Estimating within-flock transmission rate parameter for H5N2 highly pathogenic avian influenza virus in Minnesota turkey flocks during the 2015 epizootic

A. Ssematimba, S. Malladi, T. J. Hagenaars, P. J. Bonney, J. T. Weaver, K. A. Patyk, E. Spackman, D. A. Halvorson, C. J. Cardona

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)e179
Number of pages8
JournalEpidemiology and infection
Volume147
DOIs
StatePublished - Jan 1 2019

Bibliographical note

Funding Information:
We thank Marian Bos, Mart de Jong, Jos? Gonzales and Bas Engel for discussions. Ssematimba is grateful to Gulu University for granting him the opportunity to work with the UMN Secure Food Systems Team. This work was funded by the United States Department of Agriculture Animal and Plant Health Inspection Service (USDA APHIS; Riverdale Park, Maryland USA) as a supplement to grant number 16-9794-2536-CA (Facilitating Public Private Partnerships for the Management of High Path Avian Influenza and Other Animal Disease Emergencies). Dr Cardona is also funded by the B.S. Pomeroy Chair in Avian Health at the University of Minnesota, College of Veterinary Medicine.

Funding Information:
Bas Engel for discussions. Ssematimba is grateful to Gulu University for granting him the opportunity to work with the UMN Secure Food Systems Team. This work was funded by the United States Department of Agriculture Animal and Plant Health Inspection Service (USDA APHIS; Riverdale Park, Maryland USA) as a supplement to grant number 16-9794-2536-CA (Facilitating Public Private Partnerships for the Management of High Path Avian Influenza and Other Animal Disease Emergencies). Dr Cardona is also funded by the B.S. Pomeroy Chair in Avian Health at the University of Minnesota, College of Veterinary Medicine.

Publisher Copyright:
© The Author(s) 2019.

Keywords

  • Analysis of data
  • avian flu
  • mathematical modelling
  • veterinary epidemiology

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

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