Student Choice

Visualization: https://gis.cdc.gov/grasp/COVIDNet/COVID19_3.html

What is its purpose?

This interactive tool allows users to display and query information about laboratory-confirmed COVID-19-associated hospitalizations by age group, underlying medical conditions, and other selected characteristics.

What is the data?

The data looks at the COVID-19 hospitalization rates for all the different variables that are present in the visualization.

Cases are identified through active review of notifiable disease and laboratory databases, hospital admission, and infection control practitioner logs. A minimum set of variables (age, sex, race and ethnicity, hospital admission, and SARS-CoV-2 testing data) are collected for all patients to generate age-stratified, race and ethnicity-stratified, and sex-stratified COVID-19-associated hospitalization rates each week.

COVID-19-associated hospitalization rates by race and ethnicity are calculated using hospitalized COVIDNET cases with complete race and ethnicity data for the numerator and NCHS bridged-race population estimates for the denominator. The age strata used for the adjustment are 0–4, 5–17, 18–49, 50–64, 65–74, 75–84, and 85+ years.

Detailed medical chart abstraction is conducted by trained staff, including information on signs/symptoms at admission, underlying medical conditions, intensive care unit admission, mechanical ventilation, discharge diagnoses, and in-hospital death

wHO ARE THE USERS THAT THIS VISUALIZATION WAS MADE FOR?

The users that this visualization is made for is anyone who is interested in understanding the different variables that could impact COVID-19 hospitalization rates. It could be for research purposes or for the general audience to see these impacts of other variables on COVID-19.

What questions do people want to ask?

Does age have a correlation with COVID-19 hospitalization rate?

How do medical conditions (asthma, obesity, pregnancy) impact COVID-10 hospitalization rate?

Which ethnicity has the most COVID-19 hospitalization rates?

how can they find answers with this tool?

The users can find their answers by using the drop downs for the graph so they can select the categories and variables they want to display on the graph.

The user can also filter the graph by specific age groups and by state as well to be displayed.

What works?

The visualization has a slider bar for the date at the top so that the user is able to see where this date falls on the chart below. I think this is an amazing idea because there is so much going on and it is nice to see the pinpoint of that date on the graph.

I think this graph is also very easy to work with as the user can see the dropdown has checkboxes to select which medical condition the user wants to see displayed. The user is allowed to see this both vertically and horizontally. In addition, it is color coded and the legend is very easy to comprehend. The organization of this graph and its inputs have been executed very well in my opinion.

what needs improvment?

There seems to be a lot of going on the screen and it can be quite overwhelming to the user as they do not know where to start on the controls panel to the left.

I felt like there was too much scrolling involved that could be tedious to the user. I think a better way to put the controls would be split them and put them on both sides of the graph so there was little no scrolling.

Another room for improvement would be to show the exact percentage for situations like above. The percentages are all very close to each other so it would be a good idea to show the exact number on each bar.