title: The temporal patterns of disease severity and prevalence in schistosomiasis.
abstract: Schistosomiasis is one of the most widespread public health problems in the world. In this work, we introduce an eco-epidemiological model for its transmission and dynamics with the purpose of explaining both intra- and inter-annual fluctuations of disease severity and prevalence. The model takes the form of a system of nonlinear differential equations that incorporate biological complexity associated with schistosome's life cycle, including a prepatent period in snails (i.e., the time between initial infection and onset of infectiousness). Nonlinear analysis is used to explore the parametric conditions that produce different temporal patterns (stationary, endemic, periodic, and chaotic). For the time-invariant model, we identify a transcritical and a Hopf bifurcation in the space of the human and snail infection parameters. The first corresponds to the occurrence of an endemic equilibrium, while the latter marks the transition to interannual periodic oscillations. We then investigate a more realistic time-varying model in which fertility of the intermediate host population is assumed to seasonally vary. We show that seasonality can give rise to a cascade of period-doubling bifurcations leading to chaos for larger, though realistic, values of the amplitude of the seasonal variation of fertility.
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via Ponzio 34/5, 20133 Milano, Italy.
authors.forename: Manuela
authors.initials: M
authors.lastname: Ciddio
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via Ponzio 34/5, 20133 Milano, Italy.
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Mari
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via Ponzio 34/5, 20133 Milano, Italy.
authors.forename: Marino
authors.initials: M
authors.lastname: Gatto
authors.affiliation: Laboratory of Ecohydrology, ECHO/IIE/ENAC, École Polytechnique Fédérale de Lausanne, Station 2, 1015 Lausanne, Switzerland.
authors.forename: Andrea
authors.initials: A
authors.lastname: Rinaldo
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via Ponzio 34/5, 20133 Milano, Italy.
authors.forename: Renato
authors.initials: R
authors.lastname: Casagrandi
mesh_terms: D003198:Computer Simulation; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D006801:Humans; D017711:Nonlinear Dynamics; D009991:Oscillometry / Q000379:methods*; D015995:Prevalence; D018570:Risk Assessment / Q000379:methods; D012552:Schistosomiasis / Q000453:epidemiology*; D012720:Severity of Illness Index; D062211:Spatio-Temporal Analysis