Version 1
: Received: 6 March 2023 / Approved: 9 March 2023 / Online: 9 March 2023 (09:40:44 CET)
How to cite:
Fernández-Vélez, I.; Bidegain, G.; Ben-Horin, T. Predicting the Growth of Vibrio parahaemolyticus in Oysters Under Varying Ambient Temperature. Preprints2023, 2023030173. https://doi.org/10.20944/preprints202303.0173.v1.
Fernández-Vélez, I.; Bidegain, G.; Ben-Horin, T. Predicting the Growth of Vibrio parahaemolyticus in Oysters Under Varying Ambient Temperature. Preprints 2023, 2023030173. https://doi.org/10.20944/preprints202303.0173.v1.
Cite as:
Fernández-Vélez, I.; Bidegain, G.; Ben-Horin, T. Predicting the Growth of Vibrio parahaemolyticus in Oysters Under Varying Ambient Temperature. Preprints2023, 2023030173. https://doi.org/10.20944/preprints202303.0173.v1.
Fernández-Vélez, I.; Bidegain, G.; Ben-Horin, T. Predicting the Growth of Vibrio parahaemolyticus in Oysters Under Varying Ambient Temperature. Preprints 2023, 2023030173. https://doi.org/10.20944/preprints202303.0173.v1.
Abstract
Temperature is a critical factor that influences the proliferation of pathogens in hosts. The impact of temperature on pathogens is commonly explored in controlled and constant temperatures. Experiments under varying environmental temperature are becoming more frequent, however, testing every temperature scenario à la carte is unachievable. One example of this is the human pathogen Vibrio parahaemolyticus (Vp) in oysters. Here, a predictive model was developed for predicting the growth of Vp in oysters under varying ambient temperature. The model was fitted and evaluated against data from experiments studying growth and inactivation of Vp in oysters at eight constant temperatures. Once evaluated, Vp dynamics in oysters were estimated at different post-harvest varying temperature scenarios affected by water and air temperature, and different ice treatment timing. The model performed adequately under varying temperature, reflecting that (i) increasing temperature, particularly in hot summers, favors a rapid Vp growth in oysters, resulting in a very high risk of gastroenteritis in humans after consumption of a serving of raw oysters, (ii) pathogen inactivation due to day/night oscillations, and more evidently, due to ice treatments, (iii) ice treatment is much more effective limiting risk of illness when applied immediately onboard compared to dockside. The model results to be a promising tool for improving the understanding of the Vp-oyster system and support studies on public health impact of pathogenic Vp associated with raw oyster consumption. Although robust validation of the model predictions is needed, initial results and evaluation show the potential of the model to be easily modified to match similar systems where the temperature is a critical factor shaping the proliferation of pathogens in hosts.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
