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Applications of GIS: Disaster Management and Emergency Response

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Updated: Jul 10, 2025

Necropsy-based Wild Fish Health Assessment

Necropsy-based Wild Fish Health Assessment

Published on: September 11, 2018

A Scoping Review on GIS Technologies Applied to Farmed Fish Health Management.

Tiziano Dorotea¹, Giorgia Riuzzi², Eleonora Franzago¹

¹Istituto Zooprofilattico Sperimentale delle Venezie, 35020 Legnaro, Italy.

Animals : an Open Access Journal From MDPI

|November 25, 2023

Summary

Geographical Information Systems (GIS) show limited use in finfish aquaculture disease management. Future research should focus on developing GIS-based models for aquatic surveillance and disease prevention.

Keywords:

GIS methods disease farmed fish health management risk mapping risk modelling scoping review surveillance

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Published on: July 2, 2018

Area of Science:

Aquatic Health
Veterinary Epidemiology
Geospatial Science

Background:

Finfish aquaculture faces significant economic threats from transmissible diseases.
Effective disease management is crucial for the sustainability of this rapidly growing sector.

Purpose of the Study:

To review the application of Geographical Information Systems (GIS) in finfish farmed health management from 2010-2022.
To identify key GIS technologies, databases, and functions used in aquatic surveillance.
To explore the spatiotemporal data utilized in risk and predictive models.

Main Methods:

A scoping review using PRISMA extension methodology.
Text mining approach applied to 54 selected literature records.
Analysis of GIS technologies, databases, functions, and research areas.

Main Results:

Limited utilization of GIS for disease prevention and control in finfish aquaculture.
Prevalence of GIS application in marine salmonid farming, particularly for viral and parasitic diseases.
Identified five main research areas, indicating a narrow focus on species, environments, and diseases.
Lack of GIS-based methodologies central to the reviewed publications.

Conclusions:

Geospatial technologies are underutilized in finfish health management.
Further development of GIS-based models is needed for aquatic disease surveillance and prediction.
Expanding in-field GIS applications can aid in preventing and mitigating fish disease epidemics.