Using Quantitative Disease Dynamics as a Tool for Guiding Response to Avian Influenza in Poultry in the United States of America

Authors

K. M. Pepin, Colorado State UniversityFollow
E. Spackman, USDA-ARS, Athens, GAFollow
J. D. Brown, University of GeorgiaFollow
K. L. Pabilonia, Colorado State University - Fort CollinsFollow
Lindsey P. Garber, USDA APHIS, Fort Collins, COFollow
J. Todd Weaver, USDA APHIS, Fort Collins, COFollow
D. A. Kennedy, National Institute of Health, Bethesda, MDFollow
Kelly A. Patyk, USDA APHIS, Fort Collins, COFollow
K. P. Huyvaert, Colorado State University - Fort CollinsFollow
Ryan S. Miller, USDA APHIS, Fort Collins, COFollow
Alan B. Franklin, USDA NWRCFollow
Kerri Pedersen, USDA NWRC, Fort Collins, COFollow
T. L. Bogich, National Institute of Health, Bethesda, MDFollow
P. Rohani, National Institute of Health, Bethesda, MDFollow
Susan A. Shriner, USDA/APHIS/WS National Wildlife Research CenterFollow
Colleen T. Webb, Colorado State UniversityFollow
S. Riley, National Institute of Health, Bethesda, MDFollow

Date of this Version

2014

Citation

Pepin, K.M., E. Spackman, J.D. Brown, K.L. Pabilonia, L.P. Garber, J.T. Weaver, D.A. Kennedy, K.A. Patyk, K.P. Huyvaert, R.S. Miller, A.B. Franklin, K. Pedersen, T.L. Bogich, P. Rohani, S.A. Shriner, C.T. Webb, and S. Riley. 2014. Using quantitative disease dynamics as a tool for guiding response to avian influenza in poultry in the United States of America. Preventive Veterinary Medicine 113(4): 376-397. doi: 10.1016/j.prevetmed.2013.11.011.

Comments

US govt work.

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.