A Simulation Model of Escapable and Non-Escapable Areas from Which Pregnant Women Can Reach Tsunami Evacuation Buildings: The Case in 110 Elementary School Districts in Nagoya City, Aichi, Japan.

OBJECTIVE: The objective of this study was to establish a method for evaluating the possibility of pregnant women evacuating to tsunami evacuation buildings in coastal areas affected by tsunami. METHODS: We used data published by the Japanese government and a general-purpose geographic information system to develop a simulation method for evaluating the possibility of evacuation. The data included the number of pregnant women in each elementary school district, tsunami inundation forecast maps, location information of tsunami evacuation buildings, and the number of ordinary buildings. We used our method to conduct a tsunami evacuation possibility simulation for pregnant women in each elementary school district in 7 wards of Nagoya, Japan. RESULTS: Dense population areas at low elevations are high-risk areas from which many pregnant women may not be able to evacuate. Districts with evenly distributed tsunami evacuation buildings tend to have a lower risk. CONCLUSIONS: The proposed simulation method was able to determine the risk in elementary school districts in densely populated low-lying areas. However, it is suggested that the risk tends to be estimated higher in school districts where there are differences in elevation and the building distribution is not uniform.

Road Centerline Data Accumulation for Rescue Workers Whose Expertise Is Not GIS.

OBJECTIVES: The objective of this study is to provide road centerline data for professionals of disaster medicine areas who are often beginners in GIS use. METHODS: Newly developed vector tile format data were converted into shapefile format data, then were organized as second level medical districts to which medical professionals are accustomed. RESULTS: Road centerline data in Japan is being prepared to release from Association for Promotion of Infrastructure Geospatial Information Distribution free of charge. CONCLUSION: Professionals of disaster medicine areas increased their accessibility of GIS. Logistic planning for evacuation activities and dispatching of rescue teams were improved.

Predicted Number of Pregnant Women in Aichi Prefecture, Japan: Estimation by Machine Learning Database Construction for Disaster Preparation.

Aichi prefecture, Japan is predicted to be hit by Mega-earthquake. Aichi Prefectural Association of Midwives has been making efforts to improve disaster preparedness for pregnant women. This project aims to acquire area data of pregnant women for simulated studies of rescue activities. Number of women in census survey areas in Nagoya City was acquired from nationwide data of pregnant women by machine learning (Cascade-Correlation Learning Architecture). Quite high correlation coefficients between actual data and estimation data were observed. Rescue simulations have been carried out based on the data acquired by this study.

Estimation of Pregnant Women Possibly Left Behind in Tsunami Predicted Areas of Nagoya City: A Simulation for Rescue Planning.

OBJECTIVE: In case of an outbreak of Nankai Trough Mega-earthquake, it is predicted that a tsunami would invade Nagoya City within 100 minutes, hitting about one third of the City of Nagoya. If the administrative plan of the city and midwives' expertise are coordinated, pregnant women's chances of survival will increase. The authors carried out this simulation study in an attempt to improve consistency of the two efforts. METHOD: We estimated the number of pregnant women using a machine learning model. The evacuation distance of pregnant women was estimated on the basis of the data of road center line. RESULTS: Through this simulation study, it became clear that preparation for approximately 2600 pregnant women escaping from tsunami predicted area and for about 1200 pregnant women possibly left in the area is needed. CONCLUSIONS: Our study suggests that triage point planning is needed in areas where pregnant women are evacuated. The triage makes it possible to transport women to appropriate hospitals.