A modeller's perspective on infection dynamics within and between hosts

Abstract

The goal of this case-series was to increase our understanding of some complex within and between-host infection dynamics through the creation of mathematical and computational models that are able to capture the existing host and/or parasite heterogeneity. This goal was reached through a series of research projects (regarding experimental autoimmune encephalomyelitis (EAE) in mice, Mycobacterium avium subspecies paratuberculosis infection in cattle, Eimeria acervulina infection in chicken and human malaria) that gradually build up in complexity of both the system modelled and the modelling techniques used. In this case-series, the vast majority of model components have a direct link with reality. The results have shown some detailed examples of the valuable contribution that models have in understanding infection processes. The most satisfying achievements have come from those models that were able to, in hindsight, make complicated experimental results seem obvious and logical, and where the process of building the model was as insightful as the final results. The models created in these projects help to explain a wide range of sometimes contradictory experimental results and are used to predict the effect of control measures. In addition, they generate ideas for the development of new methods of control.

Linked within-host and between-host models and data for infectious diseases: a systematic review

“…Thinking about the implications across scales is important but is also challenging as the relationships are often complex, nonlinear and, therefore, un-intuitive. Previously, theoretical models of multi-scale phenomena have been reviewed (Mideo, Alizon & Day, 2008; Reiner et al, 2013; Dorratoltaj et al, 2017; Murillo, Murillo & Perelson, 2013; Severins, 2012). Repeated themes of these works and others over the past two decades have included: the need for more data (Alizon & Van Baalen, 2008; Alizon, Luciani & Regoes, 2011; Handel & Rohani, 2015; Lavine, Poss & Grenfell, 2008; Pollitt et al, 2011); the challenge of integrating scales (Frost et al, 2015; Perelson et al, 1996; Handel & Rohani, 2015; Mideo et al, 2013); and the role of heterogeneity (Lavine, Poss & Grenfell, 2008; VanderWaal & Ezenwa, 2016).…”

Peer Review #1 of "Linked within-host and between-host models and data for infectious diseases: a systematic review (v0.1)"

“…Previously, theoretical models of multi-scale phenomena have been reviewed, e.g. (Mideo et al, 2008;Reiner et al, 2013;Dorratoltaj et al, 2017;Murillo et al, 2013;Severins, 2012). Repeated themes of these works and others over the past two decades have included: the need for more data (Alizon and Van Baalen, 2008;Alizon et al, 2011;Handel and Rohani, 2015;Lavine et al, 2008;Pollitt et al, 2011); the challenge of integrating scales (Frost et al, 2015;Perelson et al, 1996;Handel and Rohani, 2015;Mideo et al, 2013); and the role of heterogeneity (Lavine et al, 2008;VanderWaal and Ezenwa, 2016).…”

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“…Thinking about the implications across scales is important but is also challenging as the relationships are often complex, nonlinear and, therefore, unintuitive. Previously, theoretical models of multi-scale phenomena have been reviewed (Mideo et al, 2008;Reiner et al, 2013;Dorratoltaj et al, 2017;Murillo et al, 2013;Severins, 2012). In 2015, Handel and Rohani highlighted the need for a better incorporation of data into multi-scale models (Handel and Rohani, 2015).…”