title: Network-level reproduction number and extinction threshold for vector-borne diseases.
abstract: The basic reproduction number of deterministic models is an essential quantity to predict whether an epidemic will spread or not. Thresholds for disease extinction contribute crucial knowledge of disease control, elimination, and mitigation of infectious diseases. Relationships between basic reproduction numbers of two deterministic network-based ordinary differential equation vector-host models, and extinction thresholds of corresponding stochastic continuous-time Markov chain models are derived under some assumptions. Numerical simulation results for malaria and Rift Valley fever transmission on heterogeneous networks are in agreement with analytical results without any assumptions, reinforcing that the relationships may always exist and proposing a mathematical problem for proving existence of the relationships in general. Moreover, numerical simulations show that the basic reproduction number does not monotonically increase or decrease with the extinction threshold. Consistent trends of extinction probability observed through numerical simulations provide novel insights into mitigation strategies to increase the disease extinction probability. Research findings may improve understandings of thresholds for disease persistence in order to control vector-borne diseases.
authors: Kansas State Epicenter, Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506, United States. lxue@ksu.edu.
authors: Ling
authors: L
authors: Xue
authors: Caterina
authors: C
authors: Scoglio
mesh_terms: D000818:Animals; D003198:Computer Simulation; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D004199:Disease Vectors; D006801:Humans; D015994:Incidence; D008288:Malaria / Q000453:epidemiology* / Q000635:transmission; D008962:Models, Theoretical; D012295:Rift Valley Fever / Q000453:epidemiology* / Q000635:transmission; D018570:Risk Assessment / Q000379:methods