Morbidity and mortality from acute encephalitis in Vietnam have remained very high, especially in the Northern region. Except for Japanese Encephalitis (JE), the acute viral encephalitis (VE) was not studied as needed. Study was conducted in 374 hospitalized patients aged under 15 with diagnosis of VE in 2003-2004. The results showed that the male to female ratio was 2.3:1. The morbidity and mortality in all ages were not different, but the mortality rate was higher in group of under 10. More than 75% of morbidity occured from April to July.
Encephalitis ; Epidemiology ; Epidemiologic Research Design

Epidemiologic Research Design ; Sociology, Medical

Air Pollution ; prevention & control ; Epidemiologic Research Design

OBJECTIVETo explore the impact of measurement error on the associated effects under the incorrectly-measured variables when mixed with precisely measured variables.

METHODSBased on the functions of measurement error, correlation of incorrectly-measured predictors and precisely measured explanatory variables, number of precisely measured explanatory variables and associated effect, the 'R Project for Statistical Computing' method is used to analyze the impact of measurement on the validity of a study.

RESULTSUnder the scenario that the continuous response Y and the continuous explanatory Z are precisely measured but the continuous predictor X is incorrectly-measured, when focusing on inference about the effect of X on Y, the non-differential measurement error always makes the value of estimated effect less than the actual value, and the attenuation effect of measurement error more closely worsens the correlation of X and Z. Under a misclassification dichotomous predictor X with an additional precisely measured explanatory variable Z and focusing on inference about the effect of X on Y, the misclassification bias is not only related to the sensitivity and specificity of exposure measurement, but also to the correlation between X and Z and exposure proportion of X. The attenuation factor (AF) decreases gradually with the increasing correlation between X and Z. For instance, in the p = 0.5 scenario, AF is 1.419, and the estimated effect of dichotomous predictor X on continuous response Y is more than the actual effect. When it increases to 0.9, AF is 0.474, the estimated effect becomes less than the true effect.

CONCLUSIONIn the studies of the impact of measurement error in linear regression with additional precisely measured explanatory variables, the impact of measurement error on the associated effect is relatively complex, suggesting that it is necessary to control and to assess the measurement error bias in order to correctly interpret the results of a study.

OBJECTIVES: To evaluate the utility of using a web-based sample size calculator in the preparation of a research proposal.

METHODS: EpiTools, a free web-based calculator for sample size determination, was used in various study designs.

RESULTS: Computations of sample size needed for several simple epidemiologic study designs were calculated using different assumptions. The calculator was straightforward to use and user- friendly. The results were calculated quickly. Comparison of the computed sample size using different assumptions may be done to assist in evaluating research project feasibility. The input data and output of the sample size calculation may be transformed into a report for inclusion in the written research proposal.

CONCLUSION: The EpiTools web-based calculators is a convenient tool for sample size determination in the design of research protocols in relatively simple study designs. It may be used in evaluating the feasibility of the computed sample size needed by the study design.

Controlling unmeasured confounders in non-randomized controlled studies is challenging. Negative control theory is based on the theoretical concept that the test result of negative controls must be negative. Setting appropriate negative control incorporates the specificity of association into population studies for the identification and control of unmeasured confounders. This paper explains the principles to control unmeasured confounders using negative control theory from a statistical perspective. A detailed introduction of derived methods based on negative control theory is also introduced, including adjusted standardized mortality ratio method, calibrating P-value method, generalized difference-in-difference model and double negative control method. The reasonable application of those derived methods is also comprehensively summarized based on representative case studies. Negative control is an important statistical design to identify, revise and control unmeasured confounders and a valuable method for comparative effectiveness research based on real-world data.
Humans ; Confounding Factors, Epidemiologic ; Research Design ; Comparative Effectiveness Research ; Bias

Academic Dissertations as Topic ; Epidemiologic Research Design ; Molecular Epidemiology

One of the commonly accepted merits of cohort studies (CSs) refers to the exposure precedes outcome superior to other observational designs. We use Directed Acyclic Graphs to construct a causal graph among research populations under CSs. We notice that the substitution of research population in place of a susceptible one can be used for effect estimation. Its correctness depends on the outcome-free status of the substituted population and the performance of both screening and diagnosis regarding the outcomes under study at baseline. The temporal precedence of exposure over outcome occurs theoretically, despite the opposite happens in realities. Correct effect estimate is affected by both the suitability of population substitution and the validities of outcome identification and exclusion.
Causality ; Cohort Studies ; Confounding Factors, Epidemiologic ; Epidemiologic Methods ; Mass Screening ; Research Design

The final decision of study design in molecular and genetic epidemiology is usually a compromise between the research study aims and a number of logistical and ethical barriers that may limit the feasibility of the study or the interpretation of results. Although biomarker measurements may improve exposure or disease assessments, it is necessary to address the possibility that biomarker measurement inserts additional sources of misclassification and confounding that may lead to inconsistencies across the research literature. Studies targeting multi-causal diseases and investigating gene-environment interactions must not only meet the needs of a traditional epidemiologic study but also the needs of the biomarker investigation. This paper is intended to highlight the major issues that need to be considered when developing an epidemiologic study utilizing biomarkers. These issues covers from molecular and genetic epidemiology (MGE) study designs including cross-sectional, cohort, case-control, clinical trials, nested case-control, and case-only studies to matching the study design to the MGE research goals. This review summarizes logistical barriers and the most common epidemiological study designs most relevant to MGE and describes the strengths and limitations of each approach in the context of common MGE research aims to meet specific MEG objectives.
Disease Progression ; *Epidemiologic Research Design ; *Epidemiologic Studies ; Genetic Markers ; Genetic Predisposition to Disease ; Humans ; *Molecular Epidemiology ; Risk Assessment

This study was conducted to integrate the results of studies which evaluated or identified the risk factors of CVD(cerebrovascular disorders) for Koreans. We retrieved the literature published in Korean by manual search and the English literature by Medline database to identify studies on the relationship between reported risk factors and CVD conducted for the Korean from 1980 to August, 1997. Hypertension and total serum cholestrol were selected as subjects of quantitative meta-analysis as risk factors of CVD in Koreans. The overall effect sizes of the risk of CVD due to hypertension and total serum cholesterol were calculated by common odds ratio(OR) and average standardized mean difference, retrospectively. Before the integration of each effect sizes into common effect sizes, the heterogeneity tests were conducted. Also, sensitivity tests were conducted for the estimated common effect sizes. Regarding hypertension and CVD, a total of 9 epidemiologic studies were identified with a total of 2,271 cases of CVD. The overall OR of hypertension associated CVD was 4.10(95% confidence interval[CI] 3.56 to 4.71). The OR of hypertension associated with hemorrhagic CVD and ischemic CVD were 6.56(95% CI : 4.92 to 8.80) and 3.28(95% CI : 2.77 to 3.90), retrospectively. The OR of hypertension in relation to hemorrhagic CVD was significantly higher than that of hypertension in relation to overall CVD or ischemic CVD. Regarding serum total cholesterol and ischemic CVD, total 9 epidemiologic studies were identified with a total of 843 cases of ischemic CVD. Average mean difference as an effect size was 0.76, which was judged an important value according to Cohen's criteria. Our data suggested that hypertension was an important risk factor of overall CVD and its subtypes, and that the total serum cholesterol was associated with ischemic CVD in Koreans. For the lack of reliable prospective studies, however, we concluded that further research designed longitudinally would be required in this area.
Cerebrovascular Disorders* ; Cholesterol ; Epidemiologic Studies ; Hypertension ; Population Characteristics ; Research Design ; Retrospective Studies ; Risk Factors*