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APPLICATION OF EPIDEMIOLOGICAL MODELLING OF Sparicotyle chrysophrii TRANSMISSION IN Sparus aurata FARMS Elisa Stella1, *, Roberto Pastres1 , Damiano Pasetto1 , Matko Kolega2 , Danijel Mejdandžić2 , Slavica Čolak2 , Lorenzo Mari3 , Enrico Bertuzzo1 1 Department of Environmental Sciences, Informatics and Statistics, Ca’ Foscari University of Venice Scientific Campus, Via Torino, 155, 30172, Mestre- Venice, Italy 2 Cromaris d.d., Zadar, Croatia 3 Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano Via Ponzio 34/5, 20133, Milan, Italy E-mail: elisa.stella@unive.it Introduction Mediterranean aquaculture production is known to have impacts on the environmental and marine habitat, impairing water and bottom sediment quality. Furthermore, rapid development of cage fish farming has been associated with propagation of infectious diseases, pathogens and parasites. Sparicotyle chrysophrii is a common parasite of cultured Gilthead sea bream (Sparus aurata), an important species for Mediterranean aquaculture production. The parasite attaches on fish gills and can cause lethal epizootics in sea cages. Infections depend on environmental factors, in particular on water temperature (Antonelli et al., 2010). Epidemiological modeling represents a valid tool to help fish farmers understand parasite transmission and evaluate possible control measures. To this purpose, in the following we analyze a novel epidemiological model of S. chrysophrii transmission. Methods We developed a novel stratified compartmental model where each compartment Xja represents the abundance of fish infected with j juvenile parasites and a adults. The model further accounts for environmental abundance of eggs and miracidia, where the latter determines the force of infection, i.e. the rate at which parasite larvae attach to fish. The dynamics further accounts for egg production and hatching, parasite development, baseline mortality for parasites and fish, and parasite-induced fish mortality. Critical parameters controlling the progression of the disease are assumed to be temperature dependent. We applied the model to data collected in six cages of a sea bream farm managed by Cromaris (Bisage, Croatia). A controlled experiment was run between February and November 2021 in which 30 fish were collected each month and, for each fish, all eight arc gills were examined to count the number of attached parasites. We estimated model parameters in a Bayesyan framework, sampling the posterior distribution with a Markov Chain Monte Carlo algorithm. Specifically, the model estimates the temporal dynamics of the probability that a sampled fish hosts a certain number of adult parasites. The likelihood of a monthly sample is calculated assuming a multinomial distribution, where the event probabilities are estimated through the deterministic model simulation given a certain parameter set. We further included the total number of fish alive at any time in the determination of the likelihood. Results Results show that the model is able to reproduce the distribution of the number of parasites hosted by the sampled fish (Figure 1), as well as the temporal progression of the prevalence of infection (i.e., the number of fish hosting at least one parasite). Data shows that prevalence has a peak in August, after the period with the warmest water temperature, and then decreases. Discussion and conclusions We applied a novel epidemiological model to a dataset of S. chrysophrii infections collected in a sea bream farm. The model succeeds in simulating the effects of environmental factors (e.g., water temperature) on the infection dynamics. Posterior distribution of parameters shed insights on crucial process rates that control disease transmission. Future developments could involve coupling the epidemiological model with a fish growth model to simulate the effect of parasite burden on fish metabolism. The knowledge gained through this combined experimental and modeling exercise could be used in the future for designing and implementing strategies to control the spreading of the infection and, accordingly, to improve both fish health and aquaculture production. (Continued on next page) 1250 Acknowledgements The research leading to these results has received funding from the European Union’s HORIZON 2020 Framework Programme under Grant Agreement no. 862658. References Antonelli, L., Quilichini, Y., & Marchand, B (2010). Sparicotyle chrysophrii (Van Beneden and Hesse, 1863) (Monogenea: Polyopisthocotylea) parasite of cultured gilthead sea bream Sparus aurata (Linnaeus 1758) (Pisces: Teleostei) from Corsica: Ecological and morphological study. Parasitology Research, 107:389–398. |
