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Download e-book for kindle: Adaptive Dynamics of Infectious Diseases: In Pursuit of by Ulf Dieckmann, Johan A. J. Metz, Maurice W. Sabelis, Karl

By Ulf Dieckmann, Johan A. J. Metz, Maurice W. Sabelis, Karl Sigmund

ISBN-10: 0511525729

ISBN-13: 9780511525728

ISBN-10: 0521022134

ISBN-13: 9780521022132

ISBN-10: 0521781655

ISBN-13: 9780521781657

This monograph takes inventory of our present wisdom at the evolutionary ecology of infectious ailments, and units out the targets for the administration of virulent pathogens. in the course of the textual content, the basic techniques and strategies underlying the types are rigorously defined in a distinct sequence of built-in bins.

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Additional resources for Adaptive Dynamics of Infectious Diseases: In Pursuit of Virulence Management

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6. 6. 6 therefore draw attention to the potential value of developing the model and obtaining more refined epidemiological data. 4 is cast in the context of waterborne transmission, yet its general form is applicable to other modes of transmission that are predicted to favor increased virulence. The model can, for example, be adjusted to sit-and-wait transmission simply by redefining some terms. In this case, ρ is the rate at which propagules are released into the terrestrial environment rather than 2 · Alternative Transmission Modes and the Evolution of Virulence 25 into the water, βW is the rate at which such pathogens are picked up by a susceptible host moving through that environment, and W is the density of pathogens in the terrestrial environment.

3) α + d + θ (α) To analyze the consequences of this functional dependence of R0 on α, numerical simulations were performed. The following values were chosen to generate coefficients that correspond at least roughly to real infectious diseases in humans: c0 = 1 000 and c1 = 100 year−2 . The constant c2 in the recovery rate θ (α) = c2 /α is set to 500 year−2 . The normal life span of hosts is set to 60 years so that d = 1/60 year−1 . To find the value of α that maximizes R0 , denoted by αmax , we solve for d R0 /dα = 0 2α 4 + dα 3 − c1 dα − 2c1 c2 d R0 = −c0 α 2 =0.

In other cases, mass mortality resulting from cyclic epidemics may be able to regulate host population dynamics more effectively than predation or intra- and interspecific competition. The evolution and spread of virulent pathogens is becoming a cause of great concern in the protection of threatened wildlife communities and ecosystems. Endangered species have small and potentially sparse populations, and, therefore, have a reduced ability to sustain continuous infections by virulent pathogens. However, endangered species can acquire these pathogens upon contact with more common and widespread species.

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Adaptive Dynamics of Infectious Diseases: In Pursuit of Virulence Management by Ulf Dieckmann, Johan A. J. Metz, Maurice W. Sabelis, Karl Sigmund


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