Under climate change, it is expected that changes in urban weather will increase health risks such as infectious diseases and heat disorders. Particularly, developing country vulnerability is concerned. This study develops a machine learning model that predicts three health risks for cities in Southeast Asia.
This study targets cities in Southeast Asia and aims to develop machine learning models to predict the following risks: 1) Heat-related health disorders such as heat stroke and sleep disorders; 2) Water-borne infectious diseases such as diarrhea, skin disease and eye disease; 3) Mosquito-borne infections such as dengue fever and Zika.
By coupling with climate change models, DALY (disability adjustment loss year) under the assumed climate change adaptation option will be calculated respectively. An integrated risk assessment approach will be developed to estimate the economic loss.