Estimating mosquito bionomics parameters with a hierarchical Bayesian model

Area of Science:

• Entomology
• Epidemiology
• Parasitology

Background:

• Anopheles mosquito bionomics (endophily, endophagy, anthropophagy, survival) influence malaria transmission and vector control efficacy.
• Local data on these Anopheles mosquito parameters are often scarce, hindering targeted interventions.

Purpose of the Study:

• To estimate species-specific Anopheles mosquito bionomic parameters using an augmented global database.
• To quantify the impact of pyrethroid-chlorfenapyr insecticide-treated nets (ITNs) on vectorial capacity across 57 Anopheles species.

Main Methods:

• Applied inclusion/exclusion criteria to select eligible studies for parous, sac, endophagy, endophily rates, and resting duration.
• Utilized hierarchical Bayesian models based on Anopheles taxonomy to estimate bionomic parameters.
• Separated human blood index (HBI) data by indoor and outdoor collection sites.

Main Results:

• Estimated genus-level Anopheles parous rate at 56% (95% CrI: 31-78%) and endophagy at 41% (95% CrI: 14-72%).
• Resting duration averaged 2.3 days (95% CrI: 1.1-6.2 days) for the genus Anopheles.
• Vectorial capacity reduction from pyrethroid-chlorfenapyr ITNs ranged from 48% to 76% across species.

Conclusions:

• Species-specific Anopheles bionomics significantly impact malaria vector control effectiveness.
• Generated species-specific bionomic estimates to better understand local vector behavior and vulnerability.
• Highlights the need for standardized field surveys to improve characterization of local vector behavior.