This book focuses on the modelling of contemporary health and social problems, especially those considered a major burden to communities, governments and taxpayers, such as smoking, alcoholism, drug use, and heart disease. Based on a series of papers presented at a recent conference hosted by the Leverhulme-funded Tipping Points project at the University of Durham, this book illustrates a broad range of modelling approaches. Such a diverse collection demonstrates that an interdisciplinary approach is essential to modelling tipping points in health and social problems, and the assessment of associated risk and resilience.
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Yes, you can access Tipping Points by John Bissell, Camila Caiado, Sarah Curtis, Michael Goldstein, Brian Straughan, John Bissell,Camila Caiado,Sarah Curtis,Michael Goldstein,Brian Straughan in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.
Chapter 1 Generalised Compartmental Modelling of Health Epidemics
J. J. Bissell
Department of Mathematical Sciences, University of Durham, Durham, United Kingdom
Abstract
Compartmental methods adapted from epidemiology offer an intuitive and potentially useful approach to modelling the spread of socially determined behaviours, including those related to health issues. Indeed, recruitment effects similar to those which drive epidemic infection, such as the tendency for individuals to mimic the behaviour of those around them, or to enforce social conformity via coercion, are expected to play an important role in such systems. Here we describe a generalised compartmental model for such âbehaviour transmissionâ, which we formulate in the context of societal smoking dynamics. By explicitly accounting for multiple peer recruitment terms for driving rates of both uptake and cessation, we find that behavioural transmission models can exhibit bistability, non-linear âtippingâ and hysteresis. These features may be of interest to health practitioners, because it would appear (in principle) that small changes to system parameters can lead to dramatic social change.
1.1 Introduction
The notion that âinfectiousâ ideas (e.g. âbuzz-wordsâ) or behavioural patterns might spread through society in a manner analogous to the transmission of disease is both appealing and intuitive, especially given the human tendency for imitation and coercion. Indeed, recent years have seen several mathematical studies devoted to this kind of behavioural âepidemiologyâ, particularly in the contexts of those behaviours considered addictive or undesirable (such as cigarette smoking), and so relevant to both social issues and health (GonzĂĄlez et al. 2003; Mulone and Straughan 2009, 2012; Samanta 2011; Sharomi and Gumel 2008; White and Comiskey 2007). Typically, such approaches begin by dividing a total population of
individuals into several sub-classes (each exhibiting different behavioural practices) analogous to the susceptible (S), infective (I), and recovered (R) sub-populations of SIR epidemic models (Murray 2002). By allowing individuals to transfer from one class following contact with (or ârecruitmentâ by) individuals from another, the emergence of behavioural norms may then be determined by examining how the size of each class changes with time. In terms of specifying rules for class transfer, such models of collective human behaviour can be constructed relatively simply by using systems of coupled ordinary differential equations; however, the systems themselves often display a variety of emergent features which can differ widely depending on model details (Bissell et al. 2014).
I...
Table of contents
Cover
Title Page
Wiley Series in Computational and Quantitative Social Science
