Solution of epidemic models with quenched transients.

We consider a model for single-season disease epidemics, with a delay (latent period) in the onset of infectivity and a decay ("quenching") in host susceptibility described by time-varying rates of primary and secondary infections. The classical susceptible-exposed-infected (SEI) model of epidemiology is a special case with constant rates. The decaying rates force the epidemics to slow down, and eventually stop in a "quenched transient" state that depends on the full history of the epidemic including its initial state. This equilibrium state is neutrally stable (i.e., has zero-value eigenvalues), and cannot be studied using standard equilibrium analysis. We introduce a method that gives an approximate analytical solution for the quenched state. The method uses an interpolation between two exactly solvable limits and applies to the whole, five-dimensional parameter space of the model. Some applications of the solutions for analysis of epidemics are given.

[1]  P. Grassberger On the critical behavior of the general epidemic process and dynamical percolation , 1983 .

[2]  J. K. Thomas,et al.  Various aspects of the constraints imposed on the photochemistry of systems in porous silica. , 2001, Advances in colloid and interface science.

[3]  N. Boccara,et al.  Automata network SIR models for the spread of infectious diseases in populations of moving individuals , 1992 .

[4]  G. J. Gibson,et al.  Comparing approximations to spatio-temporal models for epidemics with local spread , 2001, Bulletin of mathematical biology.

[5]  M. Newman,et al.  Scaling and percolation in the small-world network model. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[6]  Christopher A. Gilligan,et al.  An epidemiological framework for disease management , 2002 .

[7]  P. Chambré On the Solution of the Poisson‐Boltzmann Equation with Application to the Theory of Thermal Explosions , 1952 .

[8]  J. Filipe,et al.  Hybrid closure-approximation to epidemic models , 1999 .

[9]  G. R. Pickett,et al.  Laboratory simulation of cosmic string formation in the early Universe using superfluid 3He , 1996, Nature.

[10]  H. Hotta,et al.  Increased Induction of Apoptosis by a Sendai Virus Mutant Is Associated with Attenuation of Mouse Pathogenicity , 1998, Journal of Virology.

[11]  M. Däumling,et al.  Experimental and theoretical studies of oxygen ordering in quenched and slow-cooled YBa2Cu3O7-δ , 1992 .

[12]  G. Gibson,et al.  Predicting variability in biological control of a plant—pathogen system using stochastic models , 1999, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[13]  D. J. Bailey,et al.  Dynamically generated variability in plant-pathogen systems with biological control , 1996, Proceedings of the Royal Society of London. Series B: Biological Sciences.