Gorka Bidegain

Dr. Gorka Bidegain

Applied Mathematics, University of the Basque Country (UPV/EHU), Bilbao, Basque Country, Spain

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 2015 in Journal of Invertebrate Pathology
Verified
Journal Article
Closed access
TBTal Ben-Horin
Tal Ben-Horin
GBGorka Bidegain
Gorka Bidegain
LHLauren Huey
Lauren Huey
DNDiego Narváez
Diego Narváez
DBDavid Bushek
David Bushek

1 October 2013 in Ecological Modelling
Verified
Journal Article
Closed access
GBGorka Bidegain
Gorka Bidegain
Javier F. BárcenaJavier F. Bárcena
Javier F. Bárcena
AGAndrés García
Andrés García
JJJosé Antonio Juanes
José Antonio Juanes

1 December 2012 in Ocean & Coastal Management
Verified
Journal Article
Closed access
JJJosé Antonio Juanes
José Antonio Juanes
GBGorka Bidegain
Gorka Bidegain
BEBeatriz Echavarri-Erasun
Beatriz Echavarri-Erasun
APAraceli Puente
Araceli Puente
AGAna García
Ana García
GGGerardo García-Castillo
Gerardo García-Castillo

28 April 2016 in Ecosphere
Verified
Journal Article
Open access
PDF file
GBGorka Bidegain
Gorka Bidegain
EPEric N. Powell
Eric N. Powell
JKJohn M. Klinck
John M. Klinck
TBTal Ben‐Horin
Tal Ben‐Horin
EHEileen E. Hofmann
Eileen E. Hofmann
Disease‐causing organisms can have significant impacts on marine species and communities. However, the dynamics that underlie the emergence of disease outbreaks in marine ecosystems still lack the equivalent level of description, conceptual understanding, and modeling context routinely present in the terrestrial systems. Here, we propose a theoretical basis for modeling the transmission of marine infectious diseases (MIDs) developed from simple models of the spread of infectious disease. The models represent the dynamics of a variety of host–pathogen systems including those unique to marine systems where transmission of disease is by contact with waterborne pathogens both directly and through filter‐feeding processes. Overall, the analysis of the epizootiological models focused on the most relevant processes that interact to drive the initiation and termination of epizootics.A priori, systems with multi‐step disease infections (e.g., infection‐death‐particle release‐filtration‐transmission) reduced dependence on individual parameters resulting in inherently slower transmissions rates. This is demonstrably not the case; thus, these alternative transmission pathways must also considerably increase the rates of processes involved in transmission. Scavengers removing dead infected animals may inhibit disease spread in both contact‐based and waterborne pathogen‐based diseases. The capacity of highly infected animals, both alive and dead, to release a substantial number of infective elements into the water column, making them available to suspension feeders results in such diseases being highly infective with a very small “low‐abundance refuge”. In these systems, the body burden of pathogens and the relative importance between the release and the removal rate of pathogens in the host tissue or water column becomes paramount. Two processes are of potential consequence inhibiting epizootics. First, large water volumes above the benthic susceptible populations can function as a sink for pathogens. Second, unlike contact‐based disease models in which an increase in the number of susceptible individuals in the population increases the likelihood of transmission and epizootic development, large populations of filter feeders can reduce this likelihood through the overfiltration of infective particles.

1 February 2017 in Fisheries Research
Verified
Journal Article
Closed access
GBGorka Bidegain
Gorka Bidegain
EPE.N. Powell
E.N. Powell
JKJ.M. Klinck
J.M. Klinck
EHE.E. Hofmann
E.E. Hofmann
TBT. Ben-Horin
T. Ben-Horin
XGX. Guo
X. Guo