The effect of Wolbachia on dengue dynamics in the presence of two serotypes of dengue: symmetric and asymmetric epidemiological characteristics

Ndii, M.Z., Allingham, D., Hickson, R., and Glass, K. (2016) The effect of Wolbachia on dengue dynamics in the presence of two serotypes of dengue: symmetric and asymmetric epidemiological characteristics. Epidemiology and Infection, 144 (13). pp. 2874-2882.

[img] PDF (Published Version) - Published Version
Restricted to Repository staff only

View at Publisher Website: https://doi.org/10.1017/S095026881600075...
 
1


Abstract

An innovative strategy to reduce dengue transmission uses the bacterium Wolbachia. We analysed the effects of Wolbachia on dengue transmission dynamics in the presence of two serotypes of dengue using a mathematical model, allowing for differences in the epidemiological characteristics of the serotypes. We found that Wolbachia has a greater effect on secondary infections than on primary infections across a range of epidemiological characteristics. If one serotype is more transmissible than the other, it will dominate primary infections and Wolbachia will be less effective at reducing secondary infections of either serotype. Differences in the antibody-dependent enhancement of the two serotypes have considerably less effect on the benefits of Wolbachia than differences in transmission probability. Even if the antibody-dependent enhancement rate is high, Wolbachia is still effective in reducing dengue. Our findings suggest that Wolbachia will be effective in the presence of more than one serotype of dengue; however, a better understanding of serotype-specific differences in transmission probability may be needed to optimize delivery of a Wolbachia intervention.

Item ID: 64033
Item Type: Article (Research - C1)
ISSN: 1469-4409
Keywords: Dengue, mathematical model, multiple serotypes, reduction, Wolbachia
Copyright Information: © Cambridge University Press 2016
Funders: University of Newcastle
Date Deposited: 13 Aug 2020 03:52
FoR Codes: 01 MATHEMATICAL SCIENCES > 0102 Applied Mathematics > 010202 Biological Mathematics @ 34%
11 MEDICAL AND HEALTH SCIENCES > 1117 Public Health and Health Services > 111706 Epidemiology @ 33%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080110 Simulation and Modelling @ 33%
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%
Downloads: Total: 1
Last 12 Months: 1
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page