College and University Health Care Professionals: An Expanding Team

Abstract

Factors contributing to students' compliance with mass vaccination programs during meningococcal outbreaks have not been well described. A 1997 mass vaccination campaign at Michigan State University provided an opportunity to study such factors. Of 34 024 students in the target population, 17 538 (51.5%) were vaccinated in 5 days. Vaccination rates were higher for women (47.9%) than for men (43.1 %) and higher for on-campus residents (65.3%) than for off-campus residents (35.6%). For each year of students' age beyond 19, the adjusted odds of vaccination were reduced by 0.82. Adjusted odds ratios for vaccination, with White students as the reference group at 1.0, were 1.33 for Asian American students, 0.97 (not significant) for Hispanic students, 0.82 for African American students, and 0.80 for Native American students. Students from the Colleges of Business, Engineering, Communication, and Natural Science had the highest vaccination rates; those from the College of Arts and Letters had the lowest rates.     

Waterborne Disease‐Related Risk Perceptions in the Sonora River Basin,Mexico

Waterborne disease is estimated to cause about 10% of all diseases worldwide. However, related risk perceptions are not well understood, particularly in the developing world where waterborne disease is an enormous problem. We focus on understanding risk perceptions related to these issues in a region within northern Mexico. Our findings show how waterborne disease problems and solutions are understood in eight small communities along a highly contaminated river system. We found major differences in risk perceptions between health professionals, government officials, and lay citizens. Health professionals believed that a high level of human‐waste‐related risk existed within the region. Few officials and lay citizens shared this belief. In addition, few officials and lay citizens were aware of poor wastewater‐management‐related disease outbreaks and water contamination. Finally, aside from health professionals, a few interviewees understood the importance of basic hygiene and water treatment measures that could help to prevent disease. Our results add to the literature on environmentally‐related risk perceptions in the developing world. We discuss recommendations for improving future human‐wastewater‐related risk communication within the region.     

神经分子生物学的发展

分子生物学的崛起改变了神经科学研究的进程。本文回顾了神经分子生物学40年的发展里程,分析了脑的1O年工程研究和焦点。展望了未来30年该领域发展趋势。     

民族地区公共卫生服务体系的完善

突如其来的新冠肺炎疫情让我们继2003年非典之后再次与传染性疾病正面遭遇,也让我们反思当下的公共卫生体系,尤其是公共卫生服务相对薄弱却面临更大的境外输入风险的民族地区,需要如何提升才能应对此次疫情和日后可能出现的其他公共卫生突发事件的冲击。少数民族地区的经济发展状况、地处边境或边疆地区等独特的自然地理环境和社会景观、恶劣的气候和不方便的交通运输,给大流行防控带来了较大的压力,也在一定程度上影响了公共卫生服务的可及性。少数民族地区的公共卫生体系与其他地区相比仍然相对薄弱,城乡不平衡仍然存在。回顾1949年中华人民共和国成立以来公共卫生体系的发展历程,我们会发现,我们积累了预防为主的政策等宝贵经验,也走过了过度市场化的弯路。因此,总结经验,吸取教训,结合少数民族地区的实际,明确政府、社会和公民在公共卫生服务体系中各自的定位、作用和责任,坚持预防为主的原则,加强国际合作,都是完善少数民族地区公共卫生体系的重要内容。     

论《沉沦》的“病态叙事”

试图通过对《沉沦》中郁达夫有意识无意识的“病态叙事”,来发掘小说的深刻内蕴;指出在郁达夫的作品中,主人公大都是“有病”的人,作者采取了“病态叙事”这种方式来展现和表达自己的内心痛苦,从而揭示五四一代先进知识分子普遍的痛苦和绝望。     

性病隐喻与两性身体叙事——中国现代文学中的“性病”意象探析

性病是中国现代文学中最典型的疾病意象之一,对性病的关注涉及对妓女生活的想象,而性别文化身份的差异在对妓女的叙事上体现为两种不同的身体叙事方式。男性主体的中心意识使文学创作更多地表现为人民伦理的宏大叙事,体现着“民族一国家”的“大意义”;女性的历史边缘处境使女性书写更多地呈现为自由伦理的私人叙事,作为一种“小意义”而存在着。对于文学作品中出现的性病,宏大叙事侧重于把女性身体编织进政治、道德、历史的意义圈,强调女性身体的公共性;私人叙事强调性病之于女性的私人经验,呈现女性身体的私人性。     

Quantitative Risk Assessment for Bovine Spongiform Encephalopathy in Low- or Zero-Prevalence Countries: The Example of Norway

A predictive case-cohort model is applied to Norwegian data to analyze the interaction between challenge and stability factors for bovine spongiform encephalopathy (BSE) during the period 1980-2010. For each year, the BSE risk in cattle is estimated as the expected number of cases. The age distribution of expected cases as well as the relative impact of different challenges is estimated. The model consists of a simple, transparent, and practical deterministic spreadsheet calculation model, in which the following country-specific inputs are entered: (i) annual imports of live cattle and meat and bone meal, (ii) age distribution of native cattle, and (iii) estimated annual basic reproduction ratio (R(0)) for BSE. Results for Norway indicate that the highest risk of BSE cases was in 1989, when a total BSE risk of 0.13 cases per year was expected. After that date, the year-to-year decrease in risk ranged between 3% and 47%, except for a secondary peak in 1994 at 0.06 cases per year. The primary peak was almost entirely (99%) attributable to the importation of 11 cattle from the United Kingdom between 1982 and 1986. The secondary peak, in 1994, originated mainly from the recycling of the U.K. imported cattle (92%). In 2006, the remaining risk was 0.0003 cases per year, or 0.001 per million cows per year, with a maximal age-specific incidence of 0.03 cases per million per year in 10-year-old cattle. Only 15% of the cases were expected in imported cattle. The probability of having zero cases in Norway in 2006 was estimated to be 99.97%. The model and results are compared to previous risk assessments of Norway by the EU.     

Development and Consideration of Global Policies for Managing the Future Risks of Poliovirus Outbreaks: Insights and Lessons Learned Through Modeling

The success of the Global Polio Eradication Initiative promises to bring large benefits, including sustained improvements in quality of life (i.e., cases of paralytic disease and deaths avoided) and costs saved from cessation of vaccination. Obtaining and maintaining these benefits requires that policymakers manage the transition from the current massive use of oral poliovirus vaccine (OPV) to a world without OPV and free of the risks of potential future reintroductions of live polioviruses. This article describes the analytical journey that began in 2001 with a retrospective case study on polio risk management and led to development of dynamic integrated risk, economic, and decision analysis tools to inform global policies for managing the risks of polio. This analytical journey has provided several key insights and lessons learned that will be useful to future analysts involved in similar complex decision-making processes.     

Discovering Spatio-Temporal Models of the Spread of West Nile Virus

Emerging infectious diseases are characterized by complex interactions among disease agents, vectors, wildlife, humans, and the environment. Since the appearance of West Nile virus (WNV) in New York City in 1999, it has infected over 8,000 people in the United States, resulting in several hundred deaths in 46 contiguous states. The virus is transmitted by mosquitoes and maintained in various bird reservoir hosts. Its unexpected introduction, high morbidity, and rapid spread have left public health agencies facing severe time constraints in a theory-poor environment, dependent largely on observational data collected by independent survey efforts and much uncertainty. Current knowledge may be expressed as a priori constraints on models learned from data. Accordingly, we applied a Bayesian probabilistic relational approach to generate spatially and temporally linked models from heterogeneous data sources. Using data collected from multiple independent sources in Maryland, we discovered the integrated context in which infected birds are plausible indicators for positive mosquito pools and human cases for 2001 and 2002.     

Using repeated-prevalence data in multi-state modeling of renal replacement therapy

Multi-state models help predict future numbers of patients requiring specific treatments but these models require exhaustive incidence data. Deriving reliable predictions from repeated-prevalence data would be helpful. A new method to model the number of patients that switch between therapeutic modalities using repeated-prevalence data is presented and illustrated. The parameters and goodness of fit obtained with the new method and repeated-prevalence data were compared to those obtained with the classical method and incidence data. The multi-state model parameters’ confidence intervals obtained with annually collected repeated-prevalence data were wider than those obtained with incidence data and six out of nine pairs of confidence intervals did not overlap. However, most parameters were of the same order of magnitude and the predicted patient distributions among various renal replacement therapies were similar regardless of the type of data used. In the absence of incidence data, a multi-state model can still be successfully built with annually collected repeated-prevalence data to predict the numbers of patients requiring specific treatments. This modeling technique can be extended to other chronic diseases.