ArticleVector borne and zoonotic diseases (Larchmont, N.Y.)2013
Estimating West Nile virus transmission period in Pennsylvania using an optimized degree-day model.
Article in Vector borne and zoonotic diseases (Larchmont, N.Y.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Impact of Day/Night Cycle Temperature Regimes on Zika Virus Replication in Mosquito Cells and Implications for Transmission Potential.Pathogens (Basel, Switzerland) · 2026Article
- The rise of West Nile Virus in Southern and Southeastern Europe: A spatial-temporal analysis investigating the combined effects of climate, land use and economic changes.One health (Amsterdam, Netherlands) · 2021Article
- The influence of diurnal temperature variation on degree-day accumulation and insect life history.PloS one · 2015Article
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Authors and funding
6 authors.
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Abstract
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.
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