EPIZOOTIOLOGY AND ENDEMIC CHANNEL OF Perkinsus marinus, PARASITE OF THE PLEASURE OYSTER Crassostrea corteziensis, IN THE PACIFIC COAST OF MEXICO  

The protozoan parasite Perkinsus marinus is the etiological agent of Perkinsosis, this pathogen is considered by the International Organization for Animal Health (OIE) as a reportable due to the high mortalities that it produces in the American oyster Crassostrea virginica in US. In 2006, this parasite was detected in the pleasure oyster Crassostrea corteziensis in Nayarit in the Pacific coast of Mexico, indicating a new host and an extension of its distribution area. Epizootiology data of Perkinsosis in the pleasure oyster are unknown. With the objective of determining the prevalence and intensity in relation with temperature and salinity throughout time, as well as for studying interactions between host size and sex with the parasite, a monthly sampling was carried out in two aquaculture sites of Nayarit from 2007 to 2014.

A total of 7,700 oysters were analyzed. In both localities, prevalence was low in winter (<6%) when temperature and salinity fluctuated around 24^°C and 33 psu, respectively; and the highest values occurred during summer (36.6%) when temperature and salinity were around 30^°C and 20 psu, respectively. Infection intensity increased in summer, but severe cases remained in average <10%. Larger oysters showed the highest values of prevalence and intensity, also higher prevalence values were generally observed in females. No unusual mortalities directly related with P. marinus were observed; however, morbidity could have a negative effect in production. Additionally, an increase in the lower temperature records from 21^°C in 2007 to 26^°C in 2014 suggests possible future changes in the interactions between parasite-host in association with global warming; thus, epizootiological surveillance is needed. An endemic threshold or endemic channel was calculated for predicting the number of cases throughout time, which will allow and aid producers and authorities for evaluating and predicting the course of the disease in the studied area, figure 1.