  In this article, we take a step back to distill seven principles out of our
experience in the spring of 2020, when our 12-person rapid-response team used
skills of data science and beyond to help distribute Covid PPE. This process
included tapping into domain knowledge of epidemiology and medical logistics
chains, curating a relevant data repository, developing models for short-term
county-level death forecasting in the US, and building a website for sharing
visualization (an automated AI machine). The principles are described in the
context of working with Response4Life, a then-new nonprofit organization, to
illustrate their necessity. Many of these principles overlap with those in
standard data-science teams, but an emphasis is put on dealing with problems
that require rapid response, often resembling agile software development.
