Added-value of mosquito vector breeding sites from street view images in the risk mapping of dengue incidence in Thailand.

ABSTRACT: Dengue is an emerging vector-borne viral disease across the world. The primary dengue mosquito vectors breed in containers with sufficient water and nutrition. Outdoor containers can be detected from geotagged images using state-of-the-art deep learning methods. In this study, we utilize such container information from street view images in developing a risk mapping model and determine the added value of including container information in predicting dengue risk. We developed seasonal-spatial models in which the target variable dengue incidence was explained using weather and container variable predictors. Linear mixed models with fixed and random effects are employed in our models to account for different characteristics of containers and weather variables. Using data from three provinces

SUBMITTER: Su Yin M 

PROVIDER: S-EPMC7971869 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature