time, as well as the amount of virus in manure. In addition, we simulated the threshold cycle value (Ct) of pooled oropharyngeal swabs from birds in the infected flock tested by real-time reverse transcription polymerase chain reaction. The simulation model predicted that little to no shedding would occur once the highest threshold of seroconversion was reached. Substantial amounts of virus in manure (median 1.5×108 and 5.8×109; 50% egg infectious dose) were predicted at the peak. Lastly, the model results suggested that higher Ct values, indicating less viral shedding, are more likely to be observed later in the infection process as the flock approaches recovery.
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7
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Estimating epidemiological parameters using diagnostic testing data from low pathogenicity avian influenza infected turkey houses. Sci Rep 2021; 11:1602. [PMID: 33452377 PMCID: PMC7810853 DOI: 10.1038/s41598-021-81254-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 01/05/2021] [Indexed: 11/28/2022] Open
Abstract
Limiting spread of low pathogenicity avian influenza (LPAI) during an outbreak is critical to reduce the negative impact on poultry producers and local economies. Mathematical models of disease transmission can support outbreak control efforts by estimating relevant epidemiological parameters. In this article, diagnostic testing data from each house on a premises infected during a LPAI H5N2 outbreak in the state of Minnesota in the United States in 2018 was used to estimate the time of virus introduction and adequate contact rate, which determines the rate of disease spread. A well-defined most likely time of virus introduction, and upper and lower 95% credibility intervals were estimated for each house. The length of the 95% credibility intervals ranged from 11 to 22 with a mean of 17 days. In some houses the contact rate estimates were also well-defined; however, the estimated upper 95% credibility interval bound for the contact rate was occasionally dependent on the upper bound of the prior distribution. The estimated modes ranged from 0.5 to 6.0 with a mean of 2.8 contacts per day. These estimates can be improved with early detection, increased testing of monitored premises, and combining the results of multiple barns that possess similar production systems.
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8
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Escalera-Zamudio M, Golden M, Gutiérrez B, Thézé J, Keown JR, Carrique L, Bowden TA, Pybus OG. Parallel evolution in the emergence of highly pathogenic avian influenza A viruses. Nat Commun 2020; 11:5511. [PMID: 33139731 PMCID: PMC7608645 DOI: 10.1038/s41467-020-19364-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 10/12/2020] [Indexed: 01/30/2023] Open
Abstract
Parallel molecular evolution and adaptation are important phenomena commonly observed in viruses. Here, we exploit parallel molecular evolution to understand virulence evolution in avian influenza viruses (AIV). Highly-pathogenic AIVs evolve independently from low-pathogenic ancestors via acquisition of polybasic cleavage sites. Why some AIV lineages but not others evolve in this way is unknown. We hypothesise that the parallel emergence of highly-pathogenic AIV may be facilitated by permissive or compensatory mutations occurring across the viral genome. We combine phylogenetic, statistical and structural approaches to discover parallel mutations in AIV genomes associated with the highly-pathogenic phenotype. Parallel mutations were screened using a statistical test of mutation-phenotype association and further evaluated in the contexts of positive selection and protein structure. Our resulting mutational panel may help to reveal new links between virulence evolution and other traits, and raises the possibility of predicting aspects of AIV evolution.
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Affiliation(s)
| | - Michael Golden
- Department of Zoology, Oxford University, Parks Rd, Oxford, OX1 3PS, UK
| | | | - Julien Thézé
- Department of Zoology, Oxford University, Parks Rd, Oxford, OX1 3PS, UK
| | - Jeremy Russell Keown
- Division of Structural Biology, Wellcome Centre for Human Genetics, Oxford, OX3 7BN, UK
| | - Loic Carrique
- Division of Structural Biology, Wellcome Centre for Human Genetics, Oxford, OX3 7BN, UK
| | - Thomas A Bowden
- Division of Structural Biology, Wellcome Centre for Human Genetics, Oxford, OX3 7BN, UK
| | - Oliver G Pybus
- Department of Zoology, Oxford University, Parks Rd, Oxford, OX1 3PS, UK.
- Department of Pathobiology and Population Sciences, Royal Veterinary College, London, UK.
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9
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Saad-Roy CM, McDermott AB, Grenfell BT. Dynamic Perspectives on the Search for a Universal Influenza Vaccine. J Infect Dis 2020; 219:S46-S56. [PMID: 30715467 DOI: 10.1093/infdis/jiz044] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
A universal influenza vaccine (UIV) could considerably alleviate the public health burden of both seasonal and pandemic influenza. Although significant progress has been achieved in clarifying basic immunology and virology relating to UIV, several important questions relating to the dynamics of infection, immunity, and pathogen evolution remain unsolved. In this study, we review these gaps, which span integrative levels, from cellular to global and timescales from molecular events to decades. We argue that they can be best addressed by a tight integration of empirical (laboratory, epidemiological) research and theory and suggest fruitful areas for this synthesis. In particular, quantifying natural and vaccinal limitations on viral transmission are central to this effort.
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Affiliation(s)
| | - Adrian B McDermott
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases
| | - Bryan T Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, New Jersey.,Woodrow Wilson School of Public and International Affairs, Princeton University, New Jersey.,Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland
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10
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Abstract
In the last several decades, avian influenza virus has caused numerous outbreaks around the world. These outbreaks pose a significant threat to the poultry industry and also to public health. When an avian influenza (AI) outbreak occurs, it is critical to make informed decisions about the potential risks, impact, and control measures. To this end, many modeling approaches have been proposed to acquire knowledge from different sources of data and perspectives to enhance decision making. Although some of these approaches have shown to be effective, they do not follow the process of knowledge discovery in databases (KDD). KDD is an iterative process, consisting of five steps, that aims at extracting unknown and useful information from the data. The present review attempts to survey AI modeling methods in the context of KDD process. We first divide the modeling techniques used in AI into two main categories: data-intensive modeling and small-data modeling. We then investigate the existing gaps in the literature and suggest several potential directions and techniques for future studies. Overall, this review provides insights into the control of AI in terms of the risk of introduction and spread of the virus.
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11
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Germeraad EA, Sanders P, Hagenaars TJ, Jong MCMD, Beerens N, Gonzales JL. Virus Shedding of Avian Influenza in Poultry: A Systematic Review and Meta-Analysis. Viruses 2019; 11:v11090812. [PMID: 31480744 PMCID: PMC6784017 DOI: 10.3390/v11090812] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 08/14/2019] [Accepted: 08/21/2019] [Indexed: 11/19/2022] Open
Abstract
Understanding virus shedding patterns of avian influenza virus (AIV) in poultry is important for understanding host-pathogen interactions and developing effective control strategies. Many AIV strains were studied in challenge experiments in poultry, but no study has combined data from those studies to identify general AIV shedding patterns. These systematic review and meta-analysis were performed to summarize qualitative and quantitative information on virus shedding levels and duration for different AIV strains in experimentally infected poultry species. Methods were designed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Four electronic databases were used to collect literature. A total of 1155 abstract were screened, with 117 studies selected for the qualitative analysis and 71 studies for the meta-analysis. A large heterogeneity in experimental methods was observed and the quantitative analysis showed that experimental variables such as species, virus origin, age, inoculation route and dose, affect virus shedding (mean, peak and duration) for highly pathogenic AIV (HPAIV), low pathogenic AIV (LPAIV) or both. In conclusion, this study highlights the need to standardize experimental procedures, it provides a comprehensive summary of the shedding patterns of AIV strains by infected poultry and identifies the variables that influence the level and duration of AIV shedding.
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Affiliation(s)
- Evelien A Germeraad
- Department of Virology, Wageningen Bioveterinary Research (WBVR), P.O. Box 65, 8200 AB Lelystad, The Netherlands.
| | - Pim Sanders
- Department of Bacteriology and Epidemiology, WBVR, P.O. Box 65, 8200 AB Lelystad, The Netherlands
- Quantitative Veterinary Epidemiology, Wageningen UR, P.O. Box 338, 6700AH Wageningen, The Netherlands
| | - Thomas J Hagenaars
- Department of Bacteriology and Epidemiology, WBVR, P.O. Box 65, 8200 AB Lelystad, The Netherlands
| | - Mart C M de Jong
- Quantitative Veterinary Epidemiology, Wageningen UR, P.O. Box 338, 6700AH Wageningen, The Netherlands
| | - Nancy Beerens
- Department of Virology, Wageningen Bioveterinary Research (WBVR), P.O. Box 65, 8200 AB Lelystad, The Netherlands
| | - Jose L Gonzales
- Department of Bacteriology and Epidemiology, WBVR, P.O. Box 65, 8200 AB Lelystad, The Netherlands
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12
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Barnes B, Scott A, Hernandez-Jover M, Toribio JA, Moloney B, Glass K. Modelling high pathogenic avian influenza outbreaks in the commercial poultry industry. Theor Popul Biol 2019; 126:59-71. [DOI: 10.1016/j.tpb.2019.02.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Revised: 12/23/2018] [Accepted: 02/15/2019] [Indexed: 10/27/2022]
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13
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Ssematimba A, Malladi S, Hagenaars TJ, Bonney PJ, Weaver JT, Patyk KA, Spackman E, Halvorson DA, Cardona CJ. Estimating within-flock transmission rate parameter for H5N2 highly pathogenic avian influenza virus in Minnesota turkey flocks during the 2015 epizootic. Epidemiol Infect 2019; 147:e179. [PMID: 31063119 PMCID: PMC6518789 DOI: 10.1017/s0950268819000633] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 02/13/2019] [Accepted: 03/11/2019] [Indexed: 11/29/2022] Open
Abstract
Better control of highly pathogenic avian influenza (HPAI) outbreaks requires deeper understanding of within-flock virus transmission dynamics. For such fatal diseases, daily mortality provides a proxy for disease incidence. We used the daily mortality data collected during the 2015 H5N2 HPAI outbreak in Minnesota turkey flocks to estimate the within-flock transmission rate parameter (β). The number of birds in Susceptible, Exposed, Infectious and Recovered compartments was inferred from the data and used in a generalised linear mixed model (GLMM) to estimate the parameters. Novel here was the correction of these data for normal mortality before use in the fitting process. We also used mortality threshold to determine HPAI-like mortality to improve the accuracy of estimates from the back-calculation approach. The estimated β was 3.2 (95% confidence interval (CI) 2.3-4.3) per day with a basic reproduction number of 12.8 (95% CI 9.2-17.2). Although flock-level estimates varied, the overall estimate was comparable to those from other studies. Sensitivity analyses demonstrated that the estimated β was highly sensitive to the bird-level latent period, emphasizing the need for its precise estimation. In all, for fatal poultry diseases, the back-calculation approach provides a computationally efficient means to obtain reasonable transmission parameter estimates from mortality data.
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Affiliation(s)
- A. Ssematimba
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, 1971 Commonwealth Avenue, Saint Paul, MN 55108, USA
- Department of Mathematics, Faculty of Science, Gulu University, P.O. Box 166, Gulu, Uganda
| | - S. Malladi
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, 1971 Commonwealth Avenue, Saint Paul, MN 55108, USA
| | - T. J. Hagenaars
- Department of Bacteriology and Epidemiology, Wageningen Bioveterinary Research, P.O. Box 65, 8200AB Lelystad, The Netherlands
| | - P. J. Bonney
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, 1971 Commonwealth Avenue, Saint Paul, MN 55108, USA
| | - J. T. Weaver
- United States Department of Agriculture, Animal and Plant Health Inspection Service, Veterinary Services, Science, Technology, and Analysis Services, Center for Epidemiology and Animal Health, Natural Resources Research Center, Bldg. B MS-2W4, 2150 Centre Avenue, Fort Collins, CO 80526, USA
| | - K. A. Patyk
- United States Department of Agriculture, Animal and Plant Health Inspection Service, Veterinary Services, Science, Technology, and Analysis Services, Center for Epidemiology and Animal Health, Natural Resources Research Center, Bldg. B MS-2W4, 2150 Centre Avenue, Fort Collins, CO 80526, USA
| | - E. Spackman
- Exotic and Emerging Avian Viral Diseases Unit, US National Poultry Research Center, USDA-ARS, 934 College Station Rd. Athens, GA 30605, USA
| | - D. A. Halvorson
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, 1971 Commonwealth Avenue, Saint Paul, MN 55108, USA
| | - C. J. Cardona
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, 1971 Commonwealth Avenue, Saint Paul, MN 55108, USA
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14
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Gonzales JL, Roberts H, Smietanka K, Baldinelli F, Ortiz-Pelaez A, Verdonck F. Assessment of low pathogenic avian influenza virus transmission via raw poultry meat and raw table eggs. EFSA J 2018; 16:e05431. [PMID: 32625713 PMCID: PMC7009628 DOI: 10.2903/j.efsa.2018.5431] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
A rapid qualitative assessment has been done by performing a theoretical analysis on the transmission of low pathogenic avian influenza (LPAI) via fresh meat from poultry reared or kept in captivity for the production of meat (raw poultry meat) or raw table eggs. A predetermined transmission pathway followed a number of steps from a commercial or non-commercial poultry establishment within the EU exposed to LPAI virus (LPAIV) to the onward virus transmission to animals and humans. The combined probability of exposure and subsequent LPAIV infection via raw poultry meat containing LPAIV is negligible for commercial poultry and humans exposed via consumption whereas it is very unlikely for non-commercial poultry, wild birds and humans exposed via handling and manipulation. The probability of LPAIV transmission from an individual infected via raw poultry meat containing LPAIV is negligible for commercial poultry and humans, whereas it is very unlikely for non-commercial poultry and wild birds. The combined probability of exposure and subsequent LPAIV infection via raw table eggs containing LPAIV is negligible for commercial poultry and humans and extremely unlikely to negligible for non-commercial poultry and wild birds. The probability of LPAIV transmission from an individual infected via raw table eggs containing LPAIV is negligible for commercial poultry and humans and very unlikely to negligible for non-commercial poultry and wild birds. Although the presence of LPAIV in raw poultry meat and table eggs is very unlikely to negligible, there is in general a high level of uncertainty on the estimation of the subsequent probabilities of key steps of the transmission pathways for poultry and wild birds, mainly due to the limited number of studies available, for instance on the viral load required to infect a bird via raw poultry meat or raw table eggs containing LPAIV.
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Price DJ, Bean NG, Ross JV, Tuke J. Designing group dose-response studies in the presence of transmission. Math Biosci 2018; 304:62-78. [PMID: 30055213 DOI: 10.1016/j.mbs.2018.07.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 05/24/2018] [Accepted: 07/17/2018] [Indexed: 10/28/2022]
Abstract
Dose-response studies are used throughout pharmacology, toxicology and in clinical research to determine safe, effective, or hazardous doses of a substance. When involving animals, the subjects are often housed in groups; this is in fact mandatory in many countries for social animals, on ethical grounds. An issue that may consequently arise is that of unregulated between-subject dosing (transmission), where a subject may transmit the substance to another subject. Transmission will obviously impact the assessment of the dose-response relationship, and will lead to biases if not properly modelled. Here we present a method for determining the optimal design - pertaining to the size of groups, the doses, and the killing times - for such group dose-response experiments, in a Bayesian framework. Our results are of importance to minimising the number of animals required in order to accurately determine dose-response relationships. Furthermore, we additionally consider scenarios in which the estimation of the amount of transmission is also of interest. A particular motivating example is that of Campylobacter jejuni in chickens. Code is provided so that practitioners may determine the optimal design for their own studies.
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Affiliation(s)
- David J Price
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, VIC 3010, Australia; Victorian Infectious Diseases Reference Laboratory Epidemiology Unit, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Royal Melbourne Hospital, VIC 3000, Australia.
| | - Nigel G Bean
- School of Mathematical Sciences, University of Adelaide, SA 5005, Australia; ARC Centre of Excellence for Mathematical & Statistical Frontiers, School of Mathematical Sciences, University of Adelaide, SA 5005, Australia
| | - Joshua V Ross
- School of Mathematical Sciences, University of Adelaide, SA 5005, Australia; ARC Centre of Excellence for Mathematical & Statistical Frontiers, School of Mathematical Sciences, University of Adelaide, SA 5005, Australia
| | - Jonathan Tuke
- School of Mathematical Sciences, University of Adelaide, SA 5005, Australia; ARC Centre of Excellence for Mathematical & Statistical Frontiers, School of Mathematical Sciences, University of Adelaide, SA 5005, Australia
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16
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Overwintering of West Nile virus in a bird community with a communal crow roost. Sci Rep 2018; 8:6088. [PMID: 29666401 PMCID: PMC5904116 DOI: 10.1038/s41598-018-24133-4] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Accepted: 03/22/2018] [Indexed: 02/04/2023] Open
Abstract
In temperate climates, transmission of West Nile virus (WNV) is detectable rarely during the coldest months (late fall through early spring), yet the virus has reappeared consistently during the next warm season. Several mechanisms may contribute to WNV persistence through winter, including bird-to-bird transmission among highly viremic species. Here we consider whether, under realistic scenarios supported by field and laboratory evidence, a winter bird community could sustain WNV through the winter in the absence of mosquitoes. With this purpose we constructed a deterministic model for a community of susceptible birds consisting of communally roosting crows, raptors and other birds. We simulated WNV introduction and subsequent transmission dynamics during the winter under realistic initial conditions and model parameterizations, including plausible contact rates for roosting crows. Model results were used to determine whether the bird community could yield realistic outbreaks that would result in WNV infectious individuals at the end of the winter, which would set up the potential for onward horizontal transmission into summer. Our findings strongly suggest that winter crow roosts could allow for WNV persistence through the winter, and our model results provide synthesis to explain inconclusive results from field studies on WNV overwintering in crow roosts.
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17
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Gonzales JL, Koch G, Elbers ARW, van der Goot JA. Similar transmissibility of the Italian H7N1 highly pathogenic avian influenza virus and its low pathogenic avian influenza virus predecessor. Vet J 2017; 232:20-22. [PMID: 29428086 DOI: 10.1016/j.tvjl.2017.12.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Revised: 12/05/2017] [Accepted: 12/06/2017] [Indexed: 11/29/2022]
Abstract
The transmissibility of the H7N1 highly pathogenic avian influenza virus (HPAIV), which caused a large epidemic in commercial poultry in Italy in 1999-2000, was studied in chickens and compared with that of the low pathogenic precursor virus (LPAIV). Group transmission experiments using the HPAIV were executed to estimate the infectious period (IP), the transmission parameter (β) and the basic reproduction number (R0). These estimates were then compared with those reported for the LPAIV. The estimated β and R0 were similar for both viruses, whilst the IP of the LPAIV was longer than that of the HPAIV. These findings indicate that transmissibility from chicken-to-chicken alone does not appear to confer an advantage for this LPAIV to evolve to a HPAIV.
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Affiliation(s)
- Jose L Gonzales
- Wageningen Bioveterinary Research, Houtribweg 39, 8221 RA Lelystad, The Netherlands.
| | - Guus Koch
- Wageningen Bioveterinary Research, Houtribweg 39, 8221 RA Lelystad, The Netherlands
| | - Armin R W Elbers
- Wageningen Bioveterinary Research, Houtribweg 39, 8221 RA Lelystad, The Netherlands
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18
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More S, Bicout D, Bøtner A, Butterworth A, Calistri P, Depner K, Edwards S, Garin-Bastuji B, Good M, Gortázar Schmidt C, Michel V, Miranda MA, Nielsen SS, Raj M, Sihvonen L, Spoolder H, Thulke HH, Velarde A, Willeberg P, Winckler C, Breed A, Brouwer A, Guillemain M, Harder T, Monne I, Roberts H, Baldinelli F, Barrucci F, Fabris C, Martino L, Mosbach-Schulz O, Verdonck F, Morgado J, Stegeman JA. Avian influenza. EFSA J 2017; 15:e04991. [PMID: 32625288 PMCID: PMC7009867 DOI: 10.2903/j.efsa.2017.4991] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Previous introductions of highly pathogenic avian influenza virus (HPAIV) to the EU were most likely via migratory wild birds. A mathematical model has been developed which indicated that virus amplification and spread may take place when wild bird populations of sufficient size within EU become infected. Low pathogenic avian influenza virus (LPAIV) may reach similar maximum prevalence levels in wild bird populations to HPAIV but the risk of LPAIV infection of a poultry holding was estimated to be lower than that of HPAIV. Only few non-wild bird pathways were identified having a non-negligible risk of AI introduction. The transmission rate between animals within a flock is assessed to be higher for HPAIV than LPAIV. In very few cases, it could be proven that HPAI outbreaks were caused by intrinsic mutation of LPAIV to HPAIV but current knowledge does not allow a prediction as to if, and when this could occur. In gallinaceous poultry, passive surveillance through notification of suspicious clinical signs/mortality was identified as the most effective method for early detection of HPAI outbreaks. For effective surveillance in anseriform poultry, passive surveillance through notification of suspicious clinical signs/mortality needs to be accompanied by serological surveillance and/or a virological surveillance programme of birds found dead (bucket sampling). Serosurveillance is unfit for early warning of LPAI outbreaks at the individual holding level but could be effective in tracing clusters of LPAIV-infected holdings. In wild birds, passive surveillance is an appropriate method for HPAIV surveillance if the HPAIV infections are associated with mortality whereas active wild bird surveillance has a very low efficiency for detecting HPAIV. Experts estimated and emphasised the effect of implementing specific biosecurity measures on reducing the probability of AIV entering into a poultry holding. Human diligence is pivotal to select, implement and maintain specific, effective biosecurity measures.
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Todd Weaver J, Malladi S, Bonney PJ, Patyk KA, Bergeron JG, Middleton JL, Alexander CY, Goldsmith TJ, Halvorson DA. A Simulation-Based Evaluation of Premovement Active Surveillance Protocol Options for the Managed Movement of Turkeys to Slaughter During an Outbreak of Highly Pathogenic Avian Influenza in the United States. Avian Dis 2017; 60:132-45. [PMID: 27309049 DOI: 10.1637/11108-042415-reg] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Risk management decisions associated with live poultry movement during a highly pathogenic avian influenza (HPAI) outbreak should be carefully considered. Live turkey movements may pose a risk for disease spread. On the other hand, interruptions in scheduled movements can disrupt business continuity. The Secure Turkey Supply (STS) Plan was developed through an industry-government-academic collaboration to address business continuity concerns that might arise during a HPAI outbreak. STS stakeholders proposed outbreak response measure options that were evaluated through risk assessment. The developed approach relies on 1) diagnostic testing of two pooled samples of swabs taken from dead turkeys immediately before movement via the influenza A matrix gene real-time reverse transcriptase polymerase chain reaction (rRT-PCR) test; 2) enhanced biosecurity measures in combination with a premovement isolation period (PMIP), restricting movement onto the premises for a few days before movement to slaughter; and 3) incorporation of a distance factor from known infected flocks such that exposure via local area spread is unlikely. Daily exposure likelihood estimates from spatial kernels from past HPAI outbreaks were coupled with simulation models of disease spread and active surveillance to evaluate active surveillance protocol options that differ with respect to the number of swabs per pooled sample and the timing of the tests in relation to movement. Simulation model results indicate that active surveillance testing, in combination with strict biosecurity, substantially increased HPAI virus detection probability. When distance from a known infected flock was considered, the overall combined likelihood of moving an infected, undetected turkey flock to slaughter was predicted to be lower at 3 and 5 km. The analysis of different active surveillance protocol options is designed to incorporate flexibility into HPAI emergency response plans.
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Affiliation(s)
- J Todd Weaver
- A U.S. Department of Agriculture, Animal and Plant Health Inspection Service, Veterinary Services, Science Technology and Analysis Services, Center for Epidemiology and Animal Health, Natural Resource Research Center, Building B, 2150 Centre Avenue, Fort Collins, CO 80526
| | - Sasidhar Malladi
- B University of Minnesota, Center for Animal Health and Food Safety, 136 Andrew Boss Laboratory, 1354 Eckles Avenue, St. Paul, MN 55108
| | - Peter J Bonney
- B University of Minnesota, Center for Animal Health and Food Safety, 136 Andrew Boss Laboratory, 1354 Eckles Avenue, St. Paul, MN 55108
| | - Kelly A Patyk
- A U.S. Department of Agriculture, Animal and Plant Health Inspection Service, Veterinary Services, Science Technology and Analysis Services, Center for Epidemiology and Animal Health, Natural Resource Research Center, Building B, 2150 Centre Avenue, Fort Collins, CO 80526
| | - Justin G Bergeron
- B University of Minnesota, Center for Animal Health and Food Safety, 136 Andrew Boss Laboratory, 1354 Eckles Avenue, St. Paul, MN 55108
| | - Jamie L Middleton
- B University of Minnesota, Center for Animal Health and Food Safety, 136 Andrew Boss Laboratory, 1354 Eckles Avenue, St. Paul, MN 55108
| | - Catherine Y Alexander
- B University of Minnesota, Center for Animal Health and Food Safety, 136 Andrew Boss Laboratory, 1354 Eckles Avenue, St. Paul, MN 55108
| | - Timothy J Goldsmith
- B University of Minnesota, Center for Animal Health and Food Safety, 136 Andrew Boss Laboratory, 1354 Eckles Avenue, St. Paul, MN 55108
| | - David A Halvorson
- C University of Minnesota, College of Veterinary Medicine, 1971 Commonwealth Avenue, St. Paul, MN 55108
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20
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More S, Bøtner A, Butterworth A, Calistri P, Depner K, Edwards S, Garin-Bastuji B, Good M, Gortázar Schmidt C, Michel V, Miranda MA, Nielsen SS, Raj M, Sihvonen L, Spoolder H, Stegeman JA, Thulke HH, Velarde A, Willeberg P, Winckler C, Baldinelli F, Broglia A, Verdonck F, Beltrán Beck B, Kohnle L, Morgado J, Bicout D. Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): low pathogenic avian influenza. EFSA J 2017; 15:e04891. [PMID: 32625556 PMCID: PMC7009921 DOI: 10.2903/j.efsa.2017.4891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Low pathogenic avian influenza (LPAI) has been assessed according to the criteria of the Animal Health Law (AHL), in particular criteria of Article 7 on disease profile and impacts, Article 5 on the eligibility of LPAI to be listed, Article 9 for the categorisation of LPAI according to disease prevention and control rules as in Annex IV and Article 8 on the list of animal species related to LPAI. The assessment has been performed following a methodology composed of information collection and compilation, expert judgement on each criterion at individual and, if no consensus was reached before, also at collective levels. The output is composed of the categorical answer, and for the questions where no consensus was reached, the different supporting views are reported. Details on the methodology used for this assessment are explained in a separate opinion. According to the assessment performed, LPAI can be considered eligible to be listed for Union intervention as laid down in Article 5(3) of the AHL. The disease would comply with the criteria as in Sections 3 and 5 of Annex IV of the AHL, for the application of the disease prevention and control rules referred to in points (c) and (e) of Article 9(1). The animal species to be listed for LPAI according to Article 8(3) criteria are all species of domestic poultry and wild species of mainly Anseriformes and Charadriiformes, as indicated in the present opinion.
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Abstract
Preparing for and responding to outbreaks of serious livestock infectious diseases are critical measures to safeguard animal health, public health, and food supply. Almost all of the current control strategies are empirical, and mass culling or “stamping out” is frequently the principal strategy for controlling epidemics. However, there are ethical, ecological, and economic reasons to consider less drastic control strategies. Here we use modeling to quantitatively study the efficacy of different control measures for viral outbreaks, where the infectiousness, transmissibility and death rate of animals commonly depends on their viral load. We develop a broad theoretical framework for exploring and understanding this heterogeneity. The model includes both direct transmission from infectious animals and indirect transmission from an environmental reservoir. We then incorporate a large variety of control measures, including vaccination, antivirals, isolation, environmental disinfection, and several forms of culling, which may result in fewer culled animals. We provide explicit formulae for the basic reproduction number, R0, for each intervention and for combinations. We evaluate the control methods for a realistic simulated outbreak of low pathogenic avian influenza on a mid-sized turkey farm. In this simulated outbreak, culling results in more total dead birds and dramatically more when culling all of the infected birds.
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22
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Nickbakhsh S, Hall MD, Dorigatti I, Lycett SJ, Mulatti P, Monne I, Fusaro A, Woolhouse ME, Rambaut A, Kao RR. Modelling the impact of co-circulating low pathogenic avian influenza viruses on epidemics of highly pathogenic avian influenza in poultry. Epidemics 2016; 17:27-34. [DOI: 10.1016/j.epidem.2016.10.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Revised: 09/26/2016] [Accepted: 10/17/2016] [Indexed: 10/20/2022] Open
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23
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Iverson SA, Gilchrist HG, Soos C, Buttler II, Harms NJ, Forbes MR. Injecting epidemiology into population viability analysis: avian cholera transmission dynamics at an arctic seabird colony. J Anim Ecol 2016; 85:1481-1490. [PMID: 27548394 DOI: 10.1111/1365-2656.12585] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2015] [Accepted: 08/17/2016] [Indexed: 10/21/2022]
Abstract
Infectious diseases have the potential to spread rapidly and cause high mortality within populations of immunologically naïve hosts. The recent appearance of avian cholera, a highly virulent disease of birds caused by the bacterium Pasteurella multocida, at remote Arctic seabird colonies is an emerging conservation concern. Determining disease risk to population viability requires a quantitative understanding of transmission potential and the factors that regulate epidemic persistence. Estimates of the basic (R0 ) and real-time (Rt ) reproductive number are critical in this regard - enumerating the number of secondary infections caused by each primary infection in a newly invaded host population and the decline in transmission rate as susceptible individuals are removed via mortality or immunized recovery. Here, we use data collected at a closely monitored common eider (Somateria mollissima) breeding colony located in the Canadian Arctic to examine transmission and host population dynamics. Specifically, we infer epidemic curves from daily mortality observations and use a likelihood-based procedure to estimate changes in the reproductive number over a series of annual outbreaks. These data are interpreted in relation to concurrent changes in host numbers to assess local extinction risk. Consistent with expectations for a novel pathogen invasion, case incidence increased exponentially during the initial wave of exposure (R0 = 2·5; generation time = 6·5 days ± 1·1 SD). Disease conditions gradually abated, but only after several years of smouldering infection (Rt ≈ 1). In total, 6194 eider deaths were recorded during outbreaks spanning eight consecutive breeding seasons. Breeding pair abundance declined by 56% from the pre-outbreak peak; however, a robust population of >4000 pairs remained intact upon epidemic fade-out. Overall, outbreak patterns were consistent with herd immunity acting as a mitigating factor governing in the extent and duration of mortality. Disease mortality is frequently modelled as a form of stochastic catastrophe in wildlife population assessments, whereas our approach gives shape to the functional response between transmission and host population dynamics. We conclude that increased emphasis on integrating epidemiological and population processes is essential to predicting the conservation impact of emerging infectious diseases in wildlife.
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Affiliation(s)
- Samuel A Iverson
- Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, ON, Canada, K1S 5B6.
| | - H Grant Gilchrist
- National Wildlife Research Centre, Environment and Climate Change Canada, 1125 Colonel By Drive, Ottawa, ON, Canada, K1A 0H3
| | - Catherine Soos
- Science and Technology Branch, Environment and Climate Change Canada, 115 Perimeter Road, Saskatoon, SK, Canada, S7N 0X4.,Department of Veterinary Pathology, University of Saskatchewan, 52 Campus Drive, Saskatoon, SK, Canada, S7N 5B4
| | - Isabel I Buttler
- Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, ON, Canada, K1S 5B6
| | - N Jane Harms
- Department of Veterinary Pathology, University of Saskatchewan, 52 Campus Drive, Saskatoon, SK, Canada, S7N 5B4
| | - Mark R Forbes
- Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, ON, Canada, K1S 5B6
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24
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Henning J, Pfeiffer DU, Stevenson M, Yulianto D, Priyono W, Meers J. Who Is Spreading Avian Influenza in the Moving Duck Flock Farming Network of Indonesia? PLoS One 2016; 11:e0152123. [PMID: 27019344 PMCID: PMC4809517 DOI: 10.1371/journal.pone.0152123] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2015] [Accepted: 03/09/2016] [Indexed: 11/30/2022] Open
Abstract
Duck populations are considered to be a reservoir of Highly pathogenic avian influenza (HPAI) virus H5N1 in some agricultural production systems, as they are able to shed the virus for several days without clinical signs. Countries endemically affected with HPAI in Asia are characterised by production systems where ducks are fed on post-harvest spilled rice. During this scavenging process it is common for ducks to come into contact with other duck flocks or wild birds, thereby providing opportunities for virus spread. Effective risk management for HPAI has been significantly compromised by a limited understanding of management of moving duck flocks in these countries, despite of a small number of recent investigations. Here, for the first time, we described the management of moving duck flocks and the structure of the moving duck flock network in quantitative terms so that factors influencing the risk of HPAIV transmission can be identified. By following moving duck flock farmers over a period of 6 months in Java, Indonesia, we were able to describe the movement of flocks and to characterise the network of various types of actors associated with the production system. We used these data to estimate the basic reproductive number for HPAI virus spread. Our results suggest that focussing HPAI prevention measures on duck flocks alone will not be sufficient. Instead, the role of transporters of moving duck flocks, hatcheries and rice paddy owners, in the spread of the HPAI virus needs to be recognised.
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Affiliation(s)
- Joerg Henning
- School of Veterinary Science, University of Queensland, Gatton, Queensland, Australia
- * E-mail:
| | - Dirk U. Pfeiffer
- Royal Veterinary College, University of London, London, United Kingdom
| | - Mark Stevenson
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville Victoria, Australia
| | | | | | - Joanne Meers
- School of Veterinary Science, University of Queensland, Gatton, Queensland, Australia
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25
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Malladi S, Weaver JT, Alexander CY, Middleton JL, Goldsmith TJ, Snider T, Tilley BJ, Gonder E, Hermes DR, Halvorson DA. Quantitative Estimation of the Number of Contaminated Hatching Eggs Released from an Infected, Undetected Turkey Breeder Hen Flock During a Highly Pathogenic Avian Influenza Outbreak. Avian Dis 2015; 59:355-67. [PMID: 26478153 DOI: 10.1637/11001-120814-reg.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
The regulatory response to an outbreak of highly pathogenic avian influenza (HPAI) in the United States may involve quarantine and stop movement orders that have the potential to disrupt continuity of operations in the U.S. turkey industry--particularly in the event that an uninfected breeder flock is located within an HPAI Control Area. A group of government-academic-industry leaders developed an approach to minimize the unintended consequences associated with outbreak response, which incorporates HPAI control measures to be implemented prior to moving hatching eggs off of the farm. Quantitative simulation models were used to evaluate the movement of potentially contaminated hatching eggs from a breeder henhouse located in an HPAI Control Area, given that active surveillance testing, elevated biosecurity, and a 2-day on-farm holding period were employed. The risk analysis included scenarios of HPAI viruses differing in characteristics as well as scenarios in which infection resulted from artificial insemination. The mean model-predicted number of internally contaminated hatching eggs released per movement from an HPAI-infected turkey breeder henhouse ranged from 0 to 0.008 under the four scenarios evaluated. The results indicate a 95% chance of no internally contaminated eggs being present per movement from an infected house before detection. Sensitivity analysis indicates that these results are robust to variation in key transmission model parameters within the range of their estimates from available literature. Infectious birds at the time of egg collection are a potential pathway of external contamination for eggs stored and then moved off of the farm; the predicted number of such infectious birds was estimated to be low. To date, there has been no evidence of vertical transmission of HPAI virus or low pathogenic avian influenza virus to day-old poults from hatching eggs originating from infected breeders. The application of risk analysis methods was beneficial for evaluating outbreak measures developed through emergency response planning initiatives that consider the managed movement of hatching eggs from monitored premises in an HPAI Control Area.
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26
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Poletto C, Meloni S, Van Metre A, Colizza V, Moreno Y, Vespignani A. Characterising two-pathogen competition in spatially structured environments. Sci Rep 2015; 5:7895. [PMID: 25600088 PMCID: PMC4298724 DOI: 10.1038/srep07895] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2014] [Accepted: 12/16/2014] [Indexed: 11/10/2022] Open
Abstract
Different pathogens spreading in the same host population often generate complex co-circulation dynamics because of the many possible interactions between the pathogens and the host immune system, the host life cycle, and the space structure of the population. Here we focus on the competition between two acute infections and we address the role of host mobility and cross-immunity in shaping possible dominance/co-dominance regimes. Host mobility is modelled as a network of traveling flows connecting nodes of a metapopulation, and the two-pathogen dynamics is simulated with a stochastic mechanistic approach. Results depict a complex scenario where, according to the relation among the epidemiological parameters of the two pathogens, mobility can either be non-influential for the competition dynamics or play a critical role in selecting the dominant pathogen. The characterisation of the parameter space can be explained in terms of the trade-off between pathogen's spreading velocity and its ability to diffuse in a sparse environment. Variations in the cross-immunity level induce a transition between presence and absence of competition. The present study disentangles the role of the relevant biological and ecological factors in the competition dynamics, and provides relevant insights into the spatial ecology of infectious diseases.
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Affiliation(s)
- Chiara Poletto
- 1] Sorbonne Universités, UPMC Univ Paris 06, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, F-75013, Paris, France [2] INSERM, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, F-75013, Paris, France
| | - Sandro Meloni
- 1] Institute for Biocomputation and Physics of Complex Systems, University of Zaragoza, Zaragoza, Spain [2] Department of Theoretical Physics, University of Zaragoza, Zaragoza, Spain
| | - Ashleigh Van Metre
- 1] Sorbonne Universités, UPMC Univ Paris 06, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, F-75013, Paris, France [2] INSERM, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, F-75013, Paris, France [3] Wofford College, South Carolina, USA
| | - Vittoria Colizza
- 1] Sorbonne Universités, UPMC Univ Paris 06, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, F-75013, Paris, France [2] INSERM, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, F-75013, Paris, France [3] ISI Foundation, Torino, Italy
| | - Yamir Moreno
- 1] Institute for Biocomputation and Physics of Complex Systems, University of Zaragoza, Zaragoza, Spain [2] Department of Theoretical Physics, University of Zaragoza, Zaragoza, Spain [3] ISI Foundation, Torino, Italy
| | - Alessandro Vespignani
- 1] ISI Foundation, Torino, Italy [2] Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston MA, USA
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Extended transmission of two H5/H7 low pathogenic avian influenza viruses in chickens. Epidemiol Infect 2014; 143:781-90. [PMID: 24924291 DOI: 10.1017/s0950268814001307] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Transmission experiments are useful for investigating the mechanisms of low pathogenic notifiable avian influenza virus (LPNAI) transmission. In this study, the hypothesis that inoculation-infected chickens are more infectious than contact-infected chickens was tested. To this end, extended transmission experiments with one H5N2 and one H7N1 LPAIV which had previously been characterized in a series of standard transmission experiments were conducted in specific pathogen-free (SPF) chickens. For the H5N2 LPAIV, the infectivity of contact-infected chickens was similar to the infectivity of inoculated chickens. Despite results from a previous study suggesting the H7N1 LPAIV strain to be similarly infectious to SPF chickens as the H5N2 LPAIV strain, the acquisition of contact-infected chickens proved more difficult for H7N1 LPAIV. It was assumed that this might have been a consequence of the length and timing of the exposure period. In conclusion, for LPNAIVs that first seemed equally infectious, short-term transmissibility may vary considerably.
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Williams PD, Dobson AP, Dhondt KV, Hawley DM, Dhondt AA. Evidence of trade-offs shaping virulence evolution in an emerging wildlife pathogen. J Evol Biol 2014; 27:1271-8. [PMID: 24750277 DOI: 10.1111/jeb.12379] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2013] [Revised: 02/25/2014] [Accepted: 03/24/2014] [Indexed: 01/24/2023]
Abstract
In the mid-1990s, the common poultry pathogen Mycoplasma gallisepticum (MG) made a successful species jump to the eastern North American house finch Haemorhous mexicanus (HM). Subsequent strain diversification allows us to directly quantify, in an experimental setting, the transmission dynamics of three sequentially emergent geographic isolates of MG, which differ in the levels of pathogen load they induce. We find significant among-strain variation in rates of transmission as well as recovery. Pathogen strains also differ in their induction of host morbidity, measured as the severity of eye lesions due to infection. Relationships between pathogen traits are also investigated, with transmission and recovery rates being significantly negatively correlated, whereas transmission and virulence, measured as average eye lesion score over the course of infection, are positively correlated. By quantifying these disease-relevant parameters and their relationships, we provide the first analysis of the trade-offs that shape the evolution of this important emerging pathogen.
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Affiliation(s)
- P D Williams
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
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Quantitative transmission characteristics of different H5 low pathogenic avian influenza viruses in Muscovy ducks. Vet Microbiol 2014; 168:78-87. [PMID: 24287046 DOI: 10.1016/j.vetmic.2013.10.020] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2013] [Revised: 10/21/2013] [Accepted: 10/24/2013] [Indexed: 11/23/2022]
Abstract
EU annual serosurveillance programs show that domestic duck flocks have the highest seroprevalence of H5 antibodies, demonstrating the circulation of notifiable avian influenza virus (AIV) according to OIE, likely low pathogenic (LP). Therefore, transmission characteristics of LPAIV within these flocks can help to understand virus circulation and possible risk of propagation. This study aimed at estimating transmission parameters of four H5 LPAIV (three field strains from French poultry and decoy ducks, and one clonal reverse-genetics strain derived from one of the former), using a SIR model to analyze data from experimental infections in SPF Muscovy ducks. The design was set up to accommodate rearing on wood shavings with a low density of 1.6 ducks/m(2): 10 inoculated ducks were housed together with 15 contact-exposed ducks. Infection was monitored by RNA detection on oropharyngeal and cloacal swabs using real-time RT-PCR with a cutoff corresponding to 2-7 EID50. Depending on the strain, the basic reproduction number (R0) varied from 5.5 to 42.7, confirming LPAIV could easily be transmitted to susceptible Muscovy ducks. The lowest R0 estimate was obtained for a H5N3 field strain, due to lower values of transmission rate and duration of infectious period, whereas reverse-genetics derived H5N1 strain had the highest R0. Frequency and intensity of clinical signs were also variable between strains, but apparently not associated with longer infectious periods. Further comparisons of quantitative transmission parameters may help to identify relevant viral genetic markers for early detection of potentially more virulent strains during surveillance of LPAIV.
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Pepin KM, Spackman E, Brown JD, Pabilonia KL, Garber LP, Weaver JT, Kennedy DA, Patyk KA, Huyvaert KP, Miller RS, Franklin AB, Pedersen K, Bogich TL, Rohani P, Shriner SA, Webb CT, Riley S. Using quantitative disease dynamics as a tool for guiding response to avian influenza in poultry in the United States of America. Prev Vet Med 2013; 113:376-97. [PMID: 24462191 PMCID: PMC3945821 DOI: 10.1016/j.prevetmed.2013.11.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2013] [Revised: 11/22/2013] [Accepted: 11/24/2013] [Indexed: 02/02/2023]
Abstract
Wild birds are the primary source of genetic diversity for influenza A viruses that eventually emerge in poultry and humans. Much progress has been made in the descriptive ecology of avian influenza viruses (AIVs), but contributions are less evident from quantitative studies (e.g., those including disease dynamic models). Transmission between host species, individuals and flocks has not been measured with sufficient accuracy to allow robust quantitative evaluation of alternate control protocols. We focused on the United States of America (USA) as a case study for determining the state of our quantitative knowledge of potential AIV emergence processes from wild hosts to poultry. We identified priorities for quantitative research that would build on existing tools for responding to AIV in poultry and concluded that the following knowledge gaps can be addressed with current empirical data: (1) quantification of the spatio-temporal relationships between AIV prevalence in wild hosts and poultry populations, (2) understanding how the structure of different poultry sectors impacts within-flock transmission, (3) determining mechanisms and rates of between-farm spread, and (4) validating current policy-decision tools with data. The modeling studies we recommend will improve our mechanistic understanding of potential AIV transmission patterns in USA poultry, leading to improved measures of accuracy and reduced uncertainty when evaluating alternative control strategies.
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Affiliation(s)
- K M Pepin
- Department of Biology, Colorado State University, Fort Collins, CO, USA; Fogarty International Center, National Institute of Health, Bethesda, MD, USA.
| | - E Spackman
- Southeast Poultry Research Laboratory, Agricultural Research Service, United States Department of Agriculture, Athens, GA, USA.
| | - J D Brown
- Department of Population Health, College of Veterinary Medicine, University of Georgia, Athens, GA, USA.
| | - K L Pabilonia
- Department of Microbiology, Immunology and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA.
| | - L P Garber
- Centers for Epidemiology and Animal Health, Veterinary Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, Fort Collins, CO, USA.
| | - J T Weaver
- Centers for Epidemiology and Animal Health, Veterinary Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, Fort Collins, CO, USA.
| | - D A Kennedy
- Fogarty International Center, National Institute of Health, Bethesda, MD, USA; Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, State College, PA, USA.
| | - K A Patyk
- Centers for Epidemiology and Animal Health, Veterinary Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, Fort Collins, CO, USA.
| | - K P Huyvaert
- Warner College of Natural Resources, Colorado State University, Fort Collins, CO, USA.
| | - R S Miller
- Centers for Epidemiology and Animal Health, Veterinary Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, Fort Collins, CO, USA.
| | - A B Franklin
- National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, Fort Collins, CO, USA.
| | - K Pedersen
- National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, Fort Collins, CO, USA.
| | - T L Bogich
- Fogarty International Center, National Institute of Health, Bethesda, MD, USA; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
| | - P Rohani
- Fogarty International Center, National Institute of Health, Bethesda, MD, USA; Department of Ecology and Evolutionary Biology, Center for the Study of Complex Systems, University of Michigan, Ann Arbor, MI, USA.
| | - S A Shriner
- National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, Fort Collins, CO, USA.
| | - C T Webb
- Department of Biology, Colorado State University, Fort Collins, CO, USA; Fogarty International Center, National Institute of Health, Bethesda, MD, USA.
| | - S Riley
- Fogarty International Center, National Institute of Health, Bethesda, MD, USA; MRC Centre for Outbreak Analysis and Disease Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London, UK.
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