2004
DOI: 10.1073/pnas.0405682101
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Emergent trade-offs and selection for outbreak frequency in spatial epidemics

Abstract: Nonspatial theory on pathogen evolution generally predicts selection for maximal number of secondary infections, constrained only by supposed physiological trade-offs between pathogen infectiousness and virulence. Spread of diseases in human populations can, however, exhibit large scale patterns, underlining the need for spatially explicit approaches to pathogen evolution. Here, we show, in a spatial model where all pathogen traits are allowed to evolve independently, that evolutionary trajectories follow a si… Show more

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Cited by 82 publications
(136 citation statements)
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“…Evolutionary bi-stability has been previously reported in spatial host parasite models (Read & Keeling, 2003;Boots et al, 2004;van Ballegooijen & Boerlijst, 2004).…”
mentioning
confidence: 72%
“…Evolutionary bi-stability has been previously reported in spatial host parasite models (Read & Keeling, 2003;Boots et al, 2004;van Ballegooijen & Boerlijst, 2004).…”
mentioning
confidence: 72%
“…These studies have shed new light onto key research issues in spatial epidemic dynamics, but the detailed theoretical studies are difficult. The study of population dynamics takes into account the species distribution in space, interactions between individual species that are located in the same neighborhood, and mobility of the various species [15,16,17]. These studies predict the formation of spatial complex structure, phase transitions, multistability, oscillatory regions, etc.…”
Section: Introductionmentioning
confidence: 99%
“…In the Ref. [17], the author studies the susceptible-infectedresistant-susceptible (SIRS) models with spatial structure using cellular automata rules, showing the formation process of the spatial patterns (turbulent waves and stable spiral waves) in the two-dimensional space and existence of stable spiral waves in the SIRS model.…”
Section: Introductionmentioning
confidence: 99%
“…Unconstrained evolution will eventually lead to strains with both high transmission rates and long infectious periods irrespective of the risk groups involved. However, if, as suggested, a trade-off between transmission and infectious period exists (Bremermann and Thieme 1989;Frank 1996;Boots and Sasaki 1999;van Ballegooijen and Boerlijst 2004) such that diseases are constrained to lie within certain regions of parameter space, then evolutionary pressures can lead to the divergence of strains and ultimately to the long-term coexistence of different strains specialized within particular risk groups. To investigate this scenario, we assume a trade-off between recovery/treatment rate, g, and transmission rate, t, of the form , with c g p a ϩ bt the constraints that and (van Baalen 2002): a, b 1 0 c 1 1 under this assumption, more easily transmitted strains are shorter lasting, and an enhanced immune response or more vigorous treatment efforts lead to a nonlinear relationship.…”
Section: Specializationmentioning
confidence: 99%