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.

On 1 January 2024, a large earthquake occurred in Japan’s Noto region. Many buildings collapsed as a result of violent shaking. Electricity and water supplies were cut off, and communications were disrupted. On 5 January, four days after the earthquake, we visited Noto and conducted disaster-relief activities. This report integrates and discusses the results of the site visits, information broadcasts by public institutions, and previous research. Evacuation centers lacked water and proper sanitation, leading to health issues, including infectious diseases. Disaster Medical Assistance Teams (DMAT) were delayed in implementing infection control measures. Isolated evacuation centers faced communication and supply challenges. Infrastructure restoration, power supply, and toilet facilities at evacuation centers were delayed because of geographical challenges. It is important to have a team that can determine and carry out the necessary activities on site, even without instructions from the DMAT. It is believed to be effective to decide in advance how volunteer teams and the private sector will conduct their activities, assuming that they will be unable to contact public institutions during a disaster. In large-scale disasters, evacuees must operate evacuation centers autonomously. To achieve this, it is necessary for residents to regularly come together as a community. Systematically recording and accumulating these experiences will contribute to improved disaster prevention and mitigation planning. We hope that the experiences we obtained through the abovementioned disaster will be useful for preparing for future disasters.

This study evaluated the detection of monthly human mobility clusters and characteristics of cluster areas before the coronavirus disease 2019 (COVID-19) outbreak using spatial epidemiological methods, namely, spatial scan statistics and geographic information systems (GIS). The research area covers approximately 10.3 km², with a population of about 350,000 people. Analysis was conducted using open data, with the exception of one dataset. Human mobility and population data were used on a 1-km mesh scale, and business location data were used to examine the area characteristics. Data from January to December 2019 were utilized to detect human mobility clusters before the COVID-19 pandemic. Spatial scan statistics were performed using SaTScan to calculate relative risk (RR). The detected clusters and other data were visualized in QGIS to explore the features of the cluster areas. Spatial scan statistics identified 33 clusters. The detailed analysis focused on clusters with an RR exceeding 1.5. Meshes with an RR over 1.5 included one with clusters for 1 year which is identified in all months of the year, one with clusters for 9 months, three with clusters for 6 months, three with clusters for 3 months, and four with clusters for 1 month. September had the highest number of clusters (eight), followed by April and November (seven each). The remaining months had five or six clusters. Characteristically, the cluster areas included the vicinity of railway stations, densely populated business areas, ball game fields, and large-scale construction sites. Statistical analysis of human mobility clusters using open data and open-source tools is crucial for the advancement of evidence-based policymaking based on scientific facts, not only for novel infectious diseases but also for existing ones, such as influenza.

Following the Great East Japan Earthquake, vertical evacuation shelters (VES) were constructed to reduce tsunami risk. Childcare centers (CCs) in the inundation area are required to evacuate to the nearest VES in the event of a tsunami. The study aim was to identify CCs and VES predicted to be inundated by a Nankai Trough earthquake-generated tsunami, and to clarify CC inundation risk. We identified 52 (45.6%) CCs in the tsunami inundation area and found that 14 (25.9%) would evacuate toward the tsunami. If the walking speed was 2.24 km/h and a 0.3 m tsunami arrived in 10 min, nine (17.3%) CCs would be late to safe evacuation. If the tsunami arrival time was 20 min, four (7.7%) CCs would have late evacuation. At a walking speed of 1.00 km/h, 38 (73.1%) and 20 (38.5%) CCs would have late evacuation, with tsunami arrival times of 10 min and 20 min, respectively. Evacuation direction is important in avoiding tsunami damage. An evacuation strategy is needed that evacuates people away from the tsunami, and takes into account children’s age, walking speed, and evacuation method. The evaluation of tsunami risk in this study may support the development of tsunami countermeasures in other coastal areas with latent tsunami risks.

On January 1, 2024, a large earthquake occurred in Japan’s Noto region. Many buildings collapsed as a result of violent shaking. Electricity and water supplies were cut off and communications were disrupted. Immediately after the earthquake, we visited Noto and conducted disaster-relief activities. This report integrates and discusses the results of the site visits, information broadcasts by public institutions, and previous research. Evacuation centers lacked water and proper sanitation, leading to health issues, including infectious diseases. Disaster Medical Assistance Teams (DMAT) were delayed in implementing infection control measures. Isolated evacuation centers faced communication and supply challenges. Infrastructure restoration, power supply, and toilet facilities at evacuation centers were delayed because of geographical challenges. There was a lack of intervention by medical professionals in evacuation centers because the DMATs were forced to invest manpower in rescue operations. It is important to have a team that can determine and carry out the necessary activities on site, even without instructions from the DMAT. It is believed to be effective to decide in advance how volunteer teams and the private sector will conduct their activities, assuming that they will be unable to contact public institutions during a disaster. In large-scale disasters, evacuees must operate evacuation centers autonomously. To achieve this, it is necessary for residents to form healthy communities regularly. A serious disaster is expected to soon occur in Japan. We hope that the experience of this disaster will be useful for preparing for future disasters.