First Steps towards a near Real-Time Modelling System of Vibrio vulnificus in the Baltic Sea

Eike M. Schütt (), Marie A. J. Hundsdörfer, Avril J. E. von Hoyningen-Huene, Xaver Lange, Agnes Koschmider and Natascha Oppelt
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Eike M. Schütt: Earth Observation and Modelling, Department of Geography, Kiel University, 24118 Kiel, Germany
Marie A. J. Hundsdörfer: Earth Observation and Modelling, Department of Geography, Kiel University, 24118 Kiel, Germany
Avril J. E. von Hoyningen-Huene: Molecular Microbiology, Institute for General Microbiology, Kiel University, 24118 Kiel, Germany
Xaver Lange: Leibniz Institute for Baltic Sea Research Warnemünde, 18119 Rostock, Germany
Agnes Koschmider: Business Informatics and Process Analytics, University of Bayreuth, 95447 Bayreuth, Germany
Natascha Oppelt: Earth Observation and Modelling, Department of Geography, Kiel University, 24118 Kiel, Germany

IJERPH, 2023, vol. 20, issue 8, 1-21

Abstract: Over the last two decades, Vibrio vulnificus infections have emerged as an increasingly serious public health threat along the German Baltic coast. To manage related risks, near real-time (NRT) modelling of V. vulnificus quantities has often been proposed. Such models require spatially explicit input data, for example, from remote sensing or numerical model products. We tested if data from a hydrodynamic, a meteorological, and a biogeochemical model are suitable as input for an NRT model system by coupling it with field samples and assessing the models’ ability to capture known ecological parameters of V. vulnificus . We also identify the most important predictors for V. vulnificus in the Baltic Sea by leveraging the St. Nicolas House Analysis. Using a 27-year time series of sea surface temperature, we have investigated trends of V. vulnificus season length, which pinpoint hotspots mainly in the east of our study region. Our results underline the importance of water temperature and salinity on V. vulnificus abundance but also highlight the potential of air temperature, oxygen, and precipitation to serve as predictors in a statistical model, albeit their relationship with V. vulnificus may not be causal. The evaluated models cannot be used in an NRT model system due to data availability constraints, but promising alternatives are presented. The results provide a valuable basis for a future NRT model for V. vulnificus in the Baltic Sea.

Keywords: Vibrio vulnificus; Baltic Sea; near real-time modelling; St. Nicolas House Analysis; network inference; public health risk; climate change (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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