Host–parasite interactions between the local and the mean-field: How and when does spatial population structure matter?

Webb, Steven D.; Keeling, Matthew James; Boots, Mike

doi:10.1016/j.jtbi.2007.06.013

Cited by 48 publications

(50 citation statements)

References 47 publications

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“…The technique called pair approximation, which we will refer to as structure-based moment closure, provides ODEs which describe the changes over time in the probabilities of certain pairs (adjacent locations) in the model [91,66]. From these ODEs, the proportion of locations in a particular state can be determined.…”

Section: Pair Approximation: Spatial Moment Closure Based On Structurementioning

confidence: 99%

“…The reason this technique is called pair approximation is because one can consider the patterns of interest to be a graph consisting of two linked vertices, with the two vertices having specific states, and one wants to know how many times this pattern appears in the graph of the model. Much of the existing research assumes a finite grid/lattice [91,66], but one can also consider the more general case of arbitrary graphs rather than regular ones.…”

Section: Pair Approximation: Spatial Moment Closure Based On Structurementioning

confidence: 99%

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Spatial Representations and Analysis Techniques

Galpin

2016

Formal Methods for the Quantitative Evaluation of Collective Adaptive Systems

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Abstract. Space plays an important role in the dynamics of collective adaptive systems (CAS). There are choices between representations to be made when we model these systems with space included explicitly, rather than being abstracted away. Since CAS often involve a large number of agents or components, we focus on scalable modelling and analysis of these models, which may involve approximation techniques. Discrete and continuous space are considered, for both models of individuals and models of populations. The aim of this tutorial is to provide an overview that supports decisions in modelling systems that involve space.

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Section: Pair Approximation: Spatial Moment Closure Based On Structurementioning

confidence: 99%

Section: Pair Approximation: Spatial Moment Closure Based On Structurementioning

confidence: 99%

Spatial Representations and Analysis Techniques

Galpin

2016

Formal Methods for the Quantitative Evaluation of Collective Adaptive Systems

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“…Periodic boundaries were used (Su et al 2008b). Initially, host individuals (susceptible and infected) were located randomly in the suitable patches because equilibrium results in such models are not sensitive to initial conditions (Hiebeler and Morin 2007;Webb et al 2007a). For each combination of model parameters, five repeats were run and the results were presented as the mean and standard deviation for comparison.…”

Section: Mean-field Approximationmentioning

confidence: 99%

“…Scientists are increasingly interested in eco-epidemiological systems (Chattopadhyay and Bariagi 2001;Keeling et al 2001;Greenman et al 2004;Webb et al 2007a;Garrett et al 2007). Since Anderson and May's (1979) theoretical demonstration of the regulation strength of parasites towards their hosts, much attention has been paid to the impact of these parasites on host populations in natural systems (Boots and Sasaki 2001;Deredec and Courchamp 2006;Webb et al 2007aWebb et al , 2007b. As a result, an epidemiological theory of host-parasite systems has been developed (Anderson 1991;Sat" o et al 1994;Rand et al 1995;Webb et al 2007aWebb et al , 2007b, based largely on the classical mean-field SIR model (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Many methods have been used to study the spatial heterogeneity in ecological systems Okuyama 2007;Webb et al 2007aWebb et al , 2007bBolker and Pacala 1997;North and Ovaskainen 2007), among which the spatially stochastic simulation is often used (Hui and MeGeoch 2007;Webb et al 2007b;Okuyama 2007;Su et al 2008b). In particular, the role of spatially structured heterogeneity in the eco-epidemiological system has been examined successfully using this method (Hiebeler 2005;North and Ovaskainen 2007;Melbourne et al 2007).…”

Section: Introductionmentioning

confidence: 99%

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The effect of landscape heterogeneity on host–parasite dynamics

et al. 2008

Ecological Research

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Environmental heterogeneity has been shown to have a profound effect on population dynamics and biological invasions, yet the effect of its spatial structure on the dynamics of disease invasion in a spatial hostparasite system has received little attention. Here we explore the effect of environment heterogeneity using the pair approximation and the stochastic spatially explicit simulation in which the lost patches are clustered in a fragmented landscape. The intensity of fragmentation is defined by the amount and spatial autocorrelation of the lost habitat. More fragmented landscape (high amount of habitat loss, low clustering of lost patches) was shown to be detrimental to the parasitic disease invasion and transmission, which implies that the potential of using artificial disturbances as a disease-control agency in biological conservation and management. Two components of the spatial heterogeneity (the amount and spatial autocorrelation of the lost habitat) formed a trade-off in determining the host-parasite dynamics. An extremely high degree of habitat loss was, counter-intuitively, harmful to the host. These results enrich our understanding of eco-epidemiological, host-parasite systems, and suggest the possibility of using the spatial arrangement of habitat patches as a conservation tool for guarding focal species against parasitic infection and transmission.

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Population structure, intergroup interaction, and human contact govern infectious disease impacts in mountain gorilla populations

Whittier

Nutter

Johnson

et al. 2021

American J Primatol

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Infectious zoonotic diseases are a threat to wildlife conservation and global health. They are especially a concern for wild apes, which are vulnerable to many human infectious diseases. As ecotourism, deforestation, and great ape field research increase, the threat of human‐sourced infections to wild populations becomes more substantial and could result in devastating population declines. The endangered mountain gorillas (Gorilla beringei beringei) of the Virunga Massif in east‐central Africa suffer periodic disease outbreaks and are exposed to infections from human‐sourced pathogens. It is important to understand the possible risks of disease introduction and spread in this population and how human contact may facilitate disease transmission. Here we present and evaluate an individual‐based, stochastic, discrete‐time disease transmission model to predict epidemic outcomes and better understand health risks to the Virunga mountain gorilla population. To model disease transmission we have derived estimates for gorilla contact, interaction, and migration rates. The model shows that the social structure of gorilla populations plays a profound role in governing disease impacts with subdivided populations experiencing less than 25% of the outbreak levels of a single homogeneous population. It predicts that gorilla group dispersal and limited group interactions are strong factors in preventing widespread population‐level outbreaks of infectious disease after such diseases have been introduced into the population. However, even a moderate amount of human contact increases disease spread and can lead to population‐level outbreaks.

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Host–parasite interactions between the local and the mean-field: How and when does spatial population structure matter?

Cited by 48 publications

References 47 publications

Spatial Representations and Analysis Techniques

Spatial Representations and Analysis Techniques

The effect of landscape heterogeneity on host–parasite dynamics

Population structure, intergroup interaction, and human contact govern infectious disease impacts in mountain gorilla populations

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