A historical analysis of vaccine mandates in the United States military and its application to the COVID-19 vaccine mandate

The Department of Defense has implemented a mandate that all military personnel be vaccinated against COVID-19. This article reviews the historical precedent of vaccine mandates for United States military personnel dating back to the formation of the continental army, as well as previous controversies about vaccine mandates such as the first influenza vaccine mandate and the Anthrax Vaccine Immunization Program. The historical review discusses precedent for the current COVID-19 vaccine mandate and the reception of these vaccine mandates by military personnel. The review then discusses how these historical lessons can inform the present COVID-19 vaccine mandate.     

下一代诊断病理学

随着人类基因组测序、生物大数据信息分析、分子病理检测和人工智能辅助病理诊断等技术进步及其应用, 临床医学发展迈向精准诊疗时代。这一时代背景下, 传统诊断病理学迎来前所未有的历史机遇, 正在向"下一代诊断病理学(next-generation diagnostic pathology)"迈进。下一代诊断病理学以病理形态和临床信息为诊断基础, 以分子检测与生物信息分析、智慧制样与流程质控、智能诊断与远程会诊、病灶活体可视化与"无创"病理诊断等创新前沿交叉技术为主要特征, 以多组学和跨尺度整合诊断为病理报告内容, 实现对疾病的"最后诊断", 并预测疾病演进和结局、建议治疗方案和评估治疗反应, 形成新的疾病诊断"金标准"。未来, 需要激发病理学科创新活力, 加快下一代诊断病理学成熟和应用, 重塑病理学科理论和技术体系, 发挥诊断病理学在疾病"防、诊、治、养"等过程中的重要作用, 促进临床医学进一步发展, 服务健康中国战略。     

Effects of state reinsurance programs on health insurance exchange premiums and insurer participation

Objective

The aim of the study was to estimate the effect of the state-based reinsurance programs through the section 1332 State Innovation Waivers on health insurance marketplace premiums and insurer participation.

Data Source

2015 to 2022 Robert Wood Johnson Foundation Health Insurance Exchange Compare Datasets.

Study Design

An event study difference-in-differences (DD) model separately for each year of implementation and a synthetic control method (SCM) are used to estimate year-by-year effects following program implementation.

Data Collection/Extraction Methods

Not applicable.

Principal Findings

Reinsurance programs were associated with a decline in premiums in the first year of implementation by 10%–13%, 5%–19%, and 11%–17% for bronze, silver, and gold plans (p < 0.05). There is a trend of sustained declines especially for states that implemented their programs in 2019 and 2020. The SCM analyses suggest some effect heterogeneity across states but also premium declines across most states. There is no evidence that reinsurance programs affected insurer participation.

Conclusion

State-based reinsurance programs have the potential to improve the affordability of health insurance coverage. However, reinsurance programs do not appear to have had an effect on insurer participation, highlighting the need for policy makers to consider complementary strategies to encourage insurer participation.     

Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

Mobile daily diaries to characterize stressors and acute health symptoms in an environmental justice neighborhood

Low-income communities and communities of color face multiple, cumulative environmental and social burdens. Methods development in environmental justice research has largely focused on spatial and quantitative approaches. Less attention has been paid to developing methodologies that help collect information on everyday stressors and quality of life experiences for residents in overburdened communities. Mixed methods approaches can be one way to structure study designs that help consider how residents experience environmental and socioeconomic impacts in a localized community context. In neighborhoods burdened by cumulative stressors, traditional cross-sectional epidemiological research designs can also be challenging, as well as limited or narrow in their application. However, repeat sampling of measures within a vulnerable population can approach a quasi-experimental design and help consider variations within residents in a single neighborhood as well as better parse relationships between exposures and outcomes. Through a community-academic partnership with university partners, local community partners, and a local promotores de salud (community health workers) network, we pilot tested a novel mobile daily diary approach in both English and Spanish in an urban, predominantly immigrant community in South Los Angeles as a potential method to collect information on daily stress, environmental quality, and health status/symptoms. We collected resident responses via a once per day 7-day SMS/text messaging survey. We sought to gather granular data on daily resident experiences of air pollution and environmental hazards. Residents reported acute health symptoms and stressors, with repeat measures demonstrating how residents might rank, categorize, or cope with stressors. We find that residents in environmental justice communities record variation in their daily diary responses and document changes in environmental quality, stressors, and odors. Refining this type of method could enable a more rigorous examination of co-occurrences of environmental quality and acute health symptoms. This approach supports the inclusion of residents in the research process and helps more systematically integrate open-ended environmental health relevant data in environmental justice efforts. Used with measured data such as air monitoring or health measures, mixed methods generated data can help support efforts that aim to alleviate sources of daily stress, alongside efforts to reduce overall pollution burdens. Mobile daily diaries can be one way to capture variable responses to environmental quality, acute health symptoms, and stressors.     

北京市三级甲等医院结直肠癌患者就医流向规律分析

目的 分析不同特征的结直肠癌患者就医行为选择在中医院（含中西医结合医院）、西医院及肿瘤专科医院间的差异，为合理引导结直肠癌患者适宜就医及制订相关政策提供依据。方法 收集北京地区2018年1月-2019年12月17家三级甲等医院21894例首诊结直肠癌成年住院患者的病案首页数据，采用EmpowerStats 2.0对数据进行描述性分析。结果 21894例结直肠癌患者中就诊于中医院的有862例（3.93%），西医院的有8723例（39.85%），肿瘤专科医院的有12309例（56.22%）。对于不同医疗机构，男性占比均大于女性，58-68岁患者占比最大。且结直肠癌患者年龄、医疗付款方式及肿瘤分期在不同医疗机构间的分布存在差异（P<0.001）。西医院及肿瘤专科医院结直肠癌Ⅲ期患者占比最大，而就诊于中医院患者中结直肠癌Ⅳ期最多。从地域分布来看，异地就诊比例（57.32%）大于本地，且就诊于肿瘤专科医院的患者中73.66%来自外地。患者来源前三名分别是北京市、河北省及内蒙古自治区。而在北京市内，西医院患者主要来源于朝阳区、海淀区及西城区，中医院患者主要来源于海淀区、朝阳区及丰台区，肿瘤专科医院则主要来源于朝阳区、海淀区及丰台区。结论 应大力倡导年轻以及早期结直肠癌患者向中医院分流，充分施展中医药在结直肠癌患者中的治疗优势；发挥三级医院带动作用，建立对口帮扶医院，减少不必要的跨省流动及提倡结直肠癌的早筛早治，以降低结直肠癌死亡率。