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Harder T, de Wit S, Gonzales JL, Ho JHP, Mulatti P, Prajitno TY, Stegeman A. Epidemiology-driven approaches to surveillance in HPAI-vaccinated poultry flocks aiming to demonstrate freedom from circulating HPAIV. Biologicals 2023; 83:101694. [PMID: 37494751 DOI: 10.1016/j.biologicals.2023.101694] [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: 04/13/2023] [Revised: 06/19/2023] [Accepted: 07/14/2023] [Indexed: 07/28/2023] Open
Abstract
Incursion pressure of high pathogenicity avian influenza viruses (HPAIV) by secondary spread among poultry holdings and/or from infected migratory wild bird populations increases worldwide. Vaccination as an additional layer of protection of poultry holdings using appropriately matched vaccines aims at reducing clinical sequelae of HPAIV infection, disrupting HPAIV transmission, curtailing economic losses and animal welfare problems and cutting exposure risks of zoonotic HPAIV at the avian-human interface. Products derived from HPAIV-vaccinated poultry should not impose any risk of virus spread or exposure. Vaccination can be carried out with zero-tolerance for infection in vaccinated herds and must then be flanked by appropriate surveillance which requires tailoring at several levels: (i) Controlling appropriate vaccination coverage and adequate population immunity in individual flocks and across vaccinated populations; (ii) assessing HPAI-infection trends in unvaccinated and vaccinated parts of the poultry population to provide early detection of new/re-emerged HPAIV outbreaks; and (iii) proving absence of HPAIV circulation in vaccinated flocks ideally by real time-monitoring. Surveillance strategies, i.e. selecting targets, tools and random sample sizes, must be accommodated to the specific epidemiologic and socio-economic background. Methodological approaches and practical examples from three countries or territories applying AI vaccination under different circumstances are reviewed here.
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Affiliation(s)
- Timm Harder
- Institute of Diagnostic Virology, Friedrich-Loeffler Institute, Greifswald-Insel Riems, Germany.
| | - Sjaak de Wit
- Royal GD, Deventer, the Netherlands; Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands
| | - Jose L Gonzales
- Epidemiology, Bio-informatics & Animal Models, Wageningen Bioveterinary Research, Lelystad, the Netherlands
| | - Jeremy H P Ho
- Agriculture, Fisheries and Conservation Department, Government of the Hong Kong Special Administrative Region, Hong Kong, China
| | - Paolo Mulatti
- Istituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy
| | - Teguh Y Prajitno
- Japfa Comfeed Indonesia, Vaksindo Satwa Nusantara, Animal Health & Laboratory Services, Jakarta, Indonesia
| | - Arjan Stegeman
- Department Population Health Sciences, Farm Animal Health, Veterinary Epidemiology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands
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2
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Research Progress in the Early Warning of Chicken Diseases by Monitoring Clinical Symptoms. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12115601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Global animal protein consumption has been steadily increasing as a result of population growth and the increasing demand for nutritious diets. The poultry industry provides a large portion of meat and eggs for human consumption. The early detection and warning of poultry infectious diseases play a critical role in the poultry breeding and production systems, improving animal welfare and reducing losses. However, inadequate methods for the early detection and prevention of infectious diseases in poultry farms sometimes fail to prevent decreased productivity and even widespread mortality. The health status of poultry is often reflected by its individual physiological, physical and behavioral clinical symptoms, such as higher body temperature resulting from fever, abnormal vocalization caused by respiratory disease and abnormal behaviors due to pathogenic infection. Therefore, the use of technologies for symptom detection can monitor the health status of broilers and laying hens in a continuous, noninvasive and automated way, and potentially assist in the early warning decision-making process. This review summarized recent literature on poultry disease detection and highlighted clinical symptom-monitoring technologies for sick poultry. The review concluded that current technologies are already showing their superiority to manual inspection, but the clinical symptom-based monitoring systems have not been fully utilized for on-farm early detection.
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Nezworski J, St Charles KM, Malladi S, Ssematimba A, Bonney PJ, Cardona CJ, Halvorson DA, Culhane MR. A Retrospective Study of Early vs. Late Virus Detection and Depopulation on Egg Laying Chicken Farms Infected with Highly Pathogenic Avian Influenza Virus During the 2015 H5N2 Outbreak in the United States. Avian Dis 2021; 65:474-482. [PMID: 34699146 DOI: 10.1637/aviandiseases-d-21-00019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 07/08/2021] [Indexed: 11/05/2022]
Abstract
The 2015 highly pathogenic avian influenza (HPAI) H5N2 outbreak affected more than 200 Midwestern U.S. poultry premises. Although each affected poultry operation incurred substantial losses, some operations of the same production type and of similar scale had differences between one another in their ability to recognize evidence of the disease before formal diagnoses and in their ability to make proactive, farm-level disease containment decisions. In this case comparison study, we examine the effect of HPAI infection on two large egg production facilities and the epidemiologic and financial implications resulting from differences in detection and decision-making processes. Each egg laying facility had more than 1 million caged birds distributed among 18 barns on one premises (Farm A) and 17 barns on the other premises (Farm B). We examine how farm workers' awareness of disease signs, as well as how management's immediate or delayed decisions to engage in depopulation procedures, affected flock mortality, levels of environmental contamination, time intervals for re population, and farm profits on each farm. By predictive mathematical modeling, we estimated the time of virus introduction to examine how quickly infection was identified on the farms and then estimated associated contact rates within barns. We found that the farm that implemented depopulation immediately after detection of abnormal mortality (Farm A) was able to begin repopulation of barns 37 days sooner than the farm that began depopulation well after the detection of abnormally elevated mortality (Farm B). From average industry economic data, we determined that the loss associated with delayed detection using lost profit per day in relation to down time was an additional $3.3 million for Farm B when compared with Farm A.
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Affiliation(s)
| | - Kaitlyn M St Charles
- Secure Food Systems Team, Department of Veterinary and Biomedical Sciences, University of Minnesota, St. Paul, MN 55108,
| | - Sasidhar Malladi
- Secure Food Systems Team, Department of Veterinary and Biomedical Sciences, University of Minnesota, St. Paul, MN 55108
| | - Amos Ssematimba
- Secure Food Systems Team, Department of Veterinary and Biomedical Sciences, University of Minnesota, St. Paul, MN 55108.,Department of Mathematics, Faculty of Science, Gulu University, Gulu, Uganda
| | - Peter J Bonney
- Secure Food Systems Team, Department of Veterinary and Biomedical Sciences, University of Minnesota, St. Paul, MN 55108
| | - Carol J Cardona
- Secure Food Systems Team, Department of Veterinary and Biomedical Sciences, University of Minnesota, St. Paul, MN 55108
| | - David A Halvorson
- Secure Food Systems Team, Department of Veterinary and Biomedical Sciences, University of Minnesota, St. Paul, MN 55108
| | - Marie R Culhane
- Secure Food Systems Team, Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55108
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4
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Schreuder J, Manders TTM, Elbers ARW, van der Spek AN, Bouwstra RJ, Stegeman JA, Velkers FC. Highly pathogenic avian influenza subtype H5Nx clade 2.3.4.4 outbreaks in Dutch poultry farms, 2014-2018: Clinical signs and mortality. Transbound Emerg Dis 2021; 68:88-97. [PMID: 32418364 PMCID: PMC8048556 DOI: 10.1111/tbed.13597] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Revised: 03/03/2020] [Accepted: 04/17/2020] [Indexed: 12/18/2022]
Abstract
In recent years, different subtypes of highly pathogenic avian influenza (HPAI) viruses caused outbreaks in several poultry types worldwide. Early detection of HPAI virus infection is crucial to reduce virus spread. Previously, the use of a mortality ratio threshold to expedite notification of suspicion in layer farms was proposed. The purpose of this study was to describe the clinical signs reported in the early stages of HPAI H5N8 and H5N6 outbreaks on chicken and Pekin duck farms between 2014 and 2018 in the Netherlands and compare them with the onset of an increased mortality ratio (MR). Data on daily mortality and clinical signs from nine egg-producing chicken farms and seven Pekin duck farms infected with HPAI H5N8 (2014 and 2016) and H5N6 (2017-2018) in the Netherlands were analysed. In 12 out of 15 outbreaks for which a MR was available, MR increase preceded or coincided with the first observation of clinical signs by the farmer. In one chicken and two Pekin duck outbreaks, clinical signs were observed prior to MR increase. On all farms, veterinarians observed clinical signs of general disease. Nervous or locomotor signs were reported in all Pekin duck outbreaks, but only in two chicken outbreaks. Other clinical signs were observed less frequently in both chickens and Pekin ducks. Compared to veterinarians, farmers observed and reported clinical signs, especially respiratory and gastrointestinal signs, less frequently. This case series suggests that a MR with a set threshold could be an objective parameter to detect HPAI infection on chicken and Pekin duck farms at an early stage. Observation of clinical signs may provide additional indication for farmers and veterinarians for notifying a clinical suspicion of HPAI infection. Further assessment and validation of a MR threshold in Pekin ducks are important as it could serve as an important tool in HPAI surveillance programs.
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Affiliation(s)
- Janneke Schreuder
- Department of Farm Animal HealthFaculty of Veterinary MedicineUtrecht UniversityUtrechtthe Netherlands
| | - Thijs T. M. Manders
- Department of Farm Animal HealthFaculty of Veterinary MedicineUtrecht UniversityUtrechtthe Netherlands
| | - Armin R. W. Elbers
- Department of Bacteriology and EpidemiologyWageningen Bioveterinary ResearchLelystadthe Netherlands
| | - Arco N. van der Spek
- Netherlands Food and Consumer Product Safety Authority (NVWA)Utrechtthe Netherlands
| | | | - J. Arjan Stegeman
- Department of Farm Animal HealthFaculty of Veterinary MedicineUtrecht UniversityUtrechtthe Netherlands
| | - Francisca C. Velkers
- Department of Farm Animal HealthFaculty of Veterinary MedicineUtrecht UniversityUtrechtthe Netherlands
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5
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Ssematimba A, Bonney PJ, Malladi S, Charles KMS, Culhane M, Goldsmith TJ, Halvorson DA, Cardona CJ. Mortality-Based Triggers and Premovement Testing Protocols for Detection of Highly Pathogenic Avian Influenza Virus Infection in Commercial Upland Game Birds. Avian Dis 2020; 63:157-164. [PMID: 31131573 DOI: 10.1637/11870-042518-reg.1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 10/21/2018] [Indexed: 11/05/2022]
Abstract
Outbreaks involving avian influenza viruses are often devastating to the poultry industry economically and otherwise. Disease surveillance is critically important because it facilitates timely detection and generates confidence that infected birds are not moved during business continuity intended to mitigate associated economic losses. The possibility of using an abnormal increase in daily mortality to levels that exceed predetermined thresholds as a trigger to initiate further diagnostic investigations for highly pathogenic avian influenza (HPAI) virus infection in the flock is explored. The range of optimal mortality thresholds varies by bird species, trigger type, and mortality thresholds, and these should be considered when assessing sector-specific triggers. The study uses purposefully collected data and data from the literature to determine optimal mortality triggers for HPAI detection in commercial upland game bird flocks. Three trigger types were assessed for the ability to detect rapidly both HPAI (on the basis of disease-induced and normal mortality data) and false alarm rate (on the basis of normal mortality data); namely, 1) exceeding a set absolute threshold on one day, 2) exceeding a set absolute threshold on two consecutive days, or 3) exceeding a multiple of a seven-day moving average. The likelihood of disease detection using some of these triggers together with premovement real-time reverse transcription PCR (rRT-PCR) testing was examined. Results indicate that the performance of the two consecutive days trigger had the best metrics (i.e., rapid detection with few false alarms) in the trade-off analysis. The collected normal mortality data was zero on 66% of all days recorded, with an overall mean of 0.6 dead birds per day. In the surveillance scenario analyses, combining the default protocol that relied only on active surveillance (i.e., premovement testing of oropharyngeal swab samples from dead birds by rRT-PCR) together with either of the mortality-based triggers improved detection rates on all days postexposure before scheduled movement. For exposures occurring within 8 days of movement, the protocol that combined the default with single-day triggers had slightly more detections than that with two consecutive days triggers. However, all assessed protocol combinations were able to detect all infections that occurred more than 10 days before scheduled movement. These findings can inform risk-based decisions pertaining to continuity of business in the commercial upland game bird industry.
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Affiliation(s)
- Amos Ssematimba
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108, .,Department of Mathematics, Faculty of Science, Gulu University, P.O. Box 166, Gulu, Uganda
| | - Peter J Bonney
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108
| | - Sasidhar Malladi
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108
| | - Kaitlyn M St Charles
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108
| | - Marie Culhane
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108
| | - Timothy J Goldsmith
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108
| | - David A Halvorson
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108
| | - Carol J Cardona
- Secure Food Systems Team, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108,
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6
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Lopez KM, Nezworski J, Rendahl A, Culhane M, Flores-Figueroa C, Muñoz-Aguayo J, Halvorson DA, Johnson R, Goldsmith T, Cardona CJ. Environmental Sampling Survey of H5N2 Highly Pathogenic Avian Influenza-Infected Layer Chicken Farms in Minnesota and Iowa. Avian Dis 2019; 62:373-380. [PMID: 31119921 DOI: 10.1637/11891-050418-reg.1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Accepted: 09/19/2018] [Indexed: 11/05/2022]
Abstract
Respiratory secretions, feces, feathers, and eggs of avian influenza-infected hens provide ample sources of virus which heavily contaminate barn and farm environments during a disease outbreak. Environmental sampling surveys were conducted in the Midwestern United States on affected farms during the 2015 H5N2 highly pathogenic avian influenza (HPAI) outbreak to assess the degree of viral contamination. A total of 930 samples were obtained from various sites inside and outside layer barns housing infected birds and tested with real-time reverse transcriptase PCR. The distribution and load of viral RNA in barns in which most birds were dead at the onset of depopulation efforts (high-mortality barns) were compared with those of barns in which birds were euthanatized before excess mortality occurred (normal-mortality barns). A statistically significant difference was seen between cycle threshold (Ct) values for samples taken of fans, feed troughs, barn floors, barn walls, cages, manure-associated locations, barn doors, egg belts, and the exterior of high-mortality vs. normal-mortality barns. In high-mortality barns, sample sites were found to be the most to least contaminated in the following order: cages, manure-associated locations, barn floors, egg belts, feed troughs, barn doors, barn walls, fans, exterior, and egg processing. Significant changes in Ct values over time following HPAI detection in a barn and depopulation of birds on an infected farm were observed for the manure-associated, barn floor, barn wall, and fan sampling sites. These results show that high mortality in a flock as a result of HPAI will increase contamination of the farm environment. The results also suggest optimal sampling locations for detection of virus; however, the persistence of RNA on highmortality farms may delay the determination that adequate sanitization has been performed for restocking to take place.
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Affiliation(s)
- Karen M Lopez
- College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108
| | - Jill Nezworski
- Blue House Veterinary, 145 West Yellowstone Trail, Buffalo, MN 55314
| | - Aaron Rendahl
- College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108
| | - Marie Culhane
- College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108
| | - Cristian Flores-Figueroa
- Mid-Central Research and Outreach Center, University of Minnesota, 1802 18th St. Northeast, Willmar, MN 56201
| | - Jeanette Muñoz-Aguayo
- Mid-Central Research and Outreach Center, University of Minnesota, 1802 18th St. Northeast, Willmar, MN 56201
| | - David A Halvorson
- College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108
| | - Rebecca Johnson
- College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108
| | - Timothy Goldsmith
- College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108
| | - Carol J Cardona
- College of Veterinary Medicine, University of Minnesota, Saint Paul, MN 55108,
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7
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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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8
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Gonzales JL, Elbers ARW. Effective thresholds for reporting suspicions and improve early detection of avian influenza outbreaks in layer chickens. Sci Rep 2018; 8:8533. [PMID: 29867092 PMCID: PMC5986775 DOI: 10.1038/s41598-018-26954-9] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Accepted: 05/18/2018] [Indexed: 11/09/2022] Open
Abstract
The objective of this study was to identify effective reporting thresholds for suspicions of both highly pathogenic (HPAI) and low pathogenic avian influenza (LPAI) outbreaks in layer farms. Daily mortality and egg-production data from 30 Dutch farms with no record of AI infection were analysed and thresholds set. Mortality rates above or egg-production below these thresholds for two consecutive days would trigger an alarm sign. The following thresholds were identified for mortality: (i) A mortality threshold of 0.08% or 0.13% for layers kept indoors or with free-range access respectively, (ii) a 2.9 times higher mortality than the average weekly mortality of the previous week, and iii) a moving-average threshold that could be implemented for each specific farm. For egg-production: (i) a weekly ratio lower than 0.94 in egg-production drop, and (ii) a moving-average threshold. The accuracy of these thresholds was assessed by quantifying their sensitivity, specificity and time to trigger disease detection using data from 15 infected and 31 non-infected farms. New thresholds were more sensitive and signalled infection two to six days earlier than the presently used thresholds. A high Specificity (97–100%) was obtained by combining mortality and egg production thresholds in a serial approach to trigger an alarm.
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Affiliation(s)
- Jose L Gonzales
- Department of Bacteriology and Epidemiology, Wageningen Bioveterinary Research, P.O. Box 65, 8200 AB, Lelystad, The Netherlands.
| | - Armin R W Elbers
- Department of Bacteriology and Epidemiology, Wageningen Bioveterinary Research, P.O. Box 65, 8200 AB, Lelystad, The Netherlands
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9
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Weaver JT, Malladi S, Spackman E, Swayne DE. Risk Reduction Modeling of High Pathogenicity Avian Influenza Virus Titers in Nonpasteurized Liquid Egg Obtained from Infected but Undetected Chicken Flocks. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2015; 35:2057-2068. [PMID: 25867713 DOI: 10.1111/risa.12374] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Control of highly pathogenic avian influenza (HPAI) outbreaks in poultry has traditionally involved the establishment of disease containment zones, where poultry products are only permitted to move from within a zone under permit. Nonpasteurized liquid egg (NPLE) is one such commodity for which movements may be permitted, considering inactivation of HPAI virus via pasteurization. Active surveillance testing at the flock level, using targeted matrix gene real-time reversed transcriptase-polymerase chain reaction testing (RRT-PCR) has been incorporated into HPAI emergency response plans as the primary on-farm diagnostic test procedure to detect HPAI in poultry and is considered to be a key risk mitigation measure. To inform decisions regarding the potential movement of NPLE to a pasteurization facility, average HPAI virus concentrations in NPLE produced from a HPAI virus infected, but undetected, commercial table-egg-layer flock were estimated for three HPAI virus strains using quantitative simulation models. Pasteurization under newly proposed international design standards (5 log10 reduction) is predicted to inactivate HPAI virus in NPLE to a very low concentration of less than 1 embryo infectious dose (EID)50 /mL, considering the predicted virus titers in NPLE from a table-egg flock under active surveillance. Dilution of HPAI virus from contaminated eggs in eggs from the same flock, and in a 40,000 lb tanker-truck load of NPLE containing eggs from disease-free flocks was also considered. Risk assessment can be useful in the evaluation of commodity-specific risk mitigation measures to facilitate safe trade in animal products from countries experiencing outbreaks of highly transmissible animal diseases.
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Affiliation(s)
- J Todd Weaver
- 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 Resources Research Center, Bldg. B MS-2W4, 2150 Centre, Avenue, Fort Collins, CO 80526, USA
| | - Sasidhar Malladi
- Center for Animal Health and Food Safety, University of Minnesota, 136 Andrew Boss Laboratory, 1354 Eckles Avenue, St. Paul, MN, 55108, USA
| | - Erica Spackman
- U.S. Department of Agriculture, Agricultural Research Service, Southeast Poultry Research Laboratory, 934 College Station Road, Athens, GA, 30605, USA
| | - David E Swayne
- U.S. Department of Agriculture, Agricultural Research Service, Southeast Poultry Research Laboratory, 934 College Station Road, Athens, GA, 30605, USA
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10
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Rodríguez-Prieto V, Vicente-Rubiano M, Sánchez-Matamoros A, Rubio-Guerri C, Melero M, Martínez-López B, Martínez-Avilés M, Hoinville L, Vergne T, Comin A, Schauer B, Dórea F, Pfeiffer DU, Sánchez-Vizcaíno JM. Systematic review of surveillance systems and methods for early detection of exotic, new and re-emerging diseases in animal populations. Epidemiol Infect 2015; 143:2018-42. [PMID: 25353252 PMCID: PMC9506978 DOI: 10.1017/s095026881400212x] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2014] [Revised: 07/25/2014] [Accepted: 07/27/2014] [Indexed: 11/07/2022] Open
Abstract
In this globalized world, the spread of new, exotic and re-emerging diseases has become one of the most important threats to animal production and public health. This systematic review analyses conventional and novel early detection methods applied to surveillance. In all, 125 scientific documents were considered for this study. Exotic (n = 49) and re-emerging (n = 27) diseases constituted the most frequently represented health threats. In addition, the majority of studies were related to zoonoses (n = 66). The approaches found in the review could be divided in surveillance modalities, both active (n = 23) and passive (n = 5); and tools and methodologies that support surveillance activities (n = 57). Combinations of surveillance modalities and tools (n = 40) were also found. Risk-based approaches were very common (n = 60), especially in the papers describing tools and methodologies (n = 50). The main applications, benefits and limitations of each approach were extracted from the papers. This information will be very useful for informing the development of tools to facilitate the design of cost-effective surveillance strategies. Thus, the current literature review provides key information about the advantages, disadvantages, limitations and potential application of methodologies for the early detection of new, exotic and re-emerging diseases.
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Affiliation(s)
- V Rodríguez-Prieto
- VISAVET Centre and Animal Health Department,Veterinary School, Complutense University of Madrid,Madrid,Spain
| | - M Vicente-Rubiano
- VISAVET Centre and Animal Health Department,Veterinary School, Complutense University of Madrid,Madrid,Spain
| | - A Sánchez-Matamoros
- VISAVET Centre and Animal Health Department,Veterinary School, Complutense University of Madrid,Madrid,Spain
| | - C Rubio-Guerri
- VISAVET Centre and Animal Health Department,Veterinary School, Complutense University of Madrid,Madrid,Spain
| | - M Melero
- VISAVET Centre and Animal Health Department,Veterinary School, Complutense University of Madrid,Madrid,Spain
| | - B Martínez-López
- VISAVET Centre and Animal Health Department,Veterinary School, Complutense University of Madrid,Madrid,Spain
| | - M Martínez-Avilés
- VISAVET Centre and Animal Health Department,Veterinary School, Complutense University of Madrid,Madrid,Spain
| | - L Hoinville
- AHVLA Centre for Epidemiology & Risk Analysis,Animal Health Veterinary Laboratories Agency,New Haw,Addlestone,Surrey,UK
| | - T Vergne
- RVC Veterinary Epidemiology,Economics and Public Health Group,Royal Veterinary College,North Mymms,London,UK
| | - A Comin
- SVA Department of Disease Control and Epidemiology,National Veterinary Institute,Uppsala,Sweden
| | - B Schauer
- FLI Institute of Epidemiology, Friedrich-Loeffler-Institute, Federal Research Institute for Animal Health,Greifswald - Insel Riems,Germany
| | - F Dórea
- SVA Department of Disease Control and Epidemiology,National Veterinary Institute,Uppsala,Sweden
| | - D U Pfeiffer
- RVC Veterinary Epidemiology,Economics and Public Health Group,Royal Veterinary College,North Mymms,London,UK
| | - J M Sánchez-Vizcaíno
- VISAVET Centre and Animal Health Department,Veterinary School, Complutense University of Madrid,Madrid,Spain
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11
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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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12
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Weaver JT, Malladi S, Goldsmith TJ, Hueston W, Hennessey M, Lee B, Voss S, Funk J, Der C, Bjork KE, Clouse TL, Halvorson DA. Impact of virus strain characteristics on early detection of highly pathogenic avian influenza infection in commercial table-egg layer flocks and implications for outbreak control. Avian Dis 2013; 56:905-12. [PMID: 23402111 DOI: 10.1637/10189-041012-reg.1] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Early detection of highly pathogenic avian influenza (HPAI) infection in commercial poultry flocks is a critical component of outbreak control. Reducing the time to detect HPAI infection can reduce the risk of disease transmission to other flocks. The timeliness of different types of detection triggers could be dependent on clinical signs that are first observed in a flock, signs that might vary due to HPAI virus strain characteristics. We developed a stochastic disease transmission model to evaluate how transmission characteristics of various HPAI strains might effect the relative importance of increased mortality, drop in egg production, or daily real-time reverse transcriptase (RRT)-PCR testing, toward detecting HPAI infection in a commercial table-egg layer flock. On average, daily RRT-PCR testing resulted in the shortest time to detection (from 3.5 to 6.1 days) depending on the HPAI virus strain and was less variable over a range of transmission parameters compared with other triggers evaluated. Our results indicate that a trigger to detect a drop in egg production would be useful for HPAI virus strains with long infectious periods (6-8 days) and including an egg-drop detection trigger in emergency response plans would lead to earlier and consistent reporting in some cases. We discuss implications for outbreak control and risk of HPAI spread attributed to different HPAI strain characteristics where an increase in mortality or a drop in egg production or both would be among the first clinical signs observed in an infected flock.
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Affiliation(s)
- J Todd Weaver
- USDA Animal and Plant Health Inspection Service, Veterinary Services, Centers for Epidemiology and Animal Health, Center for Animal Health Information and Analysis, Natural Resource Research Center, Building B MS-2W4, 2150 Centre Avenue, Fort Collins, CO 80526, USA.
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13
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Malladi S, Weaver JT, Goldsmith T, Hueston W, Voss S, Funk J, Der C, Bjork KE, Clouse TL, Hennessey M, Sampedro F, Lee B, Halvorson DA. The impact of holding time on the likelihood of moving internally contaminated eggs from a highly pathogenic avian influenza infected but undetected commercial table-egg layer flock. Avian Dis 2013; 56:897-904. [PMID: 23402110 DOI: 10.1637/10191-041012-reg.1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Emergency response during a highly pathogenic avian influenza (HPAI) outbreak may involve quarantine and movement controls for poultry products such as eggs. However, such disease control measures may disrupt business continuity and impact food security, since egg production facilities often do not have sufficient capacity to store eggs for prolonged periods. We propose the incorporation of a holding time before egg movement in conjunction with targeted active surveillance as a novel approach to move eggs from flocks within a control area with a low likelihood of them being contaminated with HPAI virus. Holding time reduces the likelihood of HPAI-contaminated eggs being moved from a farm before HPAI infection is detected in the flock. We used a stochastic disease transmission model to estimate the HPAI disease prevalence, disease mortality, and fraction of internally contaminated eggs at various time points postinfection of a commercial table-egg layer flock. The transmission model results were then used in a simulation model of a targeted matrix gene real-time reverse transcriptase (RRT)-PCR testing based surveillance protocol to estimate the time to detection and the number of contaminated eggs moved under different holding times. Our simulation results indicate a significant reduction in the number of internally contaminated eggs moved from an HPAI-infected undetected flock with each additional day of holding time. Incorporation of a holding time and the use of targeted surveillance have been adopted by the U.S. Department of Agriculture in their Draft Secure Egg Supply Plan for movement of egg industry products during an HPAI outbreak.
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Affiliation(s)
- Sasidhar Malladi
- University of Minnesota, Center for Animal Health and Food Safety, 136 Andrew Boss Laboratory, 1354 Eckles Avenue, St. Paul, MN 55108, USA.
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