The medical records of service in disaster provided at a place other than a medical facility are defined as disaster medical records (DMRs). In this epidemiological study, to clarify medical need characteristics and trends after disaster, we analyzed the all anonymized DMRs of Minamisanriku Town that lost medical facilities in 2011 Great East Japan Earthquake and its consequent tsunami. After screening of duplicated or irrelevant documents, there were 10,464 DMRs with 18,532 diagnoses from March 11 through May 13. From 34 diagnostic groups according to International Classification of Diseases (ICD)-10, we integrated diagnostic groups into five modules that might require treatment concepts of different types: non-communicable disease (NCD), infectious disease, mental health issue, trauma, and maternal and child health (MCH). Age and sex distributions of the patients were similar to those of population before the disaster. The largest diagnostic module was NCD (68%), followed by infectious disease (21%), mental health issues (6%), trauma (4%), and MCH (0.2%). The age-specific rate of NCD exhibited a similar or suppressed level from that of nationwide survey, with higher rate of pollinosis among young population. Infectious disease increased in most age groups but there was no apparent outbreak because of early interventions. Sleep deprivation was twice as frequent in middle-aged women, compared with men. Trauma and MCH were less frequent, but each exhibited a unique time trend. Trauma onset was continuously recorded, while MCH visits were concentrated on a specific day. The medical need after disaster dynamically changes, and appropriate anticipatory countermeasures are necessary.

In the 2011 Great East Japan Earthquake (GEJE), successful medical and public health coordination by pre-assigned disaster medical coordinators saved many affected people, though the coordination itself had difficulties. This study aims to clarify the implementation and the challenges of disaster medical coordinators in Japan. We performed questionnaire surveillance in 2012 and 2014 to all prefectural government on assignment of disaster medical coordinators, their expected roles and supporting system. Out of all 47 prefectures, assignment or planning of disaster medical coordinators jumped up from four (8.5%) to 43 (91.5%) by the end of 2015. The most expected role is the coordination with Japan Disaster Medical Assistant Team (DMAT) and with other early responders. The evacuation center management, public health coordination and preparedness before disaster are less frequently expected. The supporting materials, human resource, and tools for communication vary according to the prefecture. Successful implementation requires the effort of health and governmental stakeholders. The coordination between prefectural and local coordinators and the coordination between medical and public health authorities still need to be improved. The roles of disaster medical coordinators depend on the local context and types of hazards. Education and training to build fundamental capacity is necessary. In conclusion, Japanese disaster medical system rapidly implemented disaster medical coordinator after GEJE. Their roles and standardization are challenging, but education, training and systematic support by the local government will enhance the effective preparedness and response of the health sector in disasters.

In 2011, Minamisanriku Town lost all of its medical facilities during the Great East Japan Earthquake. Using 10,459 anonymized disaster medical records of affected people in Minamisanriku Town, we assessed the prevalence and risk factors of sleep disturbance, which is known to exacerbate non-communicable diseases (NCDs) and anxiety disorder. Because sleep disturbance is a part of mental health issues, we divided the patients into two groups: patients (n = 492) with mental health issues other than sleep disturbance and the remaining (n = 9,967) with other comorbidities. Out of 492 patients with mental health issues, 295 patients (60.0%, 114 male, 158 female and 23 unknown) had sleep disturbance who might have required specific treatments. Out of the remaining 9,967 patients, 1,203 patients (12.1%, 361 male and 769 female and 73 unknown) had sleep disturbance. Univariate and multivariate analyses of the 9,967 patients revealed that the odds ratio (OR) of sleep disturbance was higher for female (OR 1.95), elderly persons over 60 (OR 16.15) and residing in evacuation centers (OR 1.36). Patients with two or more NCD had higher risk (OR 1.42). Importantly, sleep disturbance affects younger patients without NCD residing in evacuation center. Emergency medical teams most frequently prescribed benzodiazepines both for sleep induction and anxiolysis. In addition to high risk groups (female, older, with other mental health issues, residing in evacuation center), it is important to survey sleep disturbance in younger and healthier populations especially in evacuation centers and to provide psychosocial and medical support for them.

A healthy community is a community resilient to disaster. The Sendai Framework for Disaster Risk Reduction considers disaster impacts on health and encourages the implementation of disaster medicine and access to mental health services. Life expectancy (LE) is a basic statistic that indicates public health achievements and social development, including the health system, infrastructure, and accurate vital statistics. Thus, we hypothesized that LE corelates with disaster risk and strategies to achieve long LE can help achieving disaster risk reduction. We compared the disaster risk obtained from Index for Risk Management (INFORM) with the LE of both genders at birth to identify which component of INFORM risk correlates with LE. A correlation analysis revealed that overall INFORM risk negatively correlated with LE. The natural hazard category did not correlate with LE, but the human hazard category, vulnerability, and lack of coping capacity negatively correlated with LE. In the vulnerability dimension, indicators of socioeconomic vulnerability, health conditions, and children U5 negatively correlated with LE. In the lack of coping capacity dimension, indicators of communication, physical infrastructure, and access to health care negatively correlated with LE. Japan has achieved the longest LE and a low INFORM risk because of its lower vulnerability and reduced lack of coping capacity, including healthrelated indicators. In a cluster analysis of LE and INFORM categories of risk, we divided countries into four clusters and found categories that could be improved. Compared with another global disaster risk index, the Word Risk Index (WRI), the INFORM risk index seems to represent the overall disaster risk better, though they have different aspects of risk evaluation. The WRI is also negatively correlated with LE, supporting our hypothesis. In conclusion, LE is an important indicator of disaster risk and strategies to achieve long LE can be effective and important strategies in disaster risk reduction.

Healthcare workers (HCWs) are often exposed to nosocomial infection when caring for patients with Ebola Virus Disease (EVD). During the 2014-2016 EVD outbreak in West Africa, more than 200 HCWs died of EVD in Sierra Leone. To determine the factors that are important for preventing infection among HCWs during EVD outbreak, we used agent-based modeling and simulation (ABMS) by focusing on education, training and performance of HCWs. Here, we assumed 1, 000 HCWs as "agents" to analyze their behavior within a given condition and selected four parameters (P1-P4) that are important in the prevention of infection: "initially educated HCWs (P1)", "initially educated trained (P2)", "probability of seeking training (P3)" and "probability of appropriate care procedure (P4)." After varying each parameter from 0% to 100%, P3 and P4 showed a greater effect on reducing the number of HCWs infected during EVD outbreak, compared with the other two parameters. The numbers of infected HCWs were decreased from 897 to 26 and from 1,000 to 59, respectively, when P3 or P4 was increased from 0% to 100%. When P2 was increased from 0% to 100%, the number of HCWs infected was decreased from 166 to 44. Paradoxically, the number of HCWs infected was increased from 56 to 109, when P1 was increased, indicating that initial education alone cannot prevent nosocomial infection. Our results indicate that effective training and appropriate care procedure play an important role in preventing infection. The present model is useful to manage nosocomial infection among HCWs during EVD outbreak.