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Open AccessArticle

Forecasting Seasonal Vibrio parahaemolyticus Concentrations in New England Shellfish

1
Northeast Center for Vibrio Disease and Ecology, University of New Hampshire, Durham, NH 03824, USA
2
Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, NH 03824, USA
3
Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH 03824, USA
4
Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
5
Division of Nutrition Data Sciences, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2019, 16(22), 4341; https://doi.org/10.3390/ijerph16224341
Received: 18 September 2019 / Revised: 30 October 2019 / Accepted: 30 October 2019 / Published: 7 November 2019
(This article belongs to the Special Issue Infectious Disease Modeling in the Era of Complex Data)
Seafood-borne Vibrio parahaemolyticus illness is a global public health issue facing resource managers and the seafood industry. The recent increase in shellfish-borne illnesses in the Northeast United States has resulted in the application of intensive management practices based on a limited understanding of when and where risks are present. We aim to determine the contribution of factors that affect V. parahaemolyticus concentrations in oysters (Crassostrea virginica) using ten years of surveillance data for environmental and climate conditions in the Great Bay Estuary of New Hampshire from 2007 to 2016. A time series analysis was applied to analyze V. parahaemolyticus concentrations and local environmental predictors and develop predictive models. Whereas many environmental variables correlated with V. parahaemolyticus concentrations, only a few retained significance in capturing trends, seasonality and data variability. The optimal predictive model contained water temperature and pH, photoperiod, and the calendar day of study. The model enabled relatively accurate seasonality-based prediction of V. parahaemolyticus concentrations for 2014–2016 based on the 2007–2013 dataset and captured the increasing trend in extreme values of V. parahaemolyticus concentrations. The developed method enables the informative tracking of V. parahaemolyticus concentrations in coastal ecosystems and presents a useful platform for developing area-specific risk forecasting models. View Full-Text
Keywords: Vibrio parahaemolyticus; seasonality; seafood illness; forecasting; climate change Vibrio parahaemolyticus; seasonality; seafood illness; forecasting; climate change
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Hartwick, M.A.; Urquhart, E.A.; Whistler, C.A.; Cooper, V.S.; Naumova, E.N.; Jones, S.H. Forecasting Seasonal Vibrio parahaemolyticus Concentrations in New England Shellfish. Int. J. Environ. Res. Public Health 2019, 16, 4341.

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