[MUSIC] Hello, this Aurna Chandran and I'm delighted to welcome you to our course entitled Depiction of Epidemiologic Data. The learning objectives for this course are as follows, to understand what data visualization is and why it is an essential tool in public health and epidemiologic practice. To describe risk factors in public health and how they are measured. To explore the Visualization Hub of organizations such as the Institute for Health Metrics and Evaluation. And to describe the key components and considerations in graphing public health data. In this section we will define data visualization and provide a basic description of what it is and its use. Data visualization is the presentation of data in pictorial or graphical format. In fact, it can actually be interactive, allowing the user to change different inputs and view the resulting patterns or trends. As computer technology has improved data visualization has been brought to the forefront of corporate work and more recently public health practice. Large amounts of complex data can be much better understood using visualizations as opposed to charts and tables. That's the old adage a picture is worth 1,000 words. One of the earliest examples of data visualization actually comes from approximately 1812 when Charles Minard, a civil engineer, created a map showing the movement of Napoleon's army into and out of Russia. While maps were very commonly used at this time this map was unique in that it showed not only the army's path but also included numbers of soldiers, temperature, as well as time. Take a moment to explore this early example of data visualization and how useful such a map might have been. What does data visualization do for us? It allows individuals to comprehend information quickly and easily. You can imagine it is much easier to digest information from a figure than it might be from a complex table. It shows patterns, relationships, and trends. It allows identification of newly emerging changes, hotspots, or outliers. It allows prediction of future events through extrapolation but not necessarily through modeling. And it communicates a story or a message. Let's look at an example of a data visualization organization. I use FiveThirtyEight as an example here. There are many, many such organizations that do data visualization work. As this is a rapidly evolving field, I encourage you to take some time to explore such organizations. FiveThirtyEight provides analyses of politics, economics, sports, and pretty much anything else of popular concern. It has been a licensed feature of the New York Times online since 2010 and as of April 2018 was acquired by ABC News. This group has won numerous awards. So let's take a minute to look at the website, the link being provided on the instructions page, and think about why you think this website or this type of data visualization is so popular. On this slide, I provide some examples of data visualizations that jumped out at me. One of the reasons they are so popular is the creativity they use in visually depicting data related to issues that are of concern or interest to the general public. Use of pictures for example, can be very eye catching and certainly providing information on topics of popular concern such as professional basketball or the TV show American Idol. There are many different types of data visualizations. They can range from traditional charts or graphs, to maps, infographics, dashboards, and much more interactive storyboards. Let's take a moment to explore some data visualizations relevant to public health. The United States Census Bureau compiles geographic and sociodemographic information on all US residents on a regular basis. One of the tools it provides is a Data Visualization Visualization Gallery. The link to the gallery is provided on the instructions page. Open one of the visualization options that is of interest to you and answer the questions displayed on the following slide. Now that you are looking at your chosen data visualizations think about the following, first, in two to three sentences, describe the data and the message that is being conveyed. Second, name two positive or interesting aspects of the chosen method of visualization. Third, name two areas for improvement or challenges that you observe In your chosen visualization. Consider how might you have done this differently? As an example, I chose the date of visualization displayed here. The description, this is a time-trend map showing the US population without health insurance coverage from 2008 to 2015. Some positive aspects of this visualization, I find the map to be engaging, as it scrolls through the relevent years in a fairly rapid fashion. Thus it is easy to spot the patterns or specific geographic areas in which coverage is specifically or particularly good or particularly poor. Areas for improvement that I note, there is no clear delineation of major policy changes that occurred during this time such as the passing of the Affordable Care Act. Second, I don't get to see years placed next to each other and thus comparisons are a bit more difficult. There are important steps you want to undertake before thinking about creating your data visualization. First of all, it is imperative that you understand your data. You cannot convey messages if you don't know what your data is showing. You then must decide on the message or story that you would like to communicate and certainly this has to be tailored to your target audience. Consider logistical details, should the map be interactive? Do individuals have the opportunity to input certain parameters of interest? What type of computer access and computing power does your target audience have? Is the Internet speed for example conducive to viewing an interactive visualization? And finally, how current or updated are you able to keep your visualization? Displaying a visualization with data from several years ago is not terribly helpful. And most importantly, learn from others. There are numerous blogs, books and articles, and examples that can be found on the internet and other sources. Certainly, you will be able to see what works and what doesn't work for you. Once you do that, taking the time and learning how to create a data visualization can be an incredibly powerful method for conveying public health information.
