52 - Competing Containers: Evaluating Ovitrap Efficiency Against Adult Traps for Aedes aegypti Surveillance in Grand Cayman

Abstract: Ovitraps are widely used for Aedes aegypti surveillance, offering a cost-effective and sensitive means of detecting vector presence. However, their efficiency can vary depending on the abundance of alternative oviposition sites, which influences gravid female behaviour and egg distribution. This study compared ovitrap performance with adult mosquito abundance across two contrasting environments in Grand Cayman, Cayman Islands, to assess how competing containers affect ovitrap sensitivity.

Two study areas were examined: a clean residential site at Court Road with few water-holding containers, and a large tire storage area containing millions of potential oviposition sites. Twenty ovitraps were deployed at each location and inspected weekly for three weeks, while adult Aedes aegypti were simultaneously monitored using BG-Sentinel-2 traps baited with lactic acid. Data were analysed in RStudio using ChatGPT-assisted workflows for data cleaning, visualization, and model fitting, applying generalized linear and mixed models with DHARMa residual diagnostics to account for overdispersion and non-normality.

Ovitrap positivity was significantly higher at Court Road (71.4%) than at the tire pile (26.9%) (χ² = 19.62, p < 0.001). Mean egg counts per positive paddle were 28 at Court Road and 10 at the tire pile. In contrast, adult abundance was approximately 350-fold greater at the tire pile (mean ≈ 2,463 vs. 7 per trap; p < 0.001). These results reveal an inverse relationship between ovitrap yield and container abundance, demonstrating that ovitraps become less sensitive in environments saturated with breeding sites, potentially leading to underestimation of true mosquito density.

Ovitrap data must therefore be interpreted within their ecological context. Integrating AI-assisted analytical tools such as ChatGPT provides an efficient, reproducible framework for analysing entomological data and improving the accuracy of mosquito surveillance and control evaluation programs.