Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/34130
Title: Simulation and Analysis Methods for Stochastic Compartmental Epidemic Models
Authors: GANYANI, Tapiwa 
FAES, Christel 
HENS, Niel 
Issue Date: 2021
Publisher: ANNUAL REVIEWS
Source: Annual Review of Statistics and Its Application, 8 (1) , p. 69 -88
Series/Report: Annual Review of Statistics and Its Application
Abstract: This article considers simulation and analysis of incidence data using stochastic compartmental models in well-mixed populations. Several simulation approaches are described and compared. Thereafter, we provide an overview of likelihood estimation for stochastic models. We apply one such method to a real-life outbreak data set and compare models assuming different kinds of stochasticity. We also give references for other publications where detailed information on this topic can be found.
Notes: Ganyani, T (corresponding author), Hasselt Univ, Data Sci Inst, I BioStat, B-3500 Hasselt, Belgium.
tapiwa.ganyani@uhasselt.be
Other: Ganyani, T (corresponding author), Hasselt Univ, Data Sci Inst, I BioStat, B-3500 Hasselt, Belgium. tapiwa.ganyani@uhasselt.be
Keywords: stochastic SIR model;stochasticity;simulation;estimation;epidemic modeling
Document URI: http://hdl.handle.net/1942/34130
ISSN: 2326-8298
e-ISSN: 2326-831X
DOI: 10.1146/annurev-statistics-061120-034438
ISI #: WOS:000627718500004
Category: A1
Type: Journal Contribution
Validations: ecoom 2022
Appears in Collections:Research publications

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