Forensic Risk Alliance (FRA) has written an interesting analysis about COVID-19 modeling and statistics, noting that some are too quick to dismiss the value of this testing by looking for flaws or contradictions, instead of using the data to understand the range of possibilities and testing responses incrementally.
This message of patience and persistence will serve us well beyond the resolution of the COVID-19 crisis.
Perhaps the greatest challenge in responding to the coronavirus pandemic is that governments are being forced to make potentially life and death decisions based on imperfect information. Officials across the globe are relying on statistical models to make critical policy choices, such as how to best direct supplies and expertise, allocate funding, and enforce social distancing rules.... We believe that the public confusion stemming from these models reflects a common misunderstanding of statistical modeling and its purpose, a challenge which we often see in our work with businesses seeking to employ similar models in their operations. Models are most valuable when utilized to describe a range of possibilities, and the range of possibilities will always be highly sensitive to any reactions. In other words, models impact behavior, which impacts the model, which further impacts behavior—and so on—until the model is inevitably changed. This dynamic process requires constant refinement in order to realize maximum value. Organizational Lessons: 1) Statistical Modeling is Dynamic 2) Data Quality is Paramount 3) Communicate Your Assumptions, and Revisit Them Often 4) Utilize Data Analytics to Drive Policy