Predicting Wolbachia invasion dynamics in Aedes aegypti populations using models of density-dependent demographic traits.
Arbovirus transmission by the mosquito Aedes aegypti can be reduced by the introduction and establishment of the endosymbiotic bacteria Wolbachia in wild populations of the vector. Wolbachia spreads by increasing the fitness of its hosts relative to uninfected mosquitoes. However, mosquito fitness is also strongly affected by population size through density-dependent competition for limited food resources. We do not understand how this natural variation in fitness affects symbiont spread, which limits our ability to design successful control strategies.



We develop a mathematical model to predict A. aegypti-Wolbachia dynamics that incorporates larval density-dependent variation in important fitness components of infected and uninfected mosquitoes. Our model explains detailed features of the mosquito-Wolbachia dynamics observed in two independent experimental A. aegypti populations, allowing the combined effects on dynamics of multiple density-dependent fitness components to be characterized. We apply our model to investigate Wolbachia field release dynamics, and show how invasion outcomes can depend strongly on the severity of density-dependent competition at the release site. Specifically, the ratio of released relative to wild mosquitoes required to attain a target infection frequency (at the end of a release program) can vary by nearly an order of magnitude. The time taken for Wolbachia to become established following releases can differ by over 2 years. These effects depend on the relative fitness of field and insectary-reared mosquitoes.



Models of Wolbachia invasion incorporating density-dependent demographic variation in the host population explain observed dynamics in experimental A. aegypti populations. These models predict strong effects of density-dependence on Wolbachia dynamics in field populations, and can assist in the effective use of Wolbachia to control the transmission of arboviruses such as dengue, chikungunya and zika.
Department of Zoology, University of Oxford, South Parks Road, Oxford, OX1 3PS, UK. hancock.penelope@gmail.com.
Penelope A
PA
Hancock
Bio 21 Institute, School of Biosciences, University of Melbourne, Melbourne, Victoria, 3010, Australia.
Vanessa L
VL
White
Australian Institute of Tropical Health and Medicine, James Cook University, Townsville City, Queensland, 4878, Australia.
Scott A
SA
Ritchie
Bio 21 Institute, School of Biosciences, University of Melbourne, Melbourne, Victoria, 3010, Australia.
Ary A
AA
Hoffmann
Department of Zoology, University of Oxford, South Parks Road, Oxford, OX1 3PS, UK.
H Charles J
HC
Godfray
D000330:Aedes / Q000382:microbiology*; D000818:Animals; D001499:Bayes Theorem; D008962:Models, Theoretical; D020577:Wolbachia / Q000472:pathogenicity*; D000071244:Zika Virus / Q000472:pathogenicity
Aedes aegypti; Bayesian statistical model; Dengue; Density-dependence; Fitness; Invasion; Mosquito; Vector-borne disease; Wolbachia; Zika