Breaking beta: deconstructing the parasite transmission function

McCallum, Hamish, Fenton, Andy, Hudson, Peter J., Lee, Brian, Levick, Beth, Norman, Rachel, Perkins, Sarah E. ORCID: https://orcid.org/0000-0002-7457-2699, Viney, Mark, Wilson, Anthony J. and Lello, Joanne ORCID: https://orcid.org/0000-0002-2640-1027 2017. Breaking beta: deconstructing the parasite transmission function. Philosophical Transactions B: Biological Sciences 372 (1719) , 20160084. 10.1098/rstb.2016.0084

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Abstract

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 b. 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 b 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. This article is part of the themed issue ‘Opening the black box: re-examining the ecology and evolution of parasite transmission’.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Biosciences
Subjects:	Q Science > Q Science (General)
Uncontrolled Keywords:	infection, infectious disease, modelling, nonlinearities, heterogeneity, transmission function
Additional Information:	Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
Publisher:	Royal Society, The
ISSN:	0962-8436
Date of First Compliant Deposit:	3 February 2017
Date of Acceptance:	22 December 2016
Last Modified:	04 May 2023 19:38
URI:	https://orca.cardiff.ac.uk/id/eprint/98038

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