Deploying dengue-suppressing Wolbachia: Robust models predict slow but effective spatial spread in Aedes aegypti

M. Turelli, N.H. Barton, Theoretical Population Biology 115 (2017) 45–60.

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Journal Article | Published | English
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Abstract
A novel strategy for controlling the spread of arboviral diseases such as dengue, Zika and chikungunya is to transform mosquito populations with virus-suppressing Wolbachia. In general, Wolbachia transinfected into mosquitoes induce fitness costs through lower viability or fecundity. These maternally inherited bacteria also produce a frequency-dependent advantage for infected females by inducing cytoplasmic incompatibility (CI), which kills the embryos produced by uninfected females mated to infected males. These competing effects, a frequency-dependent advantage and frequency-independent costs, produce bistable Wolbachia frequency dynamics. Above a threshold frequency, denoted pˆ, CI drives fitness-decreasing Wolbachia transinfections through local populations; but below pˆ, infection frequencies tend to decline to zero. If pˆ is not too high, CI also drives spatial spread once infections become established over sufficiently large areas. We illustrate how simple models provide testable predictions concerning the spatial and temporal dynamics of Wolbachia introductions, focusing on rate of spatial spread, the shape of spreading waves, and the conditions for initiating spread from local introductions. First, we consider the robustness of diffusion-based predictions to incorporating two important features of wMel-Aedes aegypti biology that may be inconsistent with the diffusion approximations, namely fast local dynamics induced by complete CI (i.e., all embryos produced from incompatible crosses die) and long-tailed, non-Gaussian dispersal. With complete CI, our numerical analyses show that long-tailed dispersal changes wave-width predictions only slightly; but it can significantly reduce wave speed relative to the diffusion prediction; it also allows smaller local introductions to initiate spatial spread. Second, we use approximations for pˆ and dispersal distances to predict the outcome of 2013 releases of wMel-infected Aedes aegypti in Cairns, Australia, Third, we describe new data from Ae. aegypti populations near Cairns, Australia that demonstrate long-distance dispersal and provide an approximate lower bound on pˆ for wMel in northeastern Australia. Finally, we apply our analyses to produce operational guidelines for efficient transformation of vector populations over large areas. We demonstrate that even very slow spatial spread, on the order of 10-20 m/month (as predicted), can produce area-wide population transformation within a few years following initial releases covering about 20-30% of the target area.
Publishing Year
Date Published
2017-06-01
Journal Title
Theoretical Population Biology
Volume
115
Page
45 - 60
ISSN
IST-REx-ID

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Turelli M, Barton NH. Deploying dengue-suppressing Wolbachia: Robust models predict slow but effective spatial spread in Aedes aegypti. Theoretical Population Biology. 2017;115:45-60. doi:10.1016/j.tpb.2017.03.003
Turelli, M., & Barton, N. H. (2017). Deploying dengue-suppressing Wolbachia: Robust models predict slow but effective spatial spread in Aedes aegypti. Theoretical Population Biology, 115, 45–60. https://doi.org/10.1016/j.tpb.2017.03.003
Turelli, Michael, and Nicholas H Barton. “Deploying Dengue-Suppressing Wolbachia: Robust Models Predict Slow but Effective Spatial Spread in Aedes Aegypti.” Theoretical Population Biology 115 (2017): 45–60. https://doi.org/10.1016/j.tpb.2017.03.003.
M. Turelli and N. H. Barton, “Deploying dengue-suppressing Wolbachia: Robust models predict slow but effective spatial spread in Aedes aegypti,” Theoretical Population Biology, vol. 115, pp. 45–60, 2017.
Turelli M, Barton NH. 2017. Deploying dengue-suppressing Wolbachia: Robust models predict slow but effective spatial spread in Aedes aegypti. Theoretical Population Biology. 115, 45–60.
Turelli, Michael, and Nicholas H. Barton. “Deploying Dengue-Suppressing Wolbachia: Robust Models Predict Slow but Effective Spatial Spread in Aedes Aegypti.” Theoretical Population Biology, vol. 115, Elsevier, 2017, pp. 45–60, doi:10.1016/j.tpb.2017.03.003.
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