Breaking beta: deconstructing the parasite transmission function

Hamish McCallum*, Andy Fenton, Peter J. Hudson, Brian Lee, Beth Levick, Rachel Norman, Sarah E Perkins, Mark Viney, Anthony J. Wilson, Joanne Lello

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

70 Citations (Scopus)
312 Downloads (Pure)


Transmission is a fundamental step in the life cycle of every parasite but it is also one of the most challenging processes to model and quantify. In most host–parasite models, the transmission process is encapsulated by a single parameter β. Many different biological processes and interactions, acting on both hosts and infectious organisms, are subsumed in this single term. There are, however, at least two undesirable consequences of this high level of abstraction. First, nonlinearities and heterogeneities that can be critical to the dynamic behaviour of infections are poorly represented; second, estimating the transmission coefficient β from field data is often very difficult. In this paper, we present a conceptual model, which breaks the transmission process into its component parts. This deconstruction enables us to identify circumstances that generate nonlinearities in transmission, with potential implications for emergent transmission behaviour at individual and population scales. Such behaviour cannot be explained by the traditional linear transmission frameworks. The deconstruction also provides a clearer link to the empirical estimation of key components of transmission and enables the construction of flexible models that produce a unified understanding of the spread of both micro- and macro-parasite infectious disease agents.
Original languageEnglish
Article number20160084
Number of pages11
JournalPhilosophical Transactions B: Biological Sciences
Issue number1719
Early online date13 Mar 2017
Publication statusPublished - 5 May 2017

Bibliographical note

Special issue: Opening the black box: re-examining the ecology and evolution of parasite transmission


  • infection
  • infectious disease
  • modelling
  • nonlinearities
  • heterogeneity
  • transmission function


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