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Your search keyword '"Kerri Pedersen"' showing total 3 results
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3 results on '"Kerri Pedersen"'

1. Detection error influences both temporal seroprevalence predictions and risk factors associations in wildlife disease models

Author

Michael A. Tabak, Kerri Pedersen, and Ryan S. Miller

Subjects
detection probability, hierarchical Bayesian model, opportunistic sampling, pathogen, prevalence, sensitivity, Ecology, QH540-549.5
Abstract

Abstract Understanding the prevalence of pathogens in invasive species is essential to guide efforts to prevent transmission to agricultural animals, wildlife, and humans. Pathogen prevalence can be difficult to estimate for wild species due to imperfect sampling and testing (pathogens may not be detected in infected individuals and erroneously detected in individuals that are not infected). The invasive wild pig (Sus scrofa, also referred to as wild boar and feral swine) is one of the most widespread hosts of domestic animal and human pathogens in North America. We developed hierarchical Bayesian models that account for imperfect detection to estimate the seroprevalence of five pathogens (porcine reproductive and respiratory syndrome virus, pseudorabies virus, Influenza A virus in swine, Hepatitis E virus, and Brucella spp.) in wild pigs in the United States using a dataset of over 50,000 samples across nine years. To assess the effect of incorporating detection error in models, we also evaluated models that ignored detection error. Both sets of models included effects of demographic parameters on seroprevalence. We compared our predictions of seroprevalence to 40 published studies, only one of which accounted for imperfect detection. We found a range of seroprevalence among the pathogens with a high seroprevalence of pseudorabies virus, indicating significant risk to livestock and wildlife. Demographics had mostly weak effects, indicating that other variables may have greater effects in predicting seroprevalence. Models that ignored detection error led to different predictions of seroprevalence as well as different inferences on the effects of demographic parameters. Our results highlight the importance of incorporating detection error in models of seroprevalence and demonstrate that ignoring such error may lead to erroneous conclusions about the risk associated with pathogen transmission. When using opportunistic sampling data to model seroprevalence and evaluate risk factors, detection error should be included.

Published
2019
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2. Identification and Analysis of the First 2009 Pandemic H1N1 Influenza Virus from U.S. Feral Swine

Author

Mark W. Lutman, Mohammad Bounpheng, L. G. Koster, Amir Nikooienejad, Melinda Jenkins-Moore, Sabrina L. Swenson, Mohammad Shahrokh Esfahani, M. Zhang, A. Clavijo, L. R. Bazan, T. Beckham, Charles D. Johnson, Scott Schwartz, Richard P. Metz, Thomas J. DeLiberto, Kerri Pedersen, and Esmaeli Atashpaz-Gargari

Subjects
Sanger sequencing, medicine.medical_specialty, General Veterinary, General Immunology and Microbiology, Phylogenetic tree, Epidemiology, H1N1 influenza, Public Health, Environmental and Occupational Health, Biology, Virology, Deep sequencing, DNA sequencing, Virus, symbols.namesake, Infectious Diseases, Molecular genetics, Pandemic, medicine, symbols
Abstract

Summary The first case of pandemic H1N1 influenza (pH1N1) virus in feral swine in the United States was identified in Texas through the United States Department of Agriculture (USDA) Wildlife Services’ surveillance program. Two samples were identified as pandemic influenza by reverse transcriptase quantitative PCR (RT-qPCR). Full-genome Sanger sequencing of all eight influenza segments was performed. In addition, Illumina deep sequencing of the original diagnostic samples and their respective virus isolation cultures were performed to assess the feasibility of using an unbiased whole-genome linear target amplification method and multiple sample sequencing in a single Illumina GAIIx lane. Identical sequences were obtained using both techniques. Phylogenetic analysis indicated that all gene segments belonged to the pH1N1 (2009) lineage. In conclusion, we have identified the first pH1N1 isolate in feral swine in the United States and have demonstrated the use of an easy unbiased linear amplification method for deep sequencing of multiple samples.

Published
2012

3. Surveillance for highly pathogenic avian influenza in wild birds in the USA

Author

Thomas J. DeLiberto, Mark W. Lutman, Dale L. Nolte, Alan B. Franklin, Dennis J. Kohler, John A. Baroch, Seth R. Swafford, Brandon S. Schmit, and Kerri Pedersen

Subjects
Disease surveillance, Influenza A Virus, H5N1 Subtype, Highly pathogenic, Prevalence, Pandemic influenza, Zoology, Animals, Wild, Biology, Wildlife disease, medicine.disease_cause, Virology, United States, Influenza A virus subtype H5N1, Birds, Highly Pathogenic Avian Influenza Virus, Influenza in Birds, Population Surveillance, medicine, Animals, Animal Science and Zoology, Feces
Abstract

As part of the USA’s National Strategy for Pandemic Influenza, an Interagency Strategic Plan for the Early Detection of Highly Pathogenic H5N1 Avian Influenza in Wild Migratory Birds was developed and implemented. From 1 April 2006 through 31 March 2009, 261 946 samples from wild birds and 101 457 wild bird fecal samples were collected in the USA; no highly pathogenic avian influenza was detected. The United States Department of Agriculture, and state and tribal cooperators accounted for 213 115 (81%) of the wild bird samples collected; 31, 27, 21 and 21% of the samples were collected from the Atlantic, Pacific, Central and Mississippi flyways, respectively. More than 250 species of wild birds in all 50 states were sampled. The majority of wild birds (86%) were dabbling ducks, geese, swans and shorebirds. The apparent prevalence of low pathogenic avian influenza viruses during biological years 2007 and 2008 was 9.7 and 11.0%, respectively. The apparent prevalence of H5 and H7 subtypes across all species sampled were 0.5 and 0.06%, respectively. The pooled fecal samples (n = 101 539) positive for low pathogenic avian influenza were 4.0, 6.7 and 4.7% for biological years 2006, 2007 and 2008, respectively. The highly pathogenic early detection system for wild birds developed and implemented in the USA represents the largest coordinated wildlife disease surveillance system ever conducted. This effort provided evidence that wild birds in the USA were free of highly pathogenic avian influenza virus (given the expected minimum prevalence of 0.001%) at the 99.9% confidence level during the surveillance period.

Published
2009

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