Optimization of long-lasting insecticidal bed nets for resistance management: a modelling study and user-friendly app

Area of Science:

• Vector control
• Malaria prevention
• Insecticide resistance

Background:

• Pyrethroid-treated bed nets are crucial for malaria vector control.
• Mass distribution has reduced malaria cases but led to widespread pyrethroid resistance.
• New insecticides are being developed, but optimal deployment strategies remain unclear.

Purpose of the Study:

• To present an app for optimizing insecticide-treated bed net (ITN) design and deployment.
• To model the impact of insecticide loading, lifespan, and resistance evolution on mosquito control.
• To explore trade-offs and identify optimal strategies for ITN deployment under various constraints.

Main Methods:

• Developed an app incorporating models of ITN properties and mosquito resistance evolution.
• Used default parameter values fitted from experimental data.
• Numerically searched across numerous models with variable loading and lifespan to find optimal configurations.

Main Results:

• Optimization can significantly increase mosquito population control, with greater gains at lower public health budgets.
• Optimizing ITNs within current procurement systems improves control, but unconstrained optimization yields even greater benefits.
• Coverage, influenced by cost per net, is the most critical factor for optimization.
• Pyrethroids remain a preferred partner for new insecticides due to cost-effectiveness and resistance management benefits.

Conclusions:

• Trade-offs are critical in designing effective ITNs for vector control.
• Current global procurement systems present challenges for deploying new insecticides effectively.
• Incentives for resistance management in ITN design are lacking in existing standards and procurement systems.