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Global change, parasite transmission and disease control: lessons from ecology.

Joanne CableIain BarberBrian BoagAmy R EllisonEric R MorganKris MurrayEmily L PascoeSteven M SaitAnthony James WilsonMark Booth
Published in: Philosophical transactions of the Royal Society of London. Series B, Biological sciences (2017)
Parasitic infections are ubiquitous in wildlife, livestock and human populations, and healthy ecosystems are often parasite rich. Yet, their negative impacts can be extreme. Understanding how both anticipated and cryptic changes in a system might affect parasite transmission at an individual, local and global level is critical for sustainable control in humans and livestock. Here we highlight and synthesize evidence regarding potential effects of 'system changes' (both climatic and anthropogenic) on parasite transmission from wild host-parasite systems. Such information could inform more efficient and sustainable parasite control programmes in domestic animals or humans. Many examples from diverse terrestrial and aquatic natural systems show how abiotic and biotic factors affected by system changes can interact additively, multiplicatively or antagonistically to influence parasite transmission, including through altered habitat structure, biodiversity, host demographics and evolution. Despite this, few studies of managed systems explicitly consider these higher-order interactions, or the subsequent effects of parasite evolution, which can conceal or exaggerate measured impacts of control actions. We call for a more integrated approach to investigating transmission dynamics, which recognizes these complexities and makes use of new technologies for data capture and monitoring, and to support robust predictions of altered parasite dynamics in a rapidly changing world.This article is part of the themed issue 'Opening the black box: re-examining the ecology and evolution of parasite transmission'.
Keyphrases
  • plasmodium falciparum
  • toxoplasma gondii
  • trypanosoma cruzi
  • life cycle
  • climate change
  • endothelial cells
  • healthcare
  • risk assessment
  • machine learning
  • deep learning
  • electronic health record
  • social media