<bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Background:</i></b> Technologies are increasingly being deployed in facilitating participatory healthcare. Global governments developed a variety of digital platforms, such as mobile contact tracing apps, to help the public navigate risks and uncertainties during the COVID-19 pandemic. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Literature review:</i></b> Contrary to normative approaches to information design (IxD), the global spread of COVID-19 revealed the need for an alternative design framework (i.e., concept-driven design) to help develop mobile health (mHealth) apps that can support a broader portrayal of information value in IxD. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Research questions:</i></b> 1. In response to COVID-19, what affordances are prioritized by the designers of these global mHealth apps? What do these priorities tell us about design intents and information value? 2. What interpretive framework can we use to understand mHealth designers’ intent across different geopolitical contexts? <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Research methodology:</i></b> We captured screenshots of the three apps in the US, India, and China, as well as a website in Ghana. Using touchpoints as the unit of analysis, we conducted an inventory and affinity mapping to visualize the architecture of each app and categorize touchpoints based on their affordances. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Results:</i></b> The comparison of apps across countries displays shared and divergent priorities in their touchpoints, affordances, and information depth. We developed an interpretive framework for understanding mHealth design intent across numerous contexts—Common Interpretive Framework for Design Analysis (CIFDA)—incorporating both linear analysis and recursive analysis of touchpoints, affordances, and depth. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Conclusions:</i></b> Touchpoints in mHealth applications can be designed, but they can also be measured and analyzed, and they can in return help us understand the designer's intent and expected user experience.