A spatial simulation model for dengue virus infection in urban areas

Karl, Stephan, Halder, Nilimesh, Kelso, Joel K., Ritchie, Scott A., and Milne, George J. (2014) A spatial simulation model for dengue virus infection in urban areas. BMC Infectious Diseases, 14. 447. pp. 1-17.

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Abstract

Background: The World Health Organization estimates that the global number of dengue infections range between 80–100 million per year, with some studies estimating approximately three times higher numbers. Furthermore, the geographic range of dengue virus transmission is extending with the disease now occurring more frequently in areas such as southern Europe. Ae. aegypti, one of the most prominent dengue vectors, is endemic to the far north-east of Australia and the city of Cairns frequently experiences dengue outbreaks which sometimes lead to large epidemics.

Method: A spatially-explicit, individual-based mathematical model that accounts for the spread of dengue infection as a result of human movement and mosquito dispersion is presented. The model closely couples the four key sub-models necessary for representing the overall dynamics of the physical system, namely those describing mosquito population dynamics, human movement, virus transmission and vector control. Important features are the use of high quality outbreak data and mosquito trapping data for calibration and validation and a strategy to derive local mosquito abundance based on vegetation coverage and census data.

Results: The model has been calibrated using detailed 2003 dengue outbreak data from Cairns, together with census and mosquito trapping data, and is shown to realistically reproduce a further dengue outbreak. The simulation results replicating the 2008/2009 Cairns epidemic support several hypotheses (formulated previously) aimed at explaining the large-scale epidemic which occurred in 2008/2009; specifically, while warmer weather and increased human movement had only a small effect on the spread of the virus, a shorter virus strain-specific extrinsic incubation time can explain the observed explosive outbreak of 2008/2009.

Conclusion: The proof-of-concept simulation model described in this study has potential as a tool for understanding factors contributing to dengue spread as well as planning and optimizing dengue control, including reducing the Ae. aegypti vector population and for estimating the effectiveness and cost-effectiveness of future vaccination programmes. This model could also be applied to other vector borne viral diseases such as chikungunya, also spread by Ae. aegypti and, by re-parameterisation of the vector sub-model, to dengue and chikungunya viruses spread by Aedes albopictus.

Item ID: 35990
Item Type: Article (Research - C1)
ISSN: 1471-2334
Keywords: dengue virus, individual-based simulation model, Ae. aegypti population dynamics, spatially-explicit modelling, dengue outbreaks, dengue control measures
Additional Information:

© 2014 Karl et al.; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Funders: University of Western Australia
Date Deposited: 27 Nov 2014 04:34
FoR Codes: 11 MEDICAL AND HEALTH SCIENCES > 1108 Medical Microbiology > 110899 Medical Microbiology not elsewhere classified @ 50%
11 MEDICAL AND HEALTH SCIENCES > 1108 Medical Microbiology > 110804 Medical Virology @ 50%
SEO Codes: 92 HEALTH > 9204 Public Health (excl. Specific Population Health) > 920404 Disease Distribution and Transmission (incl. Surveillance and Response) @ 100%
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