Detecting and quantifying parasite-induced host mortality from intensity data: method comparisons and limitations

Int J Parasitol. 2016 Jan;46(1):59-66. doi: 10.1016/j.ijpara.2015.08.009. Epub 2015 Oct 16.

Abstract

Parasites can significantly impact animal populations by changing host behaviour, reproduction and survival. Detecting and quantifying these impacts is critical for understanding disease dynamics and managing wild animal populations. However, for wild hosts infected with macroparasites, it is notoriously difficult to quantify the fatal parasite load and number of animals that have died due to disease. When ethical or logistical constraints prohibit experimental determination of these values, examination of parasite intensity and distribution data may offer an alternative solution. In this study we introduce a novel method for using intensity data to detect and quantify parasite-induced mortality in wildlife populations. We use simulations to show that this method is more reliable than previously proposed methods while providing quantitative estimates of parasite-induced mortality from empirical data that are consistent with previously published qualitative estimates. However this method, and all techniques that estimate parasite-induced mortality from intensity data alone, have several important assumptions that must be scrutinised before applying those to real-world data. Given that these assumptions are met, our method is a new exploratory tool that can help inform more rigorous studies of parasite-induced host mortality.

Keywords: Crofton Method; Host survival function; Lethal dose; Negative binomial distribution; Parasite aggregation.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animal Population Groups
  • Animals
  • Animals, Wild / parasitology
  • Behavior, Animal
  • Binomial Distribution
  • Computer Simulation
  • Host-Parasite Interactions*
  • Lethal Dose 50
  • Likelihood Functions
  • Models, Statistical*
  • Parasites / pathogenicity*
  • Parasitic Diseases, Animal / mortality*
  • Parasitic Diseases, Animal / parasitology
  • Reproduction
  • Statistics as Topic / methods
  • Survival Rate