4.3 Article

Hydrodynamic connectivity, water temperature, and salinity are major drivers of piscirickettsiosis prevalence and transmission among salmonid farms in Chile

期刊

AQUACULTURE ENVIRONMENT INTERACTIONS
卷 12, 期 -, 页码 263-279

出版社

INTER-RESEARCH
DOI: 10.3354/aei00368

关键词

Salmonid farming; Piscirickettsiosis; Epidemiology; Hydrodynamic connectivity; Seawater temperature; Salinity

资金

  1. Ministry of Economy, Development, and Tourism of Chile (Minecon) [FIEV014, FIE-201707240090]
  2. Association of the Chilean Salmon Industry AG (SalmonChile) [FIEV014, FIE-201707240090]

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Piscirickettsiosis is one of the most important diseases affecting farmed salmonid in Chile. Several studies have demonstrated the survival of Piscirickettsia salmonis in seawater and the horizontal transmission from infected to non-infected fish; however, the extent of waterborne transmission between farms has not been quantified. In this study, we used a stochastic hydrodynamic connectivity-based disease spread model to determine the role of hydrodynamic connectivity and the effect of seawater temperature and salinity on the dynamics of piscirickettsiosis in the Los Lagos region of Chile. Results demonstrate that environmental dynamics play a major role in disease prevalence. The strongest determinants of piscirickettsiosis prevalence were the number of infected farms in upstream waters and the extent of disease outbreaks in upstream waters (total mortality), followed by seawater salinity and temperature. In farms downstream from infected farms, observed disease prevalence 25 wk into the farming cycle was close to 100 %, while in farms with little or no exposure to upstream, infected farms, prevalence reached only -10 % by the end of the farming cycle (Week 56). No previous studies have quantified the scales of connectivity associated with piscirickettsiosis or provided risk metrics of waterborne transmission of the disease among farms; these are a novel aspect of this research. The above knowledge regarding the use of the epidemiological model will allow industry and regulators to better target disease control strategies for more effective control of piscirickettsiosis in the study area.

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