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Pleased to share my contribution to @BostonReview's "Thinking in a Pandemic" series. My focus was applying solution-based thinking to move us towards our goal of living safely. I would love for you to read it, but summarizing the main points here. 1/11 https://bostonreview.net/science-nature/natalie-dean-steps-better-covid-19-response
First, it is useful to move the discussion from the general to the specific. Our public conversation was for a while stuck at lockdown good vs. lockdown bad. A more productive debate compares a policy to one or more precisely defined alternatives. 2/11
When moving into the weeds, we can break large problems into smaller ones. The pandemic has disrupted important services like cancer screening and infant vaccinations. Instead of discussing everything at once, can we find solutions to mitigate these problems one by one? 3/11
Second, we need to continue to look globally for solutions. Each country is following a different playbook, but we can pick out the best features. Clear crisis communications in New Zealand, sensitive surveillance in South Korea, public health hotlines in Vietnam. 4/11
Some formal attempts to learn from other countries have emerged, like @OurWorldInData's Exemplars in Global Health, and the DELVE initiative from the UK. These synthesize the available info to see how strategies are working across the world. 5/11 https://royalsociety.org/news/2020/04/royal-society-convenes-data-analytics-group-to-tackle-COVID-19/
Third, we then need to adapt these strategies to local conditions. As an obvious example, drive-thru testing may work in Ohio, but not in New York City. It takes time to figure out what challenges will emerge, and how to work through them, but we need to start somewhere. 6/11
One way to adapt strategies is to use a positive deviance approach. Teams work together to learn from the outliers in their midst. This could be shadowing the contact tracer no one hangs up on. This discovery process finds solutions and trains people how to use them. 7/11
Finally, we need an architecture for learning. This starts with standardized and complete data. But then also dedicating time to learn from contact tracing so we can identify both high- and low-risk settings and adapt accordingly. 8/11 https://blogs.bmj.com/bmj/2020/07/06/covid-19-in-the-us-were-not-getting-full-value-from-our-data/
For important policy questions, it is worthwhile setting up prospective cohort or even randomized studies. Though slower and more complex, they are more likely to provide definitive evidence (remember when HCQ trials were too slow?). 9/11 https://www.washingtonpost.com/outlook/coronavirus-hydroxychloroquine-trials-research/2020/04/10/fa003ada-7a7a-11ea-a130-df573469f094_story.html
Unlike problem-based thinking which looks back on the past, solution-based thinking looks ahead to a safer future. It welcomes even incremental improvements as moving us closer to this goal. And it rejects the wishful thinking that holds out for a simple fix like a vaccine. 10/11
We should welcome the hard slog of public health ( @devisridhar!) because waiting for some future panacea may deter us from learning how to do things better now. So I hope this thread convinces you to read the piece, and that you find it helpful. :) 11/END
