An app that allows users to track their interactions and travel during the COVID-19 pandemic, and uses that self-reported information from users, in conjunction with publicly accessible information about the number of cases in counties, etc. to assign risk levels to geographic locations and to individual users. During this project, my responsibility was to focus on designing the section containing a heat map, where users would be able to search for specific locations and determine the current conditions.
Myself and two classmates
P r o c e s s
Our primary form of research consisted of contextual inquiries. Each team member conducted two interviews, specifically looking for participants who were considered to be in a high risk group (elderly or immunocompromised). We focused many of our questions around how individuals had changed their routines due to the pandemic, their feelings surrounding the virus, where they were obtaining information and news, and their thoughts on location sharing in apps.
Personas & scenarios
Once we completed our interviews and discussed our findings, we consolidated notes and created a couple of different personas and scenarios.
Based on our research findings, we created an affinity map to help us identify key themes and patterns that emerged. Some of the key themes:
- There is a customer base for an easy-to-use informational app
- Potential users are less concerned about location tracking
- There is some general anxiety among most people around COVID-19
- Many have changed routines dramatically, if possible, and are leaving primarily for walks or grocery runs
At this stage, we also began brainstorming a number of ideas that could potentially be incorporated in our app. Some ideas include:
- An app that provides news updates and notifications for Coronavirus related information; changes in health orders, travel orders
- An app that solely relies on cell phone location data to track users movements and interactions and identify hot spots
- An app where people who are high-risk could be paired with lower-risk individuals; create volunteer opportunities for people to do things like grocery shop for older/ immunocompromised people
|Design Principle||Observations from Contextual Inquiries|
|An ideal solution is easy to use, automated, and doesn’t require a lot of effort to learn.||“There is a wide range of technological literacy”|
|Our design has to clearly convey information. It cannot be overly complicated. It would need to be quick and updated regularly.||“People are seeking information” and “Varying levels of awareness regarding health measures/infection numbers|
|Our design should be free of judgement, and have a calm, clean look to reduce anxieties.||“There is some general anxiety among many people”|
|The app should have a simple aesthetic that indicates to users it is secure and contains essential information.||“People are generally willing to share their location information”|
User flow & wireframes
We created a basic flowchart in order to help us determine the structure of our app, which also helped us while we walked through how users would complete a specific task. Each team member created low-fidelity wireframes for the section they were responsible for.
During this stage, I decided to narrow down the task to a user checking the app to verify the hours of a specific location. I imagined that if a user either felt unsure about whether or not to travel or wanted to ensure it would be safe to do so, this task would help them make that decision. If they find the store they’d like to visit is too busy, exploring the map could result in them finding another store that is emptier.
Round 1 prototypes
We began building our initial prototypes in Figma.
Testing & revisions
As a group, we decided on a testing process as well as wrote a script to ensure the tests would be consistent. I observed three people navigating through my prototype, attempting to complete the task: “Find a Whole Foods grocery store on the map and find the current risk level.” We encouraged users to think aloud as they worked through the task and asked for any additional feedback once it was completed.
The primary takeaway from the observations conducted was that users may utilize the heat map in a more exploratory manner than initially expected. The first round of prototypes were designed with the assumption that most would use it to locate a specific place, find the risk level, and make a decision on whether or not to visit based on this score. However, this is the way a user might go about this if they have an exact location in mind (i.e. Whole Foods). Others might search for something more general (i.e. grocery stores) and use the app to help them find the best option. Since the first prototyping round was designed in a very linear way, the goal for the second round was to allow for a more efficient and faster way to explore their general surroundings rather than having to search for something, select it to view more information, then go back to the map to search for alternatives.