RESULTS: We demonstrate a method using a web-based tool to construct a deep learning model and later export the model for deployment. We train the model by using breeding substrate images with different spectra of illumination on known densities of larvae and evaluate the training model in both the test set and field-collected samples. In general, the model was able to predict the larval abundance by the laboratory-prepared breeding substrate with 87.56% to 94.10% accuracy, precision, recall, and F-score on the unseen test set, and white and green illumination performed significantly higher compared to other illuminations. For field samples, the model was able to obtain at least 70% correct predictions by using white and infrared illumination.

METHODS: This study conducted the PRISMA-ScR scoping review and formulated a set of research questions to identify current trends in vector-borne diseases in Borneo. These questions aim to identify which diseases have been studied, what geographical areas have been covered by the research, how the One Health approach-encompassing human, animal and environmental factors-is integrated, and what gaps and challenges exist in addressing these diseases.

RESULTS: A total of 2241 references were screened for eligibility and 117 articles were selected for review. The majority of the materials focused on mosquitoes and malaria, and the One Health elements focused mainly on humans.