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

• Published in: Animals (Basel) Vol. 13; no. 22; p. 3525
• Main Authors: Dorotea, Tiziano, Riuzzi, Giorgia, Franzago, Eleonora, Posen, Paulette, Tavornpanich, Saraya, Di Lorenzo, Alessio, Ferroni, Laura, Martelli, Walter, Mazzucato, Matteo, Soccio, Grazia, Segato, Severino, Ferrè, Nicola
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2023
• Subjects: Analysis; Animal diseases; Aquaculture; Aquaculture industry; Data mining; Development and progression; disease; Disease control; Disease prevention; Disease transmission; Epidemics; Epidemiology; farmed fish; Fish; Fish as food; Fish-culture; Fresh water; Geographic information systems; Geography; Geospatial data; GIS methods; health management; Health surveillance; Infectious diseases; Parasitic diseases; Remote sensing; Risk factors; risk mapping; risk modelling; Canada; United Kingdom; Chile; Norway
• ISSN: 2076-2615; 2076-2615
• DOI: 10.3390/ani13223525

Finfish aquaculture, one of the fastest growing intensive sectors worldwide, is threatened by numerous transmissible diseases that may have devastating impacts on its economic sustainability. This review (2010–2022) used a PRISMA extension for scoping reviews and a text mining approach to explore the extent to which geographical information systems (GIS) are used in farmed fish health management and to unveil the main GIS technologies, databases, and functions used to update the spatiotemporal data underpinning risk and predictive models in aquatic surveillance programmes. After filtering for eligibility criteria, the literature search provided 54 records, highlighting the limited use of GIS technologies for disease prevention and control, as well as the prevalence of GIS application in marine salmonid farming, especially for viruses and parasitic diseases typically associated with these species. The text mining generated five main research areas, underlining a limited range of investigated species, rearing environments, and diseases, as well as highlighting the lack of GIS-based methodologies at the core of such publications. This scoping review provides a source of information for future more detailed literature analyses and outcomes to support the development of geospatial disease spread models and expand in-field GIS technologies for the prevention and mitigation of fish disease epidemics.