Pandemic Root Cause: Infected Rich Asses Played Hide And Seek Among The Masses

slate |  Professor John P.A. Ioannidis of Stanford University—by reputation one of the smartest people in fields ranging from epidemiology to biomedical data science—published a somewhat controversial piece in Stat News last week that warned of the possibility that our best efforts might end up backfiring:

If the health system does become overwhelmed, the majority of the extra deaths may not be due to coronavirus but to other common diseases and conditions such as heart attacks, strokes, trauma, bleeding, and the like that are not adequately treated. If the level of the epidemic does overwhelm the health system and extreme measures have only modest effectiveness, then flattening the curve may make things worse: Instead of being overwhelmed during a short, acute phase, the health system will remain overwhelmed for a more protracted period.

Ioannidis’ piece got some pushback by public health experts who worried that his questioning might make people less likely to follow instructions to self-isolate and stay indoors. But even his critics seem to agree that it is absolutely critical for us to have better data. 

We are currently quite lacking in data and sorely in need of it. We need to know many more things about the virus and what it does to the human body, including whom it affects and how to treat it. We need better testing to figure out how many people in the United States have it, even as the people on the front lines are realizing that they themselves have to shift their efforts away from containment approaches and toward treatment and mitigation of spread. 

We also need data on how our current approach is working and data on what the costs of this approach really are. We need to know how much our current version of social distancing, with everyone still going to the grocery store every few days, is affecting the rate of spread. We need to figure out how much people being stuck at home might lead to an uptick in domestic abuse or suicide. We need to know if more women are giving birth at home, and if more women are being forced to carry pregnancies that they don’t want as their right to abortion is interrupted. We need to know how the people who are laid off from their jobs are getting food, and if they are still willing to access health care when the financial cost of doing so might be very uncertain. We are all engaged in an enormous, high-stakes nationwide experiment right now, and we need all of this data to answer the question: Are we doing the right thing? 

And still, the questions remain: How long can we really do this for? What else could we do? What should we do next? 

Academic physicians Aaron Carroll and Ashish Jha have a piece in the Atlantic in which they consider the various possible scenarios in front of us. The extremes are helpfully familiar—on one side, do nothing, which we’re already doing better than; on the other side, stay like this for the next 18 months or so, the current accepted timeline until there’s a vaccine. But Carroll and Jha argue that there is a third path available, somewhere in the middle of these two strategies. They think that once we do the social distancing necessary to get the initial numbers under control (which will still take time), we can create a new type of plan, a middle road that keeps public health manageable without keeping the country completely shut down.