The exclusion problem in seasonally forced epidemiological systems. (21st February 2015)

• Record Type: Journal Article
• Authors: Greenman, J.V.; Adams, B.
• Is Part Of: Journal of theoretical biology. Volume 367(2015)
• Page Start: 49
• Page End: 60
• Publication Date: 2015-02-21
• Subjects: Phase control -- Optimal scheduling -- Basic reproduction number R0 -- Reservoir of infection -- Resonance; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2014.11.011
• Languages: English
• ISSNs: 0022-5193

Abstract

Abstract: The pathogen exclusion problem is the problem of finding control measures that will exclude a pathogen from an ecological system or, if the system is already disease-free, maintain it in that state. To solve this problem we work within a holistic control theory framework which is consistent with conventional theory for simple systems (where there is no external forcing and constant controls) and seamlessly generalises to complex systems that are subject to multiple component seasonal forcing and targeted variable controls. We develop, customise and integrate a range of numerical and algebraic procedures that provide a coherent methodology powerful enough to solve the exclusion problem in the general case. An important aspect of our solution procedure is its two-stage structure which reveals the epidemiological consequences of the controls used for exclusion. This information augments technical and economic considerations in the design of an acceptable exclusion strategy. Our methodology is used in two examples to show how time-varying controls can exploit the interference and reinforcement created by the external and internal lag structure and encourage the system to 'take over' some of the exclusion effort. On–off control switching, resonant amplification, optimality and controllability are important issues that emerge in the discussion. Highlights: New holistic control approach helps solve the pathogen exclusion problem. Results inform design of exclusion strategies in complex forced conditions. New method for solving the highly unstable optimal exclusion problem. New method to find R_0 analytically under multi-component forcing. Investigation of epidemiological conditions using 2-stage control analysis.