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From the same journal

Modelling cetacean morbillivirus outbreaks in an endangered killer whale population

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Author(s)

  • Michael N. Weiss
  • Daniel W. Franks
  • Kenneth C. Balcomb
  • David K. Ellifrit
  • Matthew J. Silk
  • Michael A. Cant
  • Darren P. Croft

Department/unit(s)

Publication details

JournalBiological Conservation
DateAccepted/In press - 23 Dec 2019
DateE-pub ahead of print - 24 Jan 2020
DatePublished (current) - 1 Feb 2020
Volume242
Number of pages10
Early online date24/01/20
Original languageEnglish

Abstract

The emergence of novel diseases represents a major hurdle for the recovery of endangered populations, and in some cases may even present the threat of extinction. In recent years, epizootics of infectious diseases have emerged as a major threat to marine mammal populations, particularly group-living odontocetes. However, little research has explored the potential consequences of novel pathogens in endangered cetacean populations. Here, we present the first study predicting the spread of infectious disease over the social network of an entire free-ranging cetacean population, the southern resident killer whale community (SRKW). Utilizing 5 years of detailed data on close contacts between individuals, we build a fine-scale social network describing potential transmission pathways in this population. We then simulate the spread of cetacean morbillivirus (CeMV) over this network. Our analysis suggests that the SRKW population is highly vulnerable to CeMV. The majority of simulations resulted in unusual mortality events (UMEs), with mortality rates predicted to be at least twice the recorded maximum annual mortality. We find only limited evidence that this population's social structure inhibits disease spread. Vaccination is not likely to be an efficient strategy for reducing the likelihood of UMEs, with over 40 vaccinated individuals (>50% of the population) required to reduce the likelihood of UMEs below 5%. This analysis highlights the importance of modelling efforts in designing strategies to mitigate disease, and suggests that populations with strong social preferences and distinct social units may still be highly vulnerable to disease outbreaks.

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© 2020 Elsevier Ltd. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy.

    Research areas

  • Epidemic modelling, Orcinus orca, Social network, SRKW, Vaccination

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