Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/15409
Title: A simple periodic-forced model for dengue fitted to incidence data in Singapore
Authors: Andraud, Mathieu
HENS, Niel 
Beutels, Philippe
Issue Date: 2013
Publisher: ELSEVIER SCIENCE INC
Source: MATHEMATICAL BIOSCIENCES, 244 (1), p. 22-28
Abstract: Dengue is the world's major arbovirosis and therefore an important public health concern in endemic areas, The availability of weekly reports of dengue cases in Singapore offers the opportunity to analyze the transmission dynamics and the impact of vector control strategies. Based on a previous model studying the impact of vector control strategies in Singapore during the 2005 outbreak, a simple vector-host model accounting for seasonal fluctuation in vector density was developed to estimate the parameters governing the vector population dynamics using dengue fever incidence data from August 2003 to December 2007. The impact of vector control, which consisted principally of a systematic removal of actual and potential breeding sites during a six-week period in 2005, was also investigated. Although our approach does not account for the complex life cycle of the vector, the good fit between data and model outputs showed that the impact of seasonality on the transmission dynamics is highly important. Moreover, the periodic fluctuations of the vector population were found in phase with temperature variations, suggesting a strong climate effect on the vector density and, in turn, on the transmission dynamics. (c) 2013 Elsevier Inc. All rights reserved.
Notes: Andraud, M (reprint author), Univ Antwerp, Vaccine & Infect Dis Inst VAXINFECTIO, Ctr Hlth Econ Res & Modelling Infect Dis, B-2610 Antwerp, Belgium. Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, Diepenbeek, Belgium. Univ New S Wales, Sch Publ Hlth & Community Med, Sydney, NSW 2052, Australia. mathieu.andraud@ua.ac.be
Keywords: Arbovirus; Epidemiological model; Vector-host transmission; Vector-control; Model fit; Seasonality;Biology; Mathematical & Computational Biology
Document URI: http://hdl.handle.net/1942/15409
ISSN: 0025-5564
e-ISSN: 1879-3134
DOI: 10.1016/j.mbs.2013.04.001
ISI #: 000320747800003
Category: A1
Type: Journal Contribution
Validations: ecoom 2014
Appears in Collections:Research publications

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