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A quantitative risk assessment of waterborne infectious disease in the inundation area of a tropical monsoon region
Authors:So Kazama  Toshiki Aizawa  Toru Watanabe  Priyantha Ranjan  Luminda Gunawardhana  Ayako Amano
Institution:(1) Department of Civil Engineering, Tohoku University, 6-6-06 Aramaki aza aoba, Aoba ku, Sendai 980-8579, Japan;(2) Obayashi Corporation, Shinagawa Intercity Tower B, 2-15-2 Konan, Minato-ku, Tokyo 108-8502, Japan;(3) Faculty of Agriculture, Yamagata University, Wakaba-machi, Tsuruoka WA, 997-8555, Japan;(4) Department of Civil Engineering, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia;
Abstract:Flooding and inundation are annual events that occur during the rainy season in Cambodia, and inundation has a strong relationship with human health. This study simulated the coliform bacteria distribution using a hydraulic model and estimated the impact of inundation on public health using a dose–response model. The model parameters were calibrated using field survey data from Cambodia and obtained good agreement with the coliform group count distribution. The results suggest that the impact of inundation on human health is most noticeable in residential areas. The annual average risk of infection during medium-sized flood events is 0.21. The risk due to groundwater use ranges from 0.12 to 0.17 in inundation areas and reaches as high as 0.23 outside the inundation areas. The risk attributed to groundwater use is therefore higher than that for surface water use (0.02–0.06), except in densely populated areas at the city center. There is a high risk for infection with waterborne disease in residential areas, and the annual average risk during small flood events is 0.94. An assessment of possible countermeasures to reduce the risk shows that the control of inundation may bring more risk to public health in Cambodia. Shallower inundation water (<0.3 m) leads to a higher risk of infection, but if the depth is greater than 2 m, the risk is low in residential areas. The simulated results explain the spatial distributions of infection risk,, which are vitally important for determining the highest priority places with relatively high risk and will be helpful for decision makers when considering the implementation of countermeasures.
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