高校心理健康教育内容论略

根据社会形势对人才提出的新要求,结合大学生的身心特点和心理现状,高校的心理健康教育,应着力于心理健康知识、心理调适方法和心理疾病的防治等方面。     

Dementia Problem Behavior and the Production of Informal Caregiving Services

Informal caregivers of individuals with Alzheimer's disease spend a considerable amount of time providing care. In this paper, we use Grossman's health production and Becker's time allocation models to develop a model of informal care provision to elderly dementia patients. In our model, time inputs produce caregiving services, which provides utility to the caregiver, but reduces leisure. We assume that time is less productive of services on the margin as the disease progresses. In this framework, an increase in patients' disease severity does not necessarily increase informal caregiver time input. The cost of formal care establishes a reservation price for informal caregiving. When the costs of informal caregiving rise above this reservation level, the patient is institutionalized. We test empirically the effect of deterioration in the patients' condition, proxied by both disease severity and dementia problem behavior, on informal caregiving time. We find that dementia-related problem behaviors and functional limitations significantly increase inputs of informal caregiving time. Patients' problem behavior exerts a modifying effect on functional limitations, and patients' comorbidities have no effect on informal caregiving time.     

On Block Updating in Markov Random Field Models for Disease Mapping

Gaussian Markov random field (GMRF) models are commonly used to model spatial correlation in disease mapping applications. For Bayesian inference by MCMC, so far mainly single-site updating algorithms have been considered. However, convergence and mixing properties of such algorithms can be extremely poor due to strong dependencies of parameters in the posterior distribution. In this paper, we propose various block sampling algorithms in order to improve the MCMC performance. The methodology is rather general, allows for non-standard full conditionals, and can be applied in a modular fashion in a large number of different scenarios. For illustration we consider three different applications: two formulations for spatial modelling of a single disease (with and without additional unstructured parameters respectively), and one formulation for the joint analysis of two diseases. The results indicate that the largest benefits are obtained if parameters and the corresponding hyperparameter are updated jointly in one large block. Implementation of such block algorithms is relatively easy using methods for fast sampling of Gaussian Markov random fields ( Rue, 2001 ). By comparison, Monte Carlo estimates based on single-site updating can be rather misleading, even for very long runs. Our results may have wider relevance for efficient MCMC simulation in hierarchical models with Markov random field components.     

生猪疫病对猪肉贸易的影响及对中国的启示——来自台湾的口蹄疫案例

用台湾爆发口蹄疫的案例实证演绎了生猪传染性疫病对猪肉贸易的重大影响。研究认为:疫病预防和控制以及国际认可、国家兽医体制的控制能力以及生猪适度规模饲养是猪肉贸易健康发展的关键因素,因此,作为养猪大国的中国,必须吸取国际经验,完善生猪疫病预防和控制,促进猪肉贸易发展。     

A Quantitative Assessment of the Risks from Illegally Imported Meat Contaminated with Foot and Mouth Disease Virus to Great Britain

Foot and mouth disease (FMD) is considered by many as the most important animal disease in the world. FMD is highly contagious and outbreaks incur significant costs as affected countries are severely limited in their ability to trade. A number of trade commodities may be contaminated with FMD virus (FMDV) including animal products, for example, meat. As a member of the European Union, Great Britain (GB) has put in place a number of regulations to prevent the importation of pathogens in imported meat products. However, the illegal importation of meat provides a route by which safety controls may be circumvented and meat from FMD affected areas may be imported. This study assesses the FMD infection risk posed to the livestock population of GB from the illegal importation of meat, and estimates the major contributors to this overall risk, through the development of a quantitative risk assessment model. From model results, the total amount of illegal meat entering GB each year is estimated on average to be 11,875 tonnes. with 90% certainty that this is between 4,398 and 28,626 tonnes per year; of which between 64.5 and 565 kg are contaminated with FMDV. This flow of illegal meat results in an estimate of a frequency of FMD infection in GB livestock of 0.015 cases of infected animals per year, with 90% certainty it is between 0.0017 and 0.053. Imports from the region Near and Middle East account for 47% of this risk, and 68% of the risk is attributed to bone-in and dried de-boned products.     

Efficient heterogeneous sampling for stochastic simulation with an illustration in health care applications

In modeling disease transmission, contacts are assumed to have different infection rates. A proper simulation must model the heterogeneity in the transmission rates. In this article, we present a computationally efficient algorithm that can be applied to a population with heterogeneous transmission rates. We conducted a simulation study to show that the algorithm is more efficient than other algorithms for sampling the disease transmission in a subset of the heterogeneous population. We use a valid stochastic model of pandemic influenza to illustrate the algorithm and to estimate the overall infection attack rates of influenza A (H1N1) in a Canadian city.     

Overcoming the ‘tyranny of the urgent’: integrating gender into disease outbreak preparedness and response

ABSTRACT

This article contributes to discussions on the gender dimensions of disease outbreaks, and preparedness policies and responses, by providing a multi-level analysis of gender-related gaps, particularly illustrating how the failure to challenge gender assumptions and incorporate gender as a priority at the global level has national and local impacts. The implications of neglecting gender dynamics, as well as the potential of equity-based approaches to disease outbreak responses, is illustrated through a case study of the Social Enterprise Network for Development (SEND) Sierra Leone, a non-government organisation (NGO) based in Kailahun, during the Ebola outbreak.     

Combining QMRA and Epidemiology to Estimate Campylobacteriosis Incidence

The disease burden of pathogens as estimated by QMRA (quantitative microbial risk assessment) and EA (epidemiological analysis) often differs considerably. This is an unsatisfactory situation for policymakers and scientists. We explored methods to obtain a unified estimate using campylobacteriosis in the Netherlands as an example, where previous work resulted in estimates of 4.9 million (QMRA) and 90,600 (EA) cases per year. Using the maximum likelihood approach and considering EA the gold standard, the QMRA model could produce the original EA estimate by adjusting mainly the dose‐infection relationship. Considering QMRA the gold standard, the EA model could produce the original QMRA estimate by adjusting mainly the probability that a gastroenteritis case is caused by Campylobacter. A joint analysis of QMRA and EA data and models assuming identical outcomes, using a frequentist or Bayesian approach (using vague priors), resulted in estimates of 102,000 or 123,000 campylobacteriosis cases per year, respectively. These were close to the original EA estimate, and this will be related to the dissimilarity in data availability. The Bayesian approach further showed that attenuating the condition of equal outcomes immediately resulted in very different estimates of the number of campylobacteriosis cases per year and that using more informative priors had little effect on the results. In conclusion, EA was dominant in estimating the burden of campylobacteriosis in the Netherlands. However, it must be noted that only statistical uncertainties were taken into account here. Taking all, usually difficult to quantify, uncertainties into account might lead to a different conclusion.     

Healthy Barbs: Activism Confronts Mortality

Barbara Brenner, JD, was the Executive Director of Breast Cancer Action (BCA) from 1995–2010. Before that, she was a longtime activist in the anti-war movement and an attorney who, for most of her career, practiced public policy law. After she was diagnosed with breast cancer in 1993 at the age of 41, she took the helm of BCA. Under her leadership, the organization moved into a position of national advocacy—demanding research on the causes and prevention of breast cancer, including the role of industrial pollutants. Barbara started the “Think Before You Pink” campaign, encouraging people to question whether companies that display pink ribbons actually produce products that harm women's health or generate any funds to fight breast cancer. Her blog, “Healthy Barbs,” challenged readers to critique routine healthcare practices and policies. Barbara received numerous awards, including a Jefferson Award for Public Service in 2007, the Smith College Medal in 2012, and the ACLU-Northern California's Lola Hanzel Courageous Advocacy Award in 2012. Barbara had a recurrence of breast cancer in 1996. She died of complications associated with amyotrophic lateral sclerosis, ALS, on May 10, 2013.     

An Ecological Model for Quantitative Risk Assessment for Schistosomiasis: The Case of a Patchy Environment in the Coastal Tropical Area of Northeastern Brazil

We developed a stochastic model for quantitative risk assessment for the Schistosoma mansoni (SM) parasite, which causes an endemic disease of public concern. The model provides answers in a useful format for public health decisions, uses data and expert opinion, and can be applied to any landscape where the snail Biomphalaria glabrata is the main intermediate host (South and Central America, the Caribbean, and Africa). It incorporates several realistic and case‐specific features: stage‐structured parasite populations, periodic praziquantel (PZQ) drug treatment for humans, density dependence, extreme events (prolonged rainfall), site‐specific sanitation quality, environmental stochasticity, monthly rainfall variation, uncertainty in parameters, and spatial dynamics. We parameterize the model through a real‐world application in the district of Porto de Galinhas (PG), one of the main touristic destinations in Brazil, where previous studies identified four parasite populations within the metapopulation. The results provide a good approximation of the dynamics of the system and are in agreement with our field observations, i.e., the lack of basic infrastructure (sanitation level and health programs) makes PG a suitable habitat for the persistence and growth of a parasite metapopulation. We quantify the risk of SM metapopulation explosion and quasi‐extinction and the time to metapopulation explosion and quasi‐extinction. We evaluate the sensitivity of the results under varying scenarios of future periodic PZQ treatment (based on the Brazilian Ministry of Health's plan) and sanitation quality. We conclude that the plan might be useful to slow SM metapopulation growth but not to control it. Additional investments in better sanitation are necessary.