Tsunamis cause direct damage to property and destroy infrastructure. In addition, power outages can lead to death, especially for patients who rely on medical equipment requiring a power supply. Recently, Nankai Trough Earthquakes have been predicted, and much effort has been put into developing countermeasures in Japan. Kochi City on Shikoku Island is expected to suffer in the event of a large tsunami. The present study identifies individuals living in Kochi who need evacuation assistance and depend on electrical medical devices, simulates evacuation behavior and inundation during a tsunami using a geographic information system (GIS), and considers the usefulness of such a GIS. We asked caregivers, including visiting nurses, to introduce us to homecare recipients who rely on a ventilator, an endotracheal suction device, or other medical devices requiring electric power. We received introductions to 52 homecare recipients. Using a GIS, we plotted the area of predicted inundation and the locations of homecare recipients, nursing stations, and welfare evacuation shelters. We predicted evacuation routes, and then analyzed the time difference between the time required for evacuation and tsunami arrival at a welfare evacuation shelter. To measure the effects of the main parameters, we conducted both one-way and multi-way sensitivity analysis. In the event of a tsunami, eight of the homecare recipients living in the forecasted inundation areas in Kochi may face delayed evacuation. Among homecare recipients facing a high possibility of escape delay, 95.2% lived more than 1,800 m from the nearest welfare evacuation shelter. We found that individual evacuation behavior can be simulated by specifying the residence of a homecare recipient and the evacuation route using a GIS.

The Nankai Trough in Japan has been identified as a geological feature that could cause extensive damage in the event of a major earthquake. In this study, we investigated the impact of effective guidance signs for hearing-impaired individuals requiring special care when escaping to a tsunami evacuation building (emergency evacuation location) using geographical information system (GIS) and viewshed analysis. We selected an area we considered would suffer severe damage following a major earthquake and tsunami; we identified difficulties in the provision of escape routes. Using GIS, we determined the time required for escape and tsunami arrival time if effective signs were installed; we undertook such analysis using the height data of buildings in the target area. With effectively installed guidance signs, the average required evacuation time was 36.88 minutes; without such signs (which is currently the case in the target area), the average time was 47.10 minutes: that would result in citizens getting caught by the tsunami. Installing effective guidance signs would allow hearing-impaired individuals to escape to an evacuation building before being hit by the tsunami.

This paper describes the design and function of an application that enables vulnerable people to provide medical information for use in disasters, and presents the results of an initial test of its usability in Nankoku, Japan. The application consists of two parts: K-DiPS Solo, a smartphone app, and K-DiPS Online, a web application for disaster management by local governments. We asked vulnerable people or their family caregivers to enter medical information into the app on their smartphones and connected this information to a local government application as a demonstration of a disaster response solution that manages information. We targeted a group of 14 healthy older people. The user information that they entered into the app was stored in the cloud via the communication system of the mobile phone. A ledger of vulnerable people for use in the event of a disaster was automatically created on the web application using the information supplied by the individuals. Local government staff corrected the location information, if necessary, by dragging points plotted on a map. This disaster response solution was shown to connect individuals to government offices, and to enable a consistent flow of information from patient details to stocking of supplies, and for simulation, training, and response during disasters.

Earthquakes and tsunamis are expected to occur within the next 30 years along Japan's Nankai Trough. Existing disaster prevention plans and calculated evacuation capacities in the coastal areas that would be affected do not account for physical distancing in the context of COVID-19. Therefore, we developed a tsunami evacuation placement model incorporating physical distance guidelines for infection control and living space per person into calculations of evacuation center accommodation capacities in Aki City, Kochi Prefecture. Using available administrative, population, and tsunami inundation data, we counted and mapped evacuation centers in the estimated inundated area within three zones constructed for smooth evacuation using the ArcGIS software Build Balanced Zones Tool. We calculated the space per evacuee using the Sphere handbook standard of 3.5 m 2 or double the Sphere standard at 7 m 2 plus the recommended physical distance of 11 m 2 per person. We then compared the results with planned capacities. A total of 27 shelters are located in the area projected to be inundated at depths of 0.3–10 m, and their planned capacity, 2 m 2 for each evacuee, would accommodate 32.9% of Aki's population and result in 9639 unaccommodated evacuees. Allotting 14.5 m 2 (living space) or 18 m 2 (living space plus space to maintain physical distancing) would reduce accommodation capacities to 57.1% and 28.6% (12,133 and 12,371 unaccommodated evacuees, respectively). Given these accommodation shortages, we recommend that evacuation centers are set aside for vulnerable people and that alternative evacuation sites such as parking lots and mountain campsites are preplanned.

In the current study, we sought to identify special needs and safe evacuation conditions for children with neurodevelopmental disorders (CNDs) along Japan’s tsunami-prone Pacific coast. A survey and spatial analysis were used to collect data of CNDs (n = 47) and their caregivers. Areas predicted to be flooded in a tsunami, as well as evacuation routes to emergency shelters for vulnerable people (ESVPs), were mapped using geographic information systems (GIS). Our results showed that five professional staff were needed to support 33 CNDs requiring 135.9 m2 of ESVP space. Critical safety factors were altitude, vertical evacuation, accessibility to ESVPs, and nonexistence of estuaries in the direction of evacuation. GIS-based spatial analysis and evacuation modeling for disaster preparedness and training plans that involve nurses are essential.