Increasing Effectiveness of Genetically Modifying Mosquito Populations: Risk Assessment of Releasing Blood-Fed Females

Am J Trop Med Hyg. 2021 Mar 29;104(5):1895-1906. doi: 10.4269/ajtmh.19-0729.

Abstract

Releasing mosquito refractory to pathogens has been proposed as a means of controlling mosquito-borne diseases. A recent modeling study demonstrated that instead of the conventional male-only releases, adding blood-fed females to the release population could significantly increase the program's efficiency, hastening the decrease in disease transmission competence of the target mosquito population and reducing the duration and costs of the release program. However, releasing female mosquitoes presents a short-term risk of increased disease transmission. To quantify this risk, we constructed a Ross-MacDonald model and an individual-based stochastic model to estimate the increase in disease transmission contributed by the released blood-fed females, using the mosquito Aedes aegypti and the dengue virus as a model system. Under baseline parameter values informed by empirical data, our stochastic models predicted a 1.1-5.5% increase in dengue transmission during the initial release, depending on the resistance level of released mosquitoes and release size. The basic reproductive number (R0) increased by 0.45-3.62%. The stochastic simulations were then extended to 10 releases to evaluate the long-term effect. The overall reduction of disease transmission was much greater than the number of potential infections directly contributed by the released females. Releasing blood-fed females with males could also outperform conventional male-only releases when the release strain is sufficiently resistant, and the release size is relatively small. Overall, these results suggested that the long-term benefit of releasing blood-fed females often outweighs the short-term risk.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aedes / virology*
  • Animals
  • Communicable Disease Control / organization & administration*
  • Computer Simulation
  • Dengue
  • Dengue Virus / growth & development
  • Dengue Virus / pathogenicity*
  • Female
  • Humans
  • Male
  • Models, Statistical*
  • Mosquito Control
  • Mosquito Vectors / virology*
  • Population Dynamics / trends
  • Risk Assessment
  • Stochastic Processes