title: Endogenous quasicycles and stochastic coherence in a closed endemic model.
abstract: We study the role of demographic fluctuations in typical endemics as exemplified by the stochastic SIRS model. The birth-death master equation of the model is simulated using exact numerics and analyzed within the linear noise approximation. The endemic fixed point is unstable to internal demographic noise, and leads to sustained oscillations. This is ensured when the eigenvalues (λ) of the linearized drift matrix are complex, which in turn, is possible only if detailed balance is violated. In the oscillatory state, the phases decorrelate asymptotically, distinguishing such oscillations from those produced by external periodic forcing. These so-called quasicycles are of sufficient strength to be detected reliably only when the ratio |Im(λ)/Re(λ)| is of order unity. The coherence or regularity of these oscillations show a maximum as a function of population size, an effect known variously as stochastic coherence or coherence resonance. We find that stochastic coherence can be simply understood as resulting from a nonmonotonic variation of |Im(λ)/Re(λ)| with population size. Thus, within the linear noise approximation, stochastic coherence can be predicted from a purely deterministic analysis. The non-normality of the linearized drift matrix, associated with the violation of detailed balance, leads to enhanced fluctuations in the population amplitudes.
authors.affiliation: The Institute of Mathematical Sciences, Tharamani, Chennai, India. somdeb@imsc.res.in
authors.forename: Somdeb
authors.initials: S
authors.lastname: Ghose
authors.forename: R
authors.initials: R
authors.lastname: Adhikari
mesh_terms: D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D019353:Endemic Diseases / Q000706:statistics & numerical data*; D058872:Epidemics / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D009991:Oscillometry / Q000379:methods*; D015995:Prevalence; D013269:Stochastic Processes