Models for quantitative risk assessment of infectious diseases induced by urban flood were developed, considering effects of climate and societal changes, in some cities in Asian developing countries. One of the developed model was a QMRA-based model which enabled us to estimate risk of norovirus infection taking human behaviors in flood setting and human-to-human transmission in households into account. Another model to estimate risk of dengue fever based on climatic parameters, focusing on seasonal and spatial changes of its prevalence in cities, was developed using an algorithm for machine learning.
We also clarified infectious diseases which happen frequently in flood settings and inhabitants’ feeling to the diseases by means of interview surveys in the target cities. According to the result, the method to calculate DALY lost by the infectious diseases was modified and finally the economic loss due to the diseases induced by urban flood was quantified.