100,000 models show that not much was learned about stopping the Covid-19 pandemic
DBMI's Chirag Patel writes with Stanford's Eran Bendavid in STAT highlighting their publication in Science Advances
Image: Christopher Furlong, Getty Images
Excerpt:
In the midst of the Covid-19 pandemic, scientists and public health institutions made bold claims about the effectiveness of various policy responses such as closing schools and banning public gatherings. These claims shaped government responses and had enormous effects on the lives of billions of people around the world. Are those claims supported by data?
To answer that question, we explored whether patterns in the epidemiologic data could support claims made in the scientific literature and by public health institutions about the effectiveness of policy responses to Covid-19.
We were optimistic we would find some policies that were consistently helpful. We thought the data would show that early shelter-in-place containment measures in the spring of 2020 were more effective in preventing deaths than those later in the pandemic; or that case numbers would not rise after restrictions on attending schools were lifted.
That isn’t what we found, as we describe in a paper published today in Science Advances.