Epidemiological models with non-exponentially distributed disease stages and applications to disease control

0Citations
Citations of this article
68Readers
Mendeley users who have this article in their library.

This artice is free to access.

Abstract

SEIR epidemiological models with the inclusion of quarantine and isolation are used to study the control and intervention of infectious diseases. A simple ordinary differential equation (ODE) model that assumes exponential distribution for the latent and infectious stages is shown to be inadequate for assessing disease control strategies. By assuming arbitrarily distributed disease stages, a general integral equation model is developed, of which the simple ODE model is a special case. Analysis of the general model shows that the qualitative disease dynamics are determined by the reproductive number Rc, which is a function of control measures. The integral equation model is shown to reduce to an ODE model when the disease stages are assumed to have a gamma distribution, which is more realistic than the exponential distribution. Outcomes of these models are compared regarding the effectiveness of various intervention policies. Numerical simulations suggest that models that assume exponential and non-exponential stage distribution assumptions can produce inconsistent predictions. © 2007 Springer Science+Business Media, Inc.

Cite

CITATION STYLE

APA

Feng, Z., Xu, D., & Zhao, H. (2007). Epidemiological models with non-exponentially distributed disease stages and applications to disease control. Bulletin of Mathematical Biology, 69(5), 1511–1536. https://doi.org/10.1007/s11538-006-9174-9

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free