Modelling the Wolbachia incompatible insect technique: strategies for effective mosquito population elimination

BMC Biol. 2020 Nov 6;18(1):161. doi: 10.1186/s12915-020-00887-0.


Background: The Wolbachia incompatible insect technique (IIT) shows promise as a method for eliminating populations of invasive mosquitoes such as Aedes aegypti (Linnaeus) (Diptera: Culicidae) and reducing the incidence of vector-borne diseases such as dengue, chikungunya and Zika. Successful implementation of this biological control strategy relies on high-fidelity separation of male from female insects in mass production systems for inundative release into landscapes. Processes for sex-separating mosquitoes are typically error-prone and laborious, and IIT programmes run the risk of releasing Wolbachia-infected females and replacing wild mosquito populations.

Results: We introduce a simple Markov population process model for studying mosquito populations subjected to a Wolbachia-IIT programme which exhibit an unstable equilibrium threshold. The model is used to study, in silico, scenarios that are likely to yield a successful elimination result. Our results suggest that elimination is best achieved by releasing males at rates that adapt to the ever-decreasing wild population, thus reducing the risk of releasing Wolbachia-infected females while reducing costs.

Conclusions: While very high-fidelity sex separation is required to avoid establishment, release programmes tend to be robust to the release of a small number of Wolbachia-infected females. These findings will inform and enhance the next generation of Wolbachia-IIT population control strategies that are already showing great promise in field trials.

Keywords: Elimination; Establishment risk; Incompatible insect technique; Simulation; Stochastic model; Wolbachia.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aedes / microbiology*
  • Animals
  • Female
  • Male
  • Markov Chains
  • Models, Biological
  • Mosquito Control / methods*
  • Mosquito Vectors / microbiology*
  • Population Dynamics
  • Wolbachia / physiology*