Launch
Students will launch the project by examining outbreak evidence, community concerns, and early historical-data connections, then organize initial questions and claims that will guide later research, empathy work, and design decisions.
Days 1 - 2
Research & Empathy
Students will gather firsthand and source-based evidence about infectious disease spread, compare a modern outbreak with the Black Death, synthesize user needs from community and clinic perspectives, and build a shared evidence board that identifies patterns, questions, risks, and design constraints for the next phase.
Days 3 - 7
Define Design Brief
Students will synthesize outbreak research, historical comparison evidence, community input, and quantitative analysis into a focused How Might We statement and a prioritized design brief. They will define user-centered criteria, constraints, tradeoffs, and language-access needs, then draft a policy brief or public health campaign scope that clearly connects the problem to historical patterns, data, and stakeholder evidence.
Days 8 - 12
Ideate & Prototype
Students will generate multiple evidence-based solution pathways for their policy brief or public health campaign and infection-reducing device, build rapid low-fidelity prototypes, test them with peers and a community health partner, and document how feedback changes their design choices.
Days 13 - 17
Refine & Present
Students will use critique, user validation, and evidence-based revision to strengthen their infection-prevention prototype and multilingual policy or campaign materials, then prepare a stakeholder-facing presentation that clearly explains how historical comparison, statistics, community input, and design testing shaped their recommendations.
Days 18 - 22
Showcase
Students will present their finalized policy brief or multilingual public health campaign and infection-prevention prototype to an authentic audience, gather final response-card evidence from community members and clinic partners, and complete an individual reflection explaining how historical comparison, statistics, user feedback, and revision shaped their recommendations.
Days 23 - 24