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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/measuring-disease-epidemiology
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课程名称：流行病学中的疾病测量 课程概述：流行病学研究无处不在。即使您未意识到，您每天都接触到流行病学研究及其发现的影响。您可能听说过高收入国家肥胖率正在上升，或低收入国家疟疾造成数百万人死亡。吸烟导致癌症和身体活动对心脏病的保护作用是常识。这些事实今天看起来似乎显而易见，但经过数十年的流行病学研究才形成了必要的证据。在本课程中，您将学习流行病学的基本工具，这些工具对于进行此类研究至关重要，从描述疾病或健康相关情况的频率的测量开始。您还将学习如何量化关联的强度，并讨论关联与因果关系之间的区别。在课程的后半部分，您将利用这些知识来描述不同的预防策略，识别诊断测试的优缺点，并考虑何时适合开展筛查项目。 课程大纲： 1. 疾病频率的测量： - 本模块的主要目的是描述对人口健康重要的疾病或其他健康状况的频率。您将学习如何计算流行率、赔率、累积发病率和发病率等不同的测量方法，并了解它们的共同点和差异。通过学习，您将能够在多种背景下选择和计算适当的频率测量。 2. 关联的测量： - 本模块介绍关联与因果关系的区别，这对流行病学和一般研究至关重要。您将学习流行病学家通常使用的主要关联量化测量方法，包括风险差异、比率差异和风险、比率和赔率比。在这个过程中，您将掌握计算和解释频率测量的技能，并学会根据研究问题和数据可用性选择最合适的测量。 3. 可归因风险和预防策略： - 已发表的研究通常会报告所调查的关联的规模，这在确定因果关系时显得尤为重要。本模块将帮助您理解可归因风险和人群可归因风险的概念，这些测量量化了健康相关因素对整体人群的影响，对健康政策尤为有用。掌握这些知识后，您将探索两种主要的疾病预防方法：高风险方法和人群方法。 4. 疾病检测与筛查： - 诊断测试通常用于判断个体是否生病。然而，这些测试并不完美。量化其缺陷使我们能够理解其局限性并解释结果。本模块将教您如何计算和解释灵敏度、特异性、正负预测值等指标。应用这些指标，您将学习如何评估一个筛查项目在方法和实用性方面是否有效。
Name:Measures of disease frequency
Description:One of the main purposes of epidemiology is to describe the frequency of diseases or other conditions that are important for the health of populations. Depending on the circumstances, there are different types of measures that you can use to do this. In this module, you will learn to calculate measures such as the prevalence, odds, cumulative incidence and incidence rate. We will highlight what they have in common as well as their differences. By the end of the module, you will be able to select and calculate the appropriate measure of frequency in a variety of contexts.
Name:Measures of association
Description:This module starts by introducing the distinction between association and causation, which is critical not only for epidemiology, but for research in general. Subsequently, you will learn all the main measures epidemiologists use to quantify association; mainly risk and rate differences and risk, rate and odds ratios. Over the course of this module, you will develop the skills to calculate and interpret measures of frequency. This is not enough by itself though, so you will also learn to select the most appropriate measure depending on the research question and the availability of data.
Name:Attributable risk and strategies for prevention
Description:Published studies often report the magnitude of the association they investigate, which is clearly important when trying to identify causal links. Sometimes though, what we are interested in is the impact of a factor or of a disease on the population as a whole. This is when the concepts of attributable risk and of population attributable risk come in handy. These measures quantify the population impact of a health-related factor and therefore are particularly useful for health policy. Equipped with this knowledge, you will then explore the two main approaches to disease prevention: the high-risk and the population approach.
Name:Disease detection and screening
Description:Diagnostic tests are used all the time to determine whether an individual is sick or not. However, these tests are far from perfect. Quantifying their imperfection allows us to understand their limitations and interpret their results. In this module, you will learn to calculate and interpret the metrics used to do this, including sensitivity, specificity, positive and negative predictive values. Using these metrics, you will subsequently learn to evaluate whether a screening programme can be effective or not considering its methodological and practical aspects.
Epidemiological research is ubiquitous. Even if you don’t realise it, you come across epidemiological studies and the impact of their findings every single day. You have probably heard that obesity is increasing in high income countries or that malaria is killing millions of people in low income countries. It is common knowledge that smoking causes cancer and that physical activity is protective against heart disease. These facts may seem obvious today, but it took decades of epidemiological research to produce the necessary evidence. In this course, you will learn the fundamental tools of epidemiology which are essential to conduct such studies, starting with the measures used to describe the frequency of a disease or health-related condition. You will also learn how to quantify the strength of an association and discuss the distinction between association and causation. In the second half of the course, you will use this knowledge to describe different strategies for prevention, identify strengths and weaknesses of diagnostic tests and consider when a screening programme is appropriate.
