Surveillance of dengue vectors using spatio-temporal Bayesian modeling

Area of Science:

• Entomology and Public Health
• Spatial Epidemiology
• Vector-borne Disease Control

Background:

• Current dengue control strategies primarily target Aedes aegypti, the main disease vector.
• Existing entomological surveillance methods for Aedes aegypti are often inefficient.
• Novel approaches are crucial for effective dengue vector monitoring and control.

Purpose of the Study:

• To analyze the spatio-temporal dynamics of Aedes aegypti infestation using oviposition traps.
• To develop and implement efficient computational methods for dengue vector surveillance.
• To integrate spatio-temporal models into monitoring systems for improved dengue control.

Main Methods:

• Deployment of 240 oviposition traps across eight sentinel areas in Rio de Janeiro.
• Weekly monitoring of immature Aedes aegypti and Aedes albopictus from November 2010 to August 2012.
• Application of Bayesian zero-inflated spatio-temporal models to assess relationships between egg counts and environmental variables, using Integrated Nested Laplace Approximation (INLA).

Main Results:

• Oviposition occurred throughout the study period, with significant relationships identified between egg numbers and trap distance to boundary, minimum temperature, and accumulated rainfall.
• A more informative surveillance model was achieved by considering the interaction between temperature and rainfall, indicating favorable conditions for vector reproduction.
• Moderate temporal (0.29–0.43) and spatial (21.23–34.19 m) dependencies were observed, with spatial patterns correlating with human population density.

Conclusions:

• Aedes aegypti exhibits rapid, eruptive dynamics influenced by climate, making prediction difficult with solely temporal or spatial models.
• The developed methodology efficiently implemented spatio-temporal models accounting for zero-inflation and climate variable interactions.
• The model parameters effectively identify priority areas for entomological surveillance, enhancing dengue control efforts.