Surveillance Systems: Analysis, Dissemination, and Special Systems

Go to Course: https://www.coursera.org/learn/epidemiology-surveillance-systems-analysis

Introduction

### Course Review: Surveillance Systems: Analysis, Dissemination, and Special Systems #### Overview If you are keen on delving into public health surveillance, "Surveillance Systems: Analysis, Dissemination, and Special Systems" on Coursera proves to be an exceptional course that builds upon foundational knowledge in health surveillance. As public health becomes increasingly crucial in our globalized society, understanding how to analyze and utilize surveillance data effectively is vital for any professional in the field. This course is tailored to equip learners with specific skills to interpret and disseminate surveillance data, which can drastically affect public health outcomes. #### Course Structure The course is divided into four critical modules, each focusing on different aspects of surveillance data: 1. **Analyses of Surveillance Data** - This module introduces participants to analyzing health surveillance data, emphasizing how to interpret time trend data and detect temporal aberrations. The integration of descriptive epidemiology principles offers a comprehensive approach to understanding person, place, and time dimensions in surveillance data. This foundational knowledge is essential for public health professionals who aim to leverage these data sets in analyzing complex health issues. 2. **Dissemination Strategies and Communication Frameworks** - Here, you will learn about the strategies necessary for presenting surveillance data effectively, including navigating the complex legalities associated with these data. Unlike research data, surveillance data often lacks explicit consent from individuals, necessitating adherence to stringent legal frameworks. This module emphasizes the critical role of effective communication in public health and provides insights into how to convey sensitive data responsibly. 3. **Chronic Disease Surveillance Systems** - This section shifts focus from communicable to non-communicable diseases, introducing frameworks that guide chronic disease surveillance. By delving into examples from cancer to cardiovascular health, the course illustrates the profound impact effective communication can have on chronic disease prevention strategies. The emphasis on communication throughout this module ensures that learners appreciate its significance in translating data into actionable public health initiatives. 4. **Special Surveillance Systems** - The final module discusses unique surveillance systems that cater to health issues that do not neatly fit within standard classifications. It explores syndromic surveillance systems, event-driven surveillance, and antibiotic resistance surveillance systems. This module is particularly fascinating, as it showcases innovative approaches to tackle emerging public health challenges using tailored surveillance strategies. #### Learning Outcomes By completing this course, participants can expect to: - Develop a nuanced understanding of health surveillance data analysis. - Master strategies for effective dissemination and communication of complex surveillance data. - Acquire knowledge about various chronic disease surveillance frameworks and their applications. - Gain insights into specialized surveillance systems relevant for specific health challenges. #### Recommendations This course is highly recommended for public health professionals, epidemiologists, and researchers who aim to enhance their expertise in health surveillance. Whether you are a beginner looking to understand the fundamentals or an experienced professional aiming to brush up on the latest practices, this course is a valuable investment. The blend of analytical techniques and communication strategies will empower you to utilize surveillance data effectively in your public health efforts. In conclusion, "Surveillance Systems: Analysis, Dissemination, and Special Systems" on Coursera not only provides substantial practical skills but also fosters an appreciation for the intricacies of health surveillance. It is an essential stepping stone for anyone dedicated to improving health outcomes in communities through informed data analysis and dissemination.

Syllabus

Analyses of Surveillance Data

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.

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.

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.

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.