2013 Conference of the International Medical Geology Association (25–29 August 2013)

Paper No. 2
Presentation Time: 11:20 AM


URQUHART, Erin A., Earth and Planetary Sciences, Johns Hopkins University, 3400 N. Charles Street, 301 Olin Hall, Baltimore, MD 21218, ZAITCHIK, Benjamin F., Earth and Planetary Sciences, Johns Hopkins University, Baltimore, MD 21218 and GUIKEMA, Seth, Geography and Environmental Engineering, Johns Hopkins University, 3400 N. Charles Street, 205 Ames Hall, Baltimore, MD 21218, erinu@jhu.edu

The Chesapeake Bay is the largest estuary in the United States, and home to an increasing number of harmful marine species including Vibrio bacteria. While routine water monitoring has been successful in preventing Vibrio outbreaks in the Chesapeake Bay, there is a pressing need for advanced technology to prevent the future spread and severity of this public health problem. In situ based methods for detecting Vibrio bacteria are often constrained by financial costs as well the spatiotemporal resolution requirements for bacteria detection. Satellite-remote sensing, which has the ability to utilize optical and thermal signatures of the surface waters, can offer near-real time detection of Vibrio in coastal waters. Geospatially interpolated MODIS-derived salinity and temperature estimates can be used as input into several empirical Vibrio models capable of estimating the probability and concentration of Vibrio in the Bay. In this way, spatially complete hindcast estimates of Vibrio spp. can be produced pixel by pixel, enabling assessment of the spatial and temporal trends of Vibrio bacteria across the Bay. The intended outcome of this research is to use the information of these satellite products to inform public health risk models for Vibrio spp. in shellfish and recreational waters in the Chesapeake Bay. Though Vibrio spp. does not pose a serious health threat in the Chesapeake Bay, using the Chesapeake Bay as a model “test bed” can provide valuable model information, and help quantify model uncertainty that can later be extended to data poor regions of the world significantly aiding in the prediction and, potentially, prevention of Vibrio outbreaks.