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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/epidemiology-surveillance-systems-analysis
课程评论：没有评论
课程名称：监测系统：分析、传播与特殊系统 概述：本课程将基于该专业化的前几节课，专注于公共卫生监测相关的特定技能。我们将学习如何有效地分析监测数据，重点关注时间趋势数据的解释，以检测时间异常以及在监测数据的背景下分析个人、地点和时间。课程还将探讨监测数据的呈现策略及影响其使用的一些复杂法律要素。随后，我们将关注非传染性慢性疾病的监测及如何利用数据支持预防工作。最后，我们将探索特殊监测系统，如症状监测、抗微生物耐药性监测以及事件相关监测。本课程旨在服务于公共卫生从业人员，特别是那些在市、区、省或国家公共卫生机构负责健康监测的人员。我们相信本课程将帮助对健康监测感兴趣的人了解公共卫生实际操作中使用的各种方法。 课程大纲： 1. **监测数据分析** - 本模块重点讨论健康监测中的数据分析方法，特别是如何解释作为健康监测项目一部分的时间趋势数据，并检测时间异常。我们将延续先前的描述性流行病学课程，强调在监测数据分析中对个人、地点和时间的利用，讨论监测数据的复杂问题以及数据集的局限性。 2. **传播策略和沟通框架** - 本模块将探讨监测数据的呈现策略以及影响健康监测数据使用的一些法律复杂性。监测数据与研究数据本质上不同，监测数据在收集时不涉及明确同意，因此有特定法律规范其使用。本模块还将讨论在健康监测中沟通这些敏感数据的策略及相关建议。 3. **慢性疾病监测系统** - 本模块将转向非传染性疾病或慢性疾病的监测，介绍指导慢性疾病监测的一些框架和方法，并举例说明这些框架在癌症和心血管健康系统中的应用。我们将再次关注沟通，探讨如何有效交流这些复杂问题及在慢性疾病监测中的应用实例。 4. **特殊监测系统** - 本模块讨论一些有趣的特殊监测系统。尽管对传染性和非传染性疾病有标准化的监测方法，但仍有一些健康问题无法轻松归入这些分类，特殊监测系统在这些领域中发挥着重要作用。我们将探讨症状监测系统的使用时机和设计，并评估指示性监测与事件驱动监测系统之间的区别，进一步讨论抗微生物耐药性监测系统和事件相关监测系统的详细内容。
Name:Analyses of Surveillance Data
Description:In this first module, we're going to focus on the analyses used in health surveillance. Specifically, we're going to talk about how to interpret time trend data that's harnessed as part of health surveillance programs and strategies used to detect temporal aberrations. We're also going to build on some of your earlier specialization lessons on descriptive epidemiology with a real focus on how it can be used in the analyses of person, place, and time in the context of surveillance data. I really want to highlight throughout the module how we often underutilize surveillance data to analyze complex issues, but I also want to talk about the some of the limitations that exist within the data sets.
Name:Dissemination Strategies and Communication Frameworks
Description:In this module, we will explore strategies for the presentation of surveillance data and some of the complex legal elements that affect the use of health surveillance data. Now, surveillance data are fundamentally different from research data. In research studies, people provide explicit consent for how their data are going to be used. For surveillance data, the collection doesn't include explicit consent. As a result, there are very specific laws governing how the data can and should be used to drive public health programs. We'll also discuss communication strategies in health surveillance given how sensitive it can be to message health surveillance data, and the associated recommendations that come along with communicating these data.
Name:Chronic Disease Surveillance Systems
Description:So we're switching gears today from communicable diseases to noncommunicable diseases, or often called, chronic diseases. I'll present some of the frameworks and approaches that have been developed to guide chronic disease surveillance and then I'll focus on giving different examples of these, ranging from cancer to cardiovascular health systems. Taking you back to the surveillance cycle from Dr. Gurley's course, "Surveillance Systems: Building Blocks," I'll provide some context on how these chronic disease surveillance systems can really impact chronic disease prevention strategies if communicated effectively. And that brings us back to communication, where we will again focus on approaches to communicate these complex issues and then give an example of how to apply communication framework in the context of a chronic disease.
Name:Special Surveillance Systems
Description:In this module, I will discuss some of the really interesting special surveillance systems. Although having standardized approaches for infectious diseases and non-communicable diseases is fundamentally important, there are also some health issues that do not fit nicely into these boxes, and it's here where these special surveillance systems can really play an important role. As you will see, having a framework or approach to the issue is still relevant, but the approaches are really tailored to the issue at hand. We will start by discussing syndromic surveillance systems, including when to use them and also how to design them. We'll then really evaluate the differences between indicator versus event-driven surveillance systems. We'll then move on to anti-microbial resistance surveillance systems and then talk in more detail about event-related surveillance systems.
In this course, we'll build on the previous lessons in this specialization to focus on some very specific skills related to public health surveillance. We'll learn how to get the most out of surveillance data analysis, focusing specifically on interpreting time trend data to detect temporal aberrations as well as person, place, and time in the context of surveillance data. We'll also explore strategies for the presentation of surveillance data and some of the complex legal elements that affect its use. We'll then turn our attention to surveillance of non-communicable chronic diseases and how the data can be used to support prevention efforts. Finally, we'll explore special surveillance systems, such as syndromic surveillance, antimicrobial resistance, and event-related surveillance. This course is designed for public health practitioners with a focus on those working on health surveillance in municipal, regional, state, provincial, or even national public health agencies. We really think that this course will help those with an interest in health surveillance to see which approaches are used in actual practice of public health.
