The biggest challenge in the public health response to the coronavirus pandemic appears to be communication. Health policy has been inconsistent, suppressed or ignored, governors have rescinded mandates about masks, and health departments have faced resistance to policy, with individual health officials even suffering harrassment and death threats. We observe that public health messages meet resistance and are ineffective when issued as mandates. Health agencies and departments are limited in their legal authority and their power to enforce policy.
In the early days of the pandemic, and even now in mid-April 2020, we heard many estimates of the risk of the coronavirus SARS-CoV-2. Some think maybe it’s like the flu. Others assert, this coronavirus is no flu. When we say coronavirus is or is not like influenza, what comparison are we making? One comparison could involve the incidence of death from each disease. The question could be, how do the numbers of people who perish this week from each disease, COVID-19 vs.
Dr. John Ioannidis Dr. John Ioannidis is well known as the author of the manifesto of reproducibility in research, Why Most Published Research Findings Are False. He published that in 2005. I learned of it much later when I attended an inspiring seminar by Edward Tufte. Fast forward to now, and I’m on fire to apply data science to public health. When I turn my sights on Ioannidis again, I realize he is a professor of epidemiology and statistics.