Modelling the transmission dynamics of dengue in the presence of Wolbachia

Ndii, Meksianis Z., Hickson, R.I., Allingham, David, and Mercer, G.N. (2015) Modelling the transmission dynamics of dengue in the presence of Wolbachia. Mathematical Biosciences, 262. pp. 157-166.

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Abstract

Use of the bacterium Wolbachia is an innovative new strategy designed to break the cycle of dengue transmission. There are two main mechanisms by which Wolbachia could achieve this: by reducing the level of dengue virus in the mosquito and/or by shortening the host mosquito's lifespan. However, although Wolbachia shortens the lifespan, it also gives a breeding advantage which results in complex population dynamics. This study focuses on the development of a mathematical model to quantify the effect on human dengue cases of introducing Wolbachia into the mosquito population. The model consists of a compartment-based system of first-order differential equations; seasonal forcing in the mosquito population is introduced through the adult mosquito death rate. The analysis focuses on a single dengue outbreak typical of a region with a strong seasonally-varying mosquito population. We found that a significant reduction in human dengue cases can be obtained provided that Wolbachia-carrying mosquitoes persist when competing with mosquitoes without Wolbachia. Furthermore, using the Wolbachia strain WMel reduces the mosquito lifespan by at most 10% and allows them to persist in competition with non-Wolbachia-carrying mosquitoes. Mosquitoes carrying the WMelPop strain, however, are not likely to persist as it reduces the mosquito lifespan by up to 50%. When all other effects of Wolbachia on the mosquito physiology are ignored, cytoplasmic incompatibility alone results in a reduction in the number of human dengue cases. A sensitivity analysis of the parameters in the model shows that the transmission probability, the biting rate and the average adult mosquito death rate are the most important parameters for the outcome of the cumulative proportion of human individuals infected with dengue.

Item ID: 64160
Item Type: Article (Research - C1)
ISSN: 1879-3134
Copyright Information: © 2015 Elsevier Inc. All rights reserved.
Additional Information:

The work of the first author is supported by a Ph.D. Scholarship from The University of Newcastle, Australia. MZN thanks Professor Irene Hudson for several meetings and discussions. This paper is dedicated to the late Professor Geoff Mercer (one of the authors), who passed away on 12 April 2014 when this manuscript was under revision. The authors thank Dr. Kathryn Glass for valuable assistance in revising the manuscript.

Funders: University of Newcastle (UoN)
Date Deposited: 25 Aug 2020 23:53
FoR Codes: 01 MATHEMATICAL SCIENCES > 0102 Applied Mathematics > 010202 Biological Mathematics @ 50%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080110 Simulation and Modelling @ 30%
11 MEDICAL AND HEALTH SCIENCES > 1117 Public Health and Health Services > 111706 Epidemiology @ 20%
SEO Codes: 92 HEALTH > 9204 Public Health (excl. Specific Population Health) > 920404 Disease Distribution and Transmission (incl. Surveillance and Response) @ 60%
97 EXPANDING KNOWLEDGE > 970101 Expanding Knowledge in the Mathematical Sciences @ 40%
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