Estimating West Nile virus transmission period in Pennsylvania using an optimized degree-day model

Shi Chen, Justine I. Blanford, Shelby J. Fleischer, Michael Hutchinson, Michael C. Saunders, Matthew B. Thomas

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

We provide calibrated degree-day models to predict potential West Nile virus (WNV) transmission periods in Pennsylvania. We begin by following the standard approach of treating the degree-days necessary for the virus to complete the extrinsic incubation period (EIP), and mosquito longevity as constants. This approach failed to adequately explain virus transmission periods based on mosquito surveillance data from 4 locations (Harrisburg, Philadelphia, Pittsburgh, and Williamsport) in Pennsylvania from 2002 to 2008. Allowing the EIP and adult longevity to vary across time and space improved model fit substantially. The calibrated models increase the ability to successfully predict the WNV transmission period in Pennsylvania to 70-80% compared to less than 30% in the uncalibrated model. Model validation showed the optimized models to be robust in 3 of the locations, although still showing errors for Philadelphia. These models and methods could provide useful tools to predict WNV transmission period from surveillance datasets, assess potential WNV risk, and make informed mosquito surveillance strategies.

Original languageEnglish (US)
Pages (from-to)489-497
Number of pages9
JournalVector-Borne and Zoonotic Diseases
Volume13
Issue number7
DOIs
StatePublished - Jul 1 2013

All Science Journal Classification (ASJC) codes

  • Microbiology
  • Infectious Diseases
  • Virology

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