We did horribly - the whole world did. Too many people politicized it or told their political masters what they wanted to hear with computer models of the death estimates ranging 100's of times higher than the actual numbers.
Seattle weather guru Cliff Mass takes them to the woodshed:
Weather Forecasting is Fifty Years Ahead of Epidemiological Prediction: That Must Change
In October 2012, Hurricane Sandy approached New York from off the Atlantic. Seven days before, a near perfect track forecast was made by the European Center and two days later the U.S. model (the GFS), run by the National Weather Service's Environmental Modeling Center, has locked on as well.
The stunningly accurate prediction of an extremely unusual event, saved countless lives, with only about 100 deaths in a region of tens of millions of people (and most who died made a bad decision to ignore the forecast).
He looks at the factors going in to this and compares it to our dealings with the Wuhan Flu:
Stunningly, U.S. epidemiological modeling has almost NONE of the above components or systems, and the performance of the U.S. Centers for Disease Control and Prevention (CDC) is poor. Consider:
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- There is no large, permanent epidemiological prediction center in the U.S. government analogous to the NOAA/NWS. U.S. response to COVID had to depend on a hodgepodge of university forecasting efforts, some spun up for this event. Untested, unverified, and often very wrong.
- Unlike weather prediction, U.S. epidemiologists do not have an accurate description of what is happening NOW. Testing was slow to begin, in fact, the CDC made serious errors in test development. Even today, six months into the pandemic there are not enough tests. There is no attempt being made to randomly sample the population to understand how many folks have or were infected. Unbelievable.
- Unlike the comprehensive and smoothly running weather observational system, there is poor organization to the data collection by CDC. There are not even standard reporting approaches.
- The epidemiological models are generally primitive affairs, many of which do not consider the complex, variable transmission properties of a heterogeneous population, and lack clear information of what is occurring right now (called the initialization in weather prediction).
- Communication by CDC of both the threat and how to deal with the disease has been inconsistent and often wrong. For example, they initially discouraged the use of masks, before reversing their guidance 180 degrees. Similarly, CDC downplayed the threat in January and February, before reserving in March. The NWS works very hard to start with reliable forecasts, to communicate the uncertainties, and not to go back and forth in their warnings. They are masters at this.
Cliff is not a fan of President Trump but he offers this come-to-Jesus moment for the TDS sufferers:
The Political Opportunists
There are some folks and many media pundits who are claiming this COVID disaster is all the fault of President Trump and that things would have been much better under a Democratic President.
This is either very naive or very cynical.
There is no doubt that the President and his administration has been startlingly misinformed and ineffective. His abysmal leadership has made things much worse.
But the problems noted above are not recent developments and have been allowed to fester in recent administrations, including the 8-years of President Obama. I suspect we would not have been in much better place if Hilary Clinton would have won, because the basic institutional infrastructure was not put in place.
That is what we must do together as a nation, following the example of the weather prediction community. And speaking as one of them, we would be glad to help.
A very wise heads-up. Let us hope that President Trump has some advisers that think along the same lines. This bit of nastiness escaped from the Chinese lab despite their protestations to the contrary. Stuff like this will happen again and the sooner we can mobilize, the better.
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