Pathogen Exclusion from Eco‐Epidemiological Systems

Abstract

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. Submitted February 12, 2010; Accepted April 6, 2010; Electronically published May 26, 2010 Online enhancements: appendixes.abstract: Increasing concerns about the changing environment and the emergence of pathogens that cross species boundaries have added to the urgency of understanding the dynamics of complex ecological systems infected by pathogens. Of particular interest is the often counterintuitive way in which infection and predation interact and the consequent difficulties in designing control strategies to manage the system. To understand the mechanisms involved, we focus on the pathogen exclusion problem, using control maps (on which the network of exclusion thresholds are plotted) in order to readily identify which exclusion strategies will work and why others will not. We apply this approach to the analysis of parasite exclusion in two game bird ecologies. For higher dimensions, we propose a computational scheme that will generate the optimal exclusion strategy, taking into account all operational constraints on the pathogen invasion matrix, populations, and controls. The situation is further complicated when external forcing distorts pathogen thresholds. This distortion is highly sensitive to the lags between forcing components, a sensitivity that can be exploited by management using correctly lagged cyclically varying controls to reduce the effort involved in pathogen exclusion.

Complex dynamics of a predator–prey–parasite system: An interplay among infection rate, predator's reproductive gain and preference

“…Since then literature in the field of predator-prey-parasite system has grown enormously in the last two and half decades and Chattopadhyay and Bairagi (2001), Xiao and Chen (2001), Venturino (2002), Packer et al (2003), Hethcote et al (2004), Hall et al (2005), Fenton and Rands (2006), Bairagi et al (2007Bairagi et al ( , 2009), Hsieh and Hsiao (2008), Siekmann et al (2010), Greenman and Hoyle (2010), Sieber and Hilker (2011) are just to name a few of such recent works. It is now well recognized that PPP models show more complicated and interesting dynamics than the traditional ecological or epidemiological models (Minchella and Scott, 1991).…”

The effect of predation on the prevalence and aggregation of pathogens in prey

“…Pathogen infection and predation are distinctive but analogous inter-specific interactions, with each an important field of research in its own right (Bairagi et al, 2007;Raffel et al, 2008;Mata-Machuca et al, 2010;Kihara et al, 2011). Eco-epidemiology that considers both ecological and epidemiological dynamics ties these two fields together and has attracted increasing attention (Chattopadhyay and Bariagi, 2001;Webb et al, 2007a;Bairagi et al, 2007;Su et al, 2009a;Greenman and Hoyle, 2010). Studies in ecoepidemiology have provided increasing insights to the complex dynamics in the system and their applications in conservation management, such as the biological control of problematic species using their natural enemies through the interplay of disease transmission and predation (Holt and Roy, 2007;Greenman and Hoyle, 2010).…”

Phase control of resonant systems: Interference, chaos and high periodicity

“…That this is a feasible approach has been shown in a range of realistic examples where substantial reduction in the effort involved in excluding a pathogen can be made [31], [32], [33]. These examples show that the concepts of reinforcement and interference and the use of phase as a control variable are just as important in solving the exclusion problem as they are the epidemic suppression problem.…”

“…These examples show that the concepts of reinforcement and interference and the use of phase as a control variable are just as important in solving the exclusion problem as they are the epidemic suppression problem. We hope to add to these numerical studies by using an analytic approach based on the rare invader approximation [33] to obtain general results for the exclusion of a species. In other recent work in this area [34], [35] much of the emphasis has been on mathematical rigour, constructing an R 0 threshold index under forcing for example, rather on the exclusion control problem in ecological models experiencing multi-component forcing.…”