Awareness of disaster preparedness between administrative staff and residents in the vicinity of the Genkai and Ikata nuclear power plants following the Fukushima Daiichi nuclear power plant disaster.

When considering disaster preparedness, one challenge is mitigating the health impacts of evacuations. Nuclear disaster preparedness has evolved based on past experiences from numerous disasters, including the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. However, there is a lack of comprehensive reporting on the awareness of administrative staff, medical personnel, and residents in the areas surrounding nuclear power plants (NPPs). This study reports on a survey aimed at gaining insights into the understanding and current state of disaster preparedness and elucidating the differences in perceptions of nuclear disaster preparedness among the relevant stakeholders surrounding NPPs. Interview surveys were conducted from 14 to 16 September 2022 in the area surrounding Kyushu Electric Power's Genkai NPP in Saga Prefecture and from 11 to 13 January 2023 in the area around Shikoku Electric Power's Ikata NPP. The surveys targeted administrative, medical, and nursing care facilities and residents. Responses from 57 participants indicated a lack of awareness of natural and nuclear disasters, challenges in evacuation planning, and a gap between nuclear disaster training and residents' understanding of evacuation protocols. This study highlights inadequacies in nuclear disaster preparedness and the need for a better understanding among residents regarding evacuation procedures. This study identified three key issues: (1) a lack of awareness about disasters, including nuclear disasters; (2) concerns about complex disasters and the difficulties in creating evacuation plans; and (3) a discrepancy between nuclear disaster training and residents' understanding of evacuation procedures. To bridge this gap, it is important to deepen residents' understanding of nuclear disasters, continuously convey the lessons learned from the FDNPP accident, and regularly reassess and update nuclear disaster preparedness strategies.

The difficulty of nuclear emergency prevention measures during natural disasters: ongoing challenges in Japan.

It is crucial to anticipate nuclear emergency scenarios and implement effective measures. Japan's climate and topography make it vulnerable to natural disasters; thus, it is necessary to address compounding and cascading disaster scenarios involving the simultaneous occurrence of natural and nuclear disasters. On 1 January 2024, an earthquake hit the Noto region of Ishikawa Prefecture, resulting in damage to the area around the Shika Nuclear Power Plant, located 90 km from the epicenter. This earthquake revealed that, in the event of a complex disaster, it is possible that residents living within 30 km of the Shika Nuclear Power Plant will be completely unprepared for a nuclear disaster. In the event of a complex disaster, it is crucial to implement appropriate countermeasures while balancing responses to both nuclear and natural disasters and optimizing radiation disaster prevention measures.

Time course of adverse reactions following BNT162b2 vaccination in healthy and allergic disease individuals aged 5-11 years and comparison with individuals aged 12-15 years: an observational and historical cohort study.

We aimed to investigate the type and frequency of adverse events over 7 days following the first and second BNT162b2 vaccination. This observational and historical cohort study included patients aged 5-11 years who received two doses of BNT162b2 and provided consent along with their guardians. We collected data on sex, age, height, weight, blood type, history of Bacille Calmette-Guerin vaccination, allergic disease, medication, history of coronavirus disease 2019 (COVID-19), and adverse reactions 7 days following the first and second BNT162b2 vaccination using a questionnaire. Our results were compared with previously reported results for individuals aged 12-15 years. A total of 421 participants were eligible for this study. Among the 216 patients with allergic disease, 48 (22.2%) had experienced worsening of their chronic diseases, and the frequency of fatigue and dizziness after the second dose was higher than that of healthy individuals. The experience of systemic adverse reactions was associated with asthma. The frequency of headache, diarrhea, fatigue, muscle/joint pain, and fever after the second BNT162b2 vaccination was lower in individuals aged 5-11 years than in those aged 12-15 years. Fever was the only systemic adverse reaction that lasted longer than 5 days (1.0% of participants). CONCLUSIONS: Individuals with allergic diseases, who are potentially susceptible to COVID-19, may experience worsening of their chronic diseases and more frequent adverse reactions after BNT162b2 vaccination than healthy individuals. To ensure that children with allergic diseases receive the vaccine safely, further information needs to be collected. WHAT IS KNOWN: • Adverse reactions after BNT162b2 vaccination among individuals aged 5-11 years are generally nonserious, more common after second vaccination, and substantially less common compared to those observed among individuals aged 12-15 years. WHAT IS NEW: • Individuals with allergic diseases experienced worsening of their chronic diseases and more frequent adverse reactions after BNT162b2 vaccination than healthy individuals. • Systemic adverse reactions were associated with asthma. Fever was the only systemic adverse reaction that lasted longer than 5 days.

Insights and viewpoints from a small-scale survey on current nuclear disaster preparedness measures in Japan after the Fukushima Daiichi Nuclear Power Plant accident.

In nuclear disaster prevention, it is essential not only to make daily efforts to prevent accidents from occurring but also to properly apply lessons learnt from actual disasters. Although significant changes have been made to nuclear disaster preparedness in Japan since the Fukushima Daiichi Nuclear Power Plant accident, there is insufficient information on whether these changes have been evaluated as practical and appropriate for the needs of the Japanese public. In this survey, 20 officials of the Cabinet Office and Japan Atomic Energy Agency, in charge of planning nuclear disaster prevention policy, were asked to evaluate the current nuclear disaster prevention plan through a questionnaire, and compare it with that before the accident, and indicate what elements are lacking in the current plan. The survey results revealed that 30% of the participants (six respondents) had a positive view of the enhancement of resources, including physical and human assets. However, as many as 60% (12 respondents) expressed negative sentiments, primarily due to perceived deficiencies in organisational measures, particularly the coordination of these resources. Moreover, the participants expressed keen interest in obtaining health data during evacuation, along with information on the physical and mental effects on evacuees living in evacuation centres. These crucial insights can inform the formulation of effective future preparedness plans for evacuation and radiation protection.

Symposium on disaster-related deaths after the Fukushima Daiichi Nuclear Power Plant accident.

Disaster deaths can be classified into direct and indirect deaths. Direct deaths are those caused by the direct physical effects of disasters, such as earthquakes, tsunamis, and radiation exposure. Indirect deaths are those caused by secondary health effects such as emergency evacuation, relocation, evacuation environment, disruption of health care delivery services, and psychosocial effects. In addition, in Japan, the term disaster-related deaths refers to indirect deaths in accordance with the disaster condolence payments system, which provides relief for bereaved families. On 11 March 2011, the Great East Japan Earthquake exposed several issues related to disaster-related deaths in Japan. Therefore, on 1 February 2022, a symposium on disaster-related deaths hosted by this study was held on the website. The symposium discussed the issues and challenges associated with disaster-related deaths for future disaster preparedness. The authors introduced the concept of 'shaking' at the symposium by defining 'shaking' as 'the repeated changes in the social and living environment that worsen health conditions, regardless of the disaster'. It was also pointed out that vulnerable populations are more likely to experience more pronounced health effects. This generalised concept of 'shaking' associated with disaster-related deaths suggests that it is important to anticipate disasters before they occur to take specific preventive measures, targeted at vulnerable populations. This study found that disaster-related deaths in Japan create several problems in terms of future radiation disaster preparedness and medical countermeasures. In the future, there will be a need to examine the relevance of the issues of disaster-related deaths identified as a result of this symposium for future radiation disaster preparedness.

Fabrication of a high performance flexible capacitive porous GO/PDMS pressure sensor based on droplet microfluidic technology.

Porous structures are an effective way to improve the performance of flexible capacitive sensors, but the pore size uniformity of porous structures is not easily controlled by current methods, which may affect the inconsistent performance of different batches of sensors. In this paper, a high performance capacitive flexible porous GO/PDMS pressure sensor was prepared based on droplet microfluidic technology. By testing the performance of the sensor, we found that the sensor with a flow rate ratio of 1 : 3 has relatively good performance, with a degree of hysteresis (DH) of 8.64% and a coefficient of variation (CV) of 5.2%. Therefore, we studied the sensor performance based on this process. The result shows that the sensitivity of the flexible capacitive porous GO/PDMS pressure sensor reached 0.627 kPa-1 at low pressure (0-3 kPa), which is significantly higher than that of the pure PDMS thin film sensor (about 0.031 kPa-1) and the porous PDMS pressure sensor (0.263 kPa-1). At the same time, the sensor has a large range with a fast response time of 240 ms and a relaxation time of 300 ms at 30 kPa and an ultra-low detection limit (70 Pa). It can maintain stable operation under continuous force loading/unloading cycles and can respond well to different pressure step changes, so the sensor can be used to detect the movement process of each finger, knee, foot and other joints of the human body. In conclusion, the droplet microfluidic technology can effectively prepare high-performance capacitive flexible porous GO/PDMS pressure sensors.

Understanding Reasons for Vaccination Hesitancy and Implementing Effective Countermeasures: An Online Survey of Individuals Unvaccinated against COVID-19.

This online survey of unvaccinated people living in Japan aimed to identify the reasons for declining vaccination and to develop effective countermeasures. We conducted a hierarchical class analysis to classify participants, examine factors influencing their classification, and provide the information they needed about coronavirus disease 2019 (COVID-19) and trusted sources of COVID-19 information for each group. A total of 262 participants were classified into three groups: Group 1 with no specific reason (28 participants, 10.69%); Group 2 with clear concerns about trust in the vaccine (85 participants, 32.44%), and Group 3 with attitudinal barriers, such as distrust of the vaccine and complacency towards COVID-19, and structural barriers, such as vaccination appointments (149 participants, 56.87%). For each group, females tended to be classified in Group 2 more than Group 1 (Odds ratio (OR) [95% confidential intervals (95%CI)] = 1.64 (0.63 to 2.66), p = 0.001) and in Group 3 more than Group 1 (OR [95%CI] = 1.16 (0.19 to 2.12), p = 0.019). The information that the participants wanted to know about COVID-19 was different among each group (Safety: p < 0.001, Efficacy: p < 0.001, Genetic effects: p < 0.001). Those who did not receive the COVID-19 vaccine also had lower influenza vaccination coverage (8.02%). Additionally, 38 participants (14.50%) were subject to social disadvantages because they had not received the COVID-19 vaccine. Countermeasures should be carefully tailored according to the target population, reasons for hesitancy, and specific context. The findings of this study may help develop individualized countermeasures to address vaccine hesitancy.

Case Report: Difficulties faced by a home oxygen therapy patient who died after the Fukushima Daiichi nuclear power plant accident.

Following the Great East Japan Earthquake (GEJE) and the Fukushima Daiichi nuclear power plant accident in 2011, mandatory evacuation orders were issued to residents living near the nuclear power plant in Fukushima prefecture, including some patients receiving home oxygen therapy. Although the vulnerability of patients with home oxygen therapy (one of the population groups most vulnerable to disasters) has been noted, there is little information on the health effects of evacuation in the event of a radiation disaster. A 90-year-old man diagnosed with chronic obstructive pulmonary disease since the age of 70, and lived in a town located approximately 20 km south of the nuclear power plant, died 8 months after the disaster due to worsening health conditions. This case reveals the potential for both physical and psychological burdens experienced by vulnerable groups like patients undergoing home oxygen therapy during evacuations in times of disaster. Although it is only a case report and the information is limited, severe respiratory distress requiring home oxygen therapy may present a significant risk factor for disaster-related deaths, especially in cases where evacuations are prolonged, such as in nuclear disasters. Due to the challenge of obtaining prompt public support immediately after a disaster, home oxygen therapy patients may need to prioritize self-help and mutual assistance in their disaster preparedness efforts.

Long-term evacuation and obesity: a 12-year follow-up comparative study of residents inside and outside Katsurao Village after the Fukushima nuclear disaster.

Objective: Evacuation, owing to a disaster, impacts various aspects of an individual's life, including health status. This study aimed to determine the prevalence of obesity among residents of Katsurao Village, Fukushima Prefecture, after the evacuation order due to the Fukushima nuclear disaster in 2011 was lifted in 2016 and to compare the prevalence of obesity by place of residence (inside or outside the village). Methods: The number of examinees, sex, age, place of residence, body mass index (BMI), exercise habits, smoking habits, drinking habits, and dietary status were extracted from the results of health checkups since 2016. We compared the BMI of the indigenes of Katsurao Village by place of residence (inside or outside the village) over time. Results: Although 7 years have passed since 2016, ~70% of the registered residents of Katsurao Village still live outside the village. The obesity rates have consistently been higher among people living outside the village compared to those inside, and the place of residence was the only factor significantly associated with obesity. Conclusion: The findings of this study suggest early intervention is necessary to prevent health risks associated with disaster evacuation if the evacuation period is prolonged.

SARS-CoV-2 spike protein antibody titers after the fourth dose of BNT162b2 vaccine among Japanese patients undergoing hemodialysis: a single-center study.

Patients undergoing hemodialysis are particularly vulnerable to severe outcomes of SARS-CoV-2 infection, with mortality rates higher than that of the general population. Vaccination reduces the risk of adverse outcomes, with booster doses being particularly beneficial. However, limited data are available on the effectiveness of subsequent vaccinations or their effect on increasing antibody levels. This single-center study aimed to investigate changes in SARS-CoV-2 IgG antibody titers following the fourth vaccination among 28 patients undergoing hemodialysis. Blood tests were conducted at various intervals post-vaccination, with a focus on identifying factors associated with antibody levels. The IgG antibody levels rapidly increased by Day 7 post-vaccination, with a median time to peak of 11 days. Antibody titers tended to be higher in male patients than in female patients. This study sheds light on the immune response to the fourth vaccination in patients undergoing hemodialysis. As this study included a small sample size, with a short observation period, further research is warranted to comprehensively understand the effectiveness of vaccination and the benefits of additional doses of vaccine.

Group of longitudinal adverse event patterns after the fourth dose of COVID-19 vaccination with a latent class analysis.

Introduction: Vaccination has been implemented as a useful measure to combat the COVID-19 pandemic. However, there is a tendency for individuals to avoid vaccination due to the possibility of adverse events, making it important to investigate the relationship between COVID-19 vaccines and their adverse events. This study explored longitudinal adverse event patterns and factors that influence adverse events following the second to fourth doses of the COVID-19 vaccine through a latent class analysis. Methods: Participants were recruited from the Fukushima Prefecture and included individuals who had completed four doses of the COVID-19 mRNA vaccine. This study utilized data from questionnaire surveys and blood collection conducted between September 2021 and November 2022. In the questionnaire, factors such as sex, age, medical history, medication, type of vaccine administered, and adverse events following vaccination were recorded. Additionally, in the blood data, serological tests [IgG(S)] and cellular immune responses (T-spot) were measured. Descriptive statistics, latent class analysis, multivariable logistic regression, and multiple regression analyses were performed to identify the longitudinal adverse event patterns and influencing factors. By analyzing adverse events over time, we identified two distinct groups: those less prone to experiencing adverse events (Group 1) and those more susceptible (Group 2) to latent class analysis. Results: A total of 1,175 participants were included after excluding those without any adverse events. The median age of the participants in Group 1 was 70 years, and in Group 2 it was 51 years. The proportion of female participants was 298 in Group 1 and 353 in Group 2. Patients in Group 2 were significantly younger (p < 0.001) and more likely to be female (p < 0.001) than those in Group 1. Furthermore, the median IgG(S) value after the fourth vaccination was 3,233 AU/mL in Group 1 and 4,059.39 AU/mL in Group 2. The median T-spot value was 15.4 in Group 1 and 28.5 in Group 2. Group 2 showed significantly higher IgG(S) and T-spot values after the fourth vaccination (p < 0.001). Discussion: Our findings suggest that factors other than age, particularly sex and a history of allergies, significantly influence the likelihood of experiencing adverse events. Groups categorized by latent class analysis for longitudinal adverse events are expected to be valuable for optimizing vaccination strategies and formulating public health measures.

Diminished neutralizing activity against the XBB1.5 strain in 55.9% of individuals post 6 months COVID-19 mRNA booster vaccination: insights from a pseudovirus assay on 1,353 participants in the Fukushima vaccination community survey, Japan.

This study investigates the neutralizing activity against the XBB1.5 variant and the ancestral strain in a population post-bivalent vaccination using a pseudo virus assay validated with authentic virus assay. While bivalent booster vaccination and past infections enhanced neutralization against the XBB 1.5 strain, individuals with comorbidities showed reduced responses. The study suggests the need for continuous vaccine updates to address emerging SARS-CoV-2 variants and highlights the importance of monitoring real-world immune responses.

Predicting CKD progression using time-series clustering and light gradient boosting machines.

Predicting the transition of kidney function in chronic kidney disease is difficult as specific symptoms are lacking and often overlooked, and progress occurs due to complicating factors. In this study, we applied time-series cluster analysis and a light gradient boosting machine to predict the trajectories of kidney function in non-dialysis dependent chronic kidney disease patients with baseline estimated glomerular filtration rate (GFR) ≥ 45 mL/min/1.73 m2. Based on 5-year changes in estimated GFR, participants were stratified into groups with similar trajectories by cluster analysis. Next, we applied the light gradient boosting machine algorithm and Shapley addictive explanation to develop a prediction model for clusters and identify important parameters for prediction. Data from 780 participants were available for analysis. Participants were classified into five classes (Class 1: n = 78, mean [± standard deviation] estimated GFR 100 ± 19.3 mL/min/1.73 m2; Class 2: n = 176, 76.0 ± 9.3 mL/min/1.73 m2; Class 3: n = 191, 59.8 ± 5.9 mL/min/1.73 m2; Class 4: n = 261, 52.7 ± 4.6 mL/min/1.73 m2; and Class 5: n = 74, 53.5 ± 12.0 mL/min/1.73 m2). Declines in estimated GFR were 8.9% in Class 1, 12.2% in Class 2, 4.9% in Class 3, 12.0% in Class 4, and 45.1% in Class 5 during the 5-year period. The accuracy of prediction was 0.675, and the top three most important Shapley addictive explanation values were 1.61 for baseline estimated GFR, 0.12 for hemoglobin, and 0.11 for body mass index. The estimated GFR transition of patients with preserved chronic kidney disease mostly depended on baseline estimated GFR, and the borderline for estimated GFR trajectory was nearly 50 mL/min/1.73 m2.

Categorization of disaster-related deaths in Minamisoma city after the Fukushima nuclear disaster using clustering analysis.

The medical situation during disasters often differs from that at usual times. Disasters can lead to significant mortality that can be difficult to monitor. The types of disaster-related deaths are largely unknown. In this study, we conducted a survey to categorize the disaster-related deaths caused by a radiation disaster. A total of 520 people living in Minamisoma City, Fukushima Prefecture, at the time of the Fukushima Daiichi Nuclear Power Plant accident, who were certified to have died due to disaster-related causes were surveyed. We divided the participants into those who were at home at the time of the earthquake and those who were in hospitals or facilities when the disaster struck and conducted a hierarchical cluster analysis of the two groups. Disaster-related deaths could be divided into seven groups for those who were at home at the time of the disaster and five groups for those who were in hospitals or facilities at the time of the disaster. Each group showed different characteristics, such as "the group with disabilities," "the group receiving care," and "the group with depression," and it became evident that not only uniform post-disaster support, but support tailored to the characteristics of each group is necessary.

Modeling and predicting individual variation in COVID-19 vaccine-elicited antibody response in the general population.

As we learned during the COVID-19 pandemic, vaccines are one of the most important tools in infectious disease control. To date, an unprecedentedly large volume of high-quality data on COVID-19 vaccinations have been accumulated. For preparedness in future pandemics beyond COVID-19, these valuable datasets should be analyzed to best shape an effective vaccination strategy. We are collecting longitudinal data from a community-based cohort in Fukushima, Japan, that consists of 2,407 individuals who underwent serum sampling two or three times after a two-dose vaccination with either BNT162b2 or mRNA-1273. Using the individually reconstructed time courses of the vaccine-elicited antibody response based on mathematical modeling, we first identified basic demographic and health information that contributed to the main features of the antibody dynamics, i.e., the peak, the duration, and the area under the curve. We showed that these three features of antibody dynamics were partially explained by underlying medical conditions, adverse reactions to vaccinations, and medications, consistent with the findings of previous studies. We then applied to these factors a recently proposed computational method to optimally fit an "antibody score", which resulted in an integer-based score that can be used as a basis for identifying individuals with higher or lower antibody titers from basic demographic and health information. The score can be easily calculated by individuals themselves or by medical practitioners. Although the sensitivity of this score is currently not very high, in the future, as more data become available, it has the potential to identify vulnerable populations and encourage them to get booster vaccinations. Our mathematical model can be extended to any kind of vaccination and therefore can form a basis for policy decisions regarding the distribution of booster vaccines to strengthen immunity in future pandemics.

A Generic Graph-Based Neural Architecture Encoding Scheme With Multifaceted Information.

Neural architecture search (NAS) can automatically discover well-performing architectures in a large search space and has been shown to bring improvements to various applications. However, the computational burden of NAS is huge, since exploring a large search space can need evaluating more than thousands of architecture samples. To improve the sample efficiency of search space exploration, predictor-based NAS methods learn a performance predictor of architectures, and utilize the predictor to sample worth-evaluating architectures. The encoding scheme of NN architectures is crucial to the predictor's generalization ability, and thus crucial to the efficacy of the NAS process. To this end, we have designed a generic Graph-based neural ArchiTecture Encoding Scheme (GATES), a more reasonable modeling of NN architectures that mimics their data processing. Nevertheless, GATES is unaware of the concrete computing semantic of NN operations or architectures. Thus, the learning of operation embeddings and weights in GATES can only exploit the information in architectures-performance pairs. We propose GATES++, which incorporates multifaceted information about NN's operation-level and architecture-level computing semantics into its construction and training, respectively. Experiments on benchmark search spaces show that both the operation-level and architecture-level information can bring improvements alone, and GATES++ can discover better architectures after evaluating the same number of architectures.