绵阳市水稻主要病虫区域分布及其测报

对绵阳市 1980～ 1999年水稻病虫害发生、为害情况进行了分析、研究 ,初步明确了我市水稻主要病虫及其区域分布 ,据此提出了疫情调查的关键时期、重点区域及调查线路     

A Model for Optimization of Biomarker Testing Frequency to Minimize Disease and Cost: Example of Beryllium Sensitization Testing

A common problem with medical surveillance programs using biomarkers is determining the optimal frequency of testing to minimize adverse health effects and cost. In the case of beryllium-exposed workers, frequency of testing for beryllium sensitization may be especially important. Recent studies indicate a lack of dose response for beryllium sensitization, but do support a dose response for the development of chronic beryllium disease (CBD). Though unproven, this implies that early identification of sensitization and immediate removal from exposure may reduce development of CBD. A model is proposed to project the optimal frequency of sensitization testing using the current beryllium lymphocyte proliferation test (BeLPT) to minimize disease-related costs, assuming that a positive BeLPT will precede CBD. Conversion rates for cumulative exposure to disease development were adapted from the literature and used with testing costs and cost of disease estimates in the model. The model was run assuming several test frequency regimes. Results support the use of periodic testing in line with the annual schedule proposed in the Final Chronic Beryllium Disease Prevention Program Rule (1999) following initial testing within three months of first beryllium exposure. The financial and health benefits of reducing the time from exposure to detection of early disease was also explored with the model and demonstrated as a highly desirable characteristic for an alternative test or improved BeLPT. Limitations of the approach are discussed as well as options for adapting this biomarker optimization methodology to consider biomarkers of other exposure-associated diseases.     

Probability of Exporting Infected Carcasses from Vaccinated Pigs Following a Foot‐and‐Mouth Disease Epidemic

Emergency vaccination is an effective control strategy for foot‐and‐mouth disease (FMD) epidemics in densely populated livestock areas, but results in a six‐month waiting period before exports can be resumed, incurring severe economic consequences for pig exporting countries. In the European Union, a one‐month waiting period has been discussed based on negative test results in a final screening. The objective of this study was to analyze the risk of exporting FMD‐infected pig carcasses from a vaccinated area: (1) directly after final screening and (2) after a six‐month waiting period. A risk model has been developed to estimate the probability that a processed carcass was derived from an FMD‐infected pig (P_carc). Key variables were herd prevalence (P_H), within‐herd prevalence (P_A), and the probability of detection at slaughter (P_SL). P_H and P_A were estimated using Bayesian inference under the assumption that, despite all negative test results, ≥1 infected pigs were present. Model calculations indicated that P_carc was on average 2.0 × 10^?5 directly after final screening, and 1.7 × 10^?5 after a six‐month waiting period. Therefore, the additional waiting time did not substantially reduce P_carc. The estimated values were worst‐case scenarios because only viraemic pigs pose a risk for disease transmission, while seropositive pigs do not. The risk of exporting FMD via pig carcasses from a vaccinated area can further be reduced by heat treatment of pork and/or by excluding high‐risk pork products from export.     

Estimating precision,repeatability, and reproducibility from Gaussian and non- Gaussian data: a mixed models approach

Quality control relies heavily on the use of formal assessment metrics. In this paper, for the context of veterinary epidemiology, we review the main proposals, precision, repeatability, reproducibility, and intermediate precision, in agreement with ISO (international Organization for Standardization) practice, generalize these by placing them within the linear mixed model framework, which we then extend to the generalized linear mixed model setting, so that both Gaussian as well as non-Gaussian data can be employed. Similarities and differences are discussed between the classical ANOVA (analysis of variance) approach and the proposed mixed model settings, on the one hand, and between the Gaussian and non-Gaussian cases, on the other hand. The new proposals are applied to five studies in three diseases: Aujeszky's disease, enzootic bovine leucosis (EBL) and bovine brucellosis. The mixed-models proposals are also discussed in the light of their computational requirements.     

A Literature Review of the Experiences of African American and Caucasian TANF Women Transitioning from Welfare to Work

This study examined African American women's perceptions of their adolescent children's well-being since gaining employment. This study departed from other studies that focused on the entire Temporary Assistance to Needy Families (TANF) population and/or compared subgroups within the population. In this study, the sample population is composed of all African American mothers and all of the mothers receive Temporary Assistance to Needy Families benefits and have gained employment. The study explored the relationship between adult supervision of adolescent children that resided in distressed communities and adolescent overall well-being as measured by academic well-being, emotional well-being, and social well-being.     

Risks of Paralytic Disease Due to Wild or Vaccine-Derived Poliovirus After Eradication

After the global eradication of wild polioviruses, the risk of paralytic poliomyelitis from polioviruses will still exist and require active management. Possible reintroductions of poliovirus that can spread rapidly in unprotected populations present challenges to policymakers. For example, at least one outbreak will likely occur due to circulation of a neurovirulent vaccine-derived poliovirus after discontinuation of oral poliovirus vaccine and also could possibly result from the escape of poliovirus from a laboratory or vaccine production facility or from an intentional act. In addition, continued vaccination with oral poliovirus vaccines would result in the continued occurrence of vaccine-associated paralytic poliomyelitis. The likelihood and impacts of reintroductions in the form of poliomyelitis outbreaks depend on the policy decisions and on the size and characteristics of the vulnerable population, which change over time. A plan for managing these risks must begin with an attempt to characterize and quantify them as a function of time. This article attempts to comprehensively characterize the risks, synthesize the existing data available for modeling them, and present quantitative risk estimates that can provide a starting point for informing policy decisions.     

Interdisciplinary Considerations in the Psychotherapy of Psychosomatic Patients

Abstract

Patients with psychosomatic conditions, who comprise a significant proportion of students seeking health care, demonstrate clearly the need for effective functioning of the health care team. These patients usually present themselves with problems of physical illness for practical, social, and psychodynamic reasons. Socially they seek to avoid the stigma attached to acknowledging psychological problems. Psychodynamically, such patients have transformed psychological problems into physical illness and need help in reversing this transformation. Attending only the physical illness or dismissing the patient because “it's all in your head” are inappropriate responses deeply embedded in popular culture. Case illustrations are used to show the need for careful diagnosis from physical and psychological standpoints, for skillful referral and interdisciplinary collaboration, and to show how psychotherapy can reverse the psychosomatic process and the underlying psychological determinants. The illustrations include cases of headache, asthma, ulcers, and disturbances of sleep and appetite. Both specific psychotherapeutic technique and overall theory are discussed.     

Exploration of associations between governance and economics and country level foot-and-mouth disease status by using Bayesian model averaging

Summary.  Using Bayesian model averaging, we quantify associations of governance and economic health with country level presence of foot-and-mouth disease (FMD) and estimate the probability of the presence of FMD in each country from 1997 to 2005. The Bayesian model averaging accounted for countries' previous FMD status and other possible confounders, as well as uncertainty about the 'true' model, and provided accurate predictions (90% specificity and 80% sensitivity). This model represents a novel approach to predicting FMD, and other conditions, on a global scale and in identifying important risk factors that can be applied to global policy and allocation of resources for disease control.     

Issues Related to HIV Stigma in Nepal

ABSTRACT

We conducted a qualitative study to understand and describe experiences of people living with HIV and AIDS with regard to HIV-associated stigma in Nepal. The study has revealed four key themes associated with HIV stigma: a hierarchy of stigma (sexual transmission and women stigmatized more than injecting-drug transmission and men); exclusion and rejection (denial of care services, rejection from family); death as a form of punishment (untimely death is seen as a punishment for something done wrong in the past); and Mumbaiya disease (caught from working in “other places”). Cultural contexts are the best ways to understand HIV stigma in Nepal along with socially and culturally established gender roles. This study has confirmed that stigma manifests at different levels: individual, social, and structural, with denial and rejection being a key mechanism of stigma.     

Quantitative Risk Assessment from Farm to Fork and Beyond: A Global Bayesian Approach Concerning Food-Borne Diseases

A novel approach to the quantitative assessment of food-borne risks is proposed. The basic idea is to use Bayesian techniques in two distinct steps: first by constructing a stochastic core model via a Bayesian network based on expert knowledge, and second, using the data available to improve this knowledge. Unlike the Monte Carlo simulation approach as commonly used in quantitative assessment of food-borne risks where data sets are used independently in each module, our consistent procedure incorporates information conveyed by data throughout the chain. It allows "back-calculation" in the food chain model, together with the use of data obtained "downstream" in the food chain. Moreover, the expert knowledge is introduced more simply and consistently than with classical statistical methods. Other advantages of this approach include the clear framework of an iterative learning process, considerable flexibility enabling the use of heterogeneous data, and a justified method to explore the effects of variability and uncertainty. As an illustration, we present an estimation of the probability of contracting a campylobacteriosis as a result of broiler contamination, from the standpoint of quantitative risk assessment. Although the model thus constructed is oversimplified, it clarifies the principles and properties of the method proposed, which demonstrates its ability to deal with quite complex situations and provides a useful basis for further discussions with different experts in the food chain.