Kinetics of humoral and cellular immune responses 5 months post-COVID-19 booster dose by immune response groups at the peak immunity phase: An observational historical cohort study using the Fukushima vaccination community survey.

Background: Understanding the waning of immunity after booster vaccinations is important to identify which immune-low populations should be prioritized. Methods: We investigated longitudinal cellular and humoral immunity after the third vaccine dose in both high- and low-cellular and humoral immunity groups at the peak immunity phase after the booster vaccination in a large community-based cohort. Blood samples were collected from 1045 participants at peak (T1: median 54 days post-third dose) and decay (T2: median 145 days post-third dose) phases to assess IgG(S), neutralizing activity, and ELISpot responses. Participants were categorized into high/low ELISpot/IgG(S) groups at T1. Cellular and humoral responses were tracked for approximately five months after the third vaccination. Results: In total, 983 participants were included in the cohort. IgG(S) geometric mean fold change between timepoints revealed greater waning in the >79 years age group (T2/T1 fold change: 0.27) and higher IgG(S) fold change in the low-ELISpot group at T1 (T2/T1 fold change: 0.32-0.33) than in the other groups, although ELISpot geometric mean remained stable. Conclusions: Antibody level of those who did not respond well to third dose vaccination waned rapidly than those who responded well. Evidence-based vaccine strategies are essential in preventing potential health issues caused by vaccines, including side-effects.

Impact of the Great East Japan Earthquake followed by the nuclear power plant accident on the nursing students' academic progress in Soma, Fukushima, Japan: a retrospective cohort study with questionnaire survey.

BACKGROUND: The Great East Japan Earthquake and the subsequent Fukushima nuclear power plant accident in 2011 posed significant challenges to the educational sector, particularly affecting nursing students in the disaster area. However, to the best of our knowledge, there are no reports on the effects of the natural disaster coupled with the nuclear accident on the nursing students. Therefore, this study aimed to determine the impact of the Fukushima disasters on rate of academic failure events in nursing education. METHODS: A retrospective cohort approach was conducted, focusing on 677 students from Soma Nursing School admitted between 2001 and 2017. Four failure events-failure to pass the national examination, student retention, suspension, and withdrawal from school-were compared between three time periods: pre-disaster, early peri-disaster, and later peri-disaster. This analysis was followed by a questionnaire survey among the students and an interview with faculty members to gain further insights. RESULTS: Of the student cohort, 17% had at least one failure event. Students in the later peri-disaster phase faced an elevated failure rate at 29%. Variables such as being male, admission during later peri-disaster period, and local pre-admission residence played a significant role in these failure events in multivariate logistic regression analysis (adjusted odds ratio [95% confidence interval, p value]; 2.63 [1.49-4.64, < 0.001], 3.207 [2.00-5.15, < 0.001], and 1.84 [1.12-3.02, 0.02], respectively). CONCLUSIONS: This study highlights the impact of the Great East Japan Earthquake and the following nuclear accident on nursing education. The elevated failure rates in the later peri-disaster period emphasize the challenges posed by continuing disaster phases. Thus, there is a need for intensified and tailored strategies in nursing education in disaster-affected regions.

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.

Risk Index of Regional Infection Expansion of COVID-19: Moving Direction Entropy Study Using Mobility Data and Its Application to Tokyo.

BACKGROUND: Policies, such as stay home, bubbling, and stay with your community, recommending that individuals reduce contact with diverse communities, including families and schools, have been introduced to mitigate the spread of the COVID-19 pandemic. However, these policies are violated if individuals from various communities gather, which is a latent risk in a real society where people move among various unreported communities. OBJECTIVE: We aimed to create a physical index to assess the possibility of contact between individuals from diverse communities, which serves as an indicator of the potential risk of SARS-CoV-2 spread when considered and combined with existing indices. METHODS: Moving direction entropy (MDE), which quantifies the diversity of moving directions of individuals in each local region, is proposed as an index to evaluate a region's risk of contact of individuals from diverse communities. MDE was computed for each inland municipality in Tokyo using mobility data collected from smartphones before and during the COVID-19 pandemic. To validate the hypothesis that the impact of intercommunity contact on infection expansion becomes larger for a virus with larger infectivity, we compared the correlations of the expansion of infectious diseases with indices, including MDE and the densities of supermarkets, restaurants, etc. In addition, we analyzed the temporal changes in MDE in municipalities. RESULTS: This study had 4 important findings. First, the MDE values for local regions showed significant invariance between different periods according to the Spearman rank correlation coefficient (>0.9). Second, MDE was found to correlate with the rate of infection cases of COVID-19 among local populations in 53 inland regions (average of 0.76 during the period of expansion). The density of restaurants had a similar correlation with COVID-19. The correlation between MDE and the rate of infection was smaller for influenza than for COVID-19, and tended to be even smaller for sexually transmitted diseases (order of infectivity). These findings support the hypothesis. Third, the spread of COVID-19 was accelerated in regions with high-rank MDE values compared to those with high-rank restaurant densities during and after the period of the governmental declaration of emergency (P<.001). Fourth, the MDE values tended to be high and increased during the pandemic period in regions where influx or daytime movement was present. A possible explanation for the third and fourth findings is that policymakers and living people have been overlooking MDE. CONCLUSIONS: We recommend monitoring the regional values of MDE to reduce the risk of infection spread. To aid in this monitoring, we present a method to create a heatmap of MDE values, thereby drawing public attention to behaviors that facilitate contact between communities during a highly infectious disease pandemic.

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.

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.

Evaluating ChatGPT's effectiveness and tendencies in Japanese internal medicine.

INTRODUCTION: ChatGPT, a large-scale language model, is a notable example of AI's potential in health care. However, its effectiveness in clinical settings, especially when compared to human physicians, is not fully understood. This study evaluates ChatGPT's capabilities and limitations in answering questions for Japanese internal medicine specialists, aiming to clarify its accuracy and tendencies in both correct and incorrect responses. METHODS: We utilized ChatGPT's answers on four sets of self-training questions for internal medicine specialists in Japan from 2020 to 2023. We ran three trials for each set to evaluate its overall accuracy and performance on nonimage questions. Subsequently, we categorized the questions into two groups: those ChatGPT consistently answered correctly (Confirmed Correct Answer, CCA) and those it consistently answered incorrectly (Confirmed Incorrect Answer, CIA). For these groups, we calculated the average accuracy rates and 95% confidence intervals based on the actual performance of internal medicine physicians on each question and analyzed the statistical significance between the two groups. This process was then similarly applied to the subset of nonimage CCA and CIA questions. RESULTS: ChatGPT's overall accuracy rate was 59.05%, increasing to 65.76% for nonimage questions. 24.87% of the questions had answers that varied between correct and incorrect in the three trials. Despite surpassing the passing threshold for nonimage questions, ChatGPT's accuracy was lower than that of human specialists. There was a significant variance in accuracy between CCA and CIA groups, with ChatGPT mirroring human physician patterns in responding to different question types. CONCLUSION: This study underscores ChatGPT's potential utility and limitations in internal medicine. While effective in some aspects, its dependence on question type and context suggests that it should supplement, not replace, professional medical judgment. Further research is needed to integrate Artificial Intelligence tools like ChatGPT more effectively into specialized medical practices.

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.

Idobata-Nagaya: a community housing solution for socially isolated older adults following the great East Japan earthquake.

Introduction: Following the Great East Japan Earthquake, the living environment of socially isolated older adults has become a pressing concern. In response, Nagaya, a collective housing program, was established in Soma City, Fukushima, Japan to address social isolation among older adults and support their long-term health. This study aimed to identify characteristics of individuals in Nagaya and examine the sustainability of this initiative. Methods: We conducted a retrospective analysis of residents who were relocated to Nagaya, emphasizing their characteristics, the continuity of their stay in Nagaya, and their care certification levels, using data up to December 31, 2022. We employed Kaplan-Meier curves to analyze the duration for which residents continued to reside in Nagaya and the time leading up to the requiring care-level certification. Results: Of 65 people who moved to Nagaya after the disaster, 30 people (46.2%) continued to live there, 21 (32.3%) died during their stay, and 14 (21.5%) moved out. The overall duration of occupancy averaged 6.39 years (SD 3.83 years). The proportion of requiring care-level certification occurrences per person-year was 0.0577 for those without care certification and 0.3358 for those with requiring support level at the time of moving in. Conclusion: In summary, Nagaya-style communal housing may offer suitable living environments for older adults with diverse needs during disasters and serve as a valuable tool for developing public policies in aging societies.