Testing for coronavirus at UC San Diego Health
Testing for coronavirus at a UC San Diego Health facility. Courtesy UCSD

The stock market crashed from 29,232 on Feb. 12 down to 20,704 on March 18. We can assume carbon emissions had a similar crash. Airplanes were not flying, people were staying home. The COVID 19 triggered both a pandemic, an economic collapse, isolation at home, standing apart, wearing masks and innumerable other social and economic changes. Call it our apocalypse.

Some of the impacts were unanticipated, but nevertheless had some value as testing the capacity of our health and economic system to withstand such shocks. And to be prepared for the next one. Among the unexpected challengers were in education, Internet access and healtcare equipment.

The closing of schools had a fallback approach: Going online with a variety of apps, the most popular of which is Zoom. Getting beyond zoom-bombing was easier than dealing with equity requirements embedded in our legal protections for special education and disadvantaged students. The impending disaster was that if everyone couldn’t be provided access to educational programming then no one would.

Isn’t that a much too severe outcome? Imagine if we applied that rule to hospitals:  If one person couldn’t be treated, then no one would. Or to food:  If one person couldn’t get access to food, then no one would. Equity is important, but the argument against such severe penalties when reform actions are available is “let’s not cut off our noses to spite our faces.” Or are we locked into a severe approach even during the time of an apocalypse?

The defeat of net neutrality in the United States has proven once again that regulatory control is less nimble than private market solutions to Internet access. European net neutrality has dampened investment leading to European governments asking providers such as Netflix to slow down their transmission from high-definition to standard service. So why invest in expanded bandwidth if government wields a heavy hand?

The opposite is the experience in the United States, where net -neutrality was abandoned in 2018 by the FCC. Good news for consumers and good news for the many that are dependent on a vibrant and dependent internet from schools to businesses to telehealth and the like.

Perhaps the most challenging test has been to the healthcare system. This is what the news obsessed over for weeks. Do we have enough ventilators? PPEs? Hospital beds for COVID 19 patients? Even here, the crisis of not enough soon turned into we have more than enough and perhaps too much. How does one get a fair assessment from a media obsessed with catastrophe?

Occasionally, a rational voice from authority makes its way through the noise. At one point, Dr. Deborah Birx, formerly U.S. Ambassador at Large as Global AIDS Coordinator since 2014 and now Coronavirus Response Coordinator for the White House Coronavirus Task Force, had to tamp down the mismatch of data on need and availability of ventilators: “I don’t know if you heard the report this morning [April 1], there are 8,000 ventilators in the UK,” she said. “If you translate that to United States, that would be like the United States having less than 40,000 ventilators. We have five times that.”

Now the U.S. has so many ventilators in production that we will likely export them as foreign aid to developing countries.

The crisis will continue until we get an effective treatment regime and ultimately a vaccine. Alternatively, we can just live our lives as we have done in the past and continue to do. That’s always an option. After time, we know this apocalypse will pass. The stock market will rebound, stores will reopen although not in the same way. We will be able to leave our homes, and our collective health will slowly return to some sense of normalcy.

For the moment, let’s forego the do-nothing option. Instead, the do-something approach requires us to focus on whether we are prepared for systemic challenges both at a strategic and tactical level.

Do we have enough of X, Y and Z? Or not enough? At this moment and at other moments? In this place or distributed unevenly through many places? For what population distribution controlling for sex-age and ethnic cohorts? Health statuses? And so on. A simple question becomes complex very quickly.

How do we plan for the apocalypse or, in gentler terms, for a worst-case scenario?

The popular answer is, “We need a model.”

Or that used to be the popular answer until we watched the predicted number of infections, deaths, the needed hospital beds and the like skyrocket and force major social and economic changes. The White House mindset saw deaths forecast in the millions. The leading Institute for Health Metrics and Evaluation’s epidemic model informed us that expected deaths were in the range of 100,000 to 200,000. And, then, within weeks and even days, we saw its numbers plummet — dropping to 81,766 and then again to 60,415 total deaths in the U.S., leaving us to wonder whether the dislocations were necessary.

True, the scary numbers shocked us into behaviors of shuttering businesses and isolating ourselves that we might not have adopted or might have taken less seriously. Is that the purpose of these disease or epidemic models?  To guide our understanding? To mandate behavior change?  We need a better grasp of what such predictive models do and when they can be trusted.

There was a prescient article in 2011 that examined the R 0  (reproductive ratio) used in mathematical biology to calculate the spread of an infectious disease. The upshot of the article was a commonsense evaluation: “If R 0 is to be used, it must be accompanied by caveats about the method of calculation, underlying model assumptions and evidence that it is actually a threshold. Otherwise, the concept is meaningless.”

Looking back on our experience in listening to the media, how often were these epidemic models bracketed by caveats about how the forecasts were calculated? Were we given the model’s assumptions and evidence? That is a difficult enough in an academic journal let alone a news sound bite or even a three-minute interview with the expert.

Let us take the point of view of the generally informed reader. Even assuming we are not experts, we can still make some judgment calls.

First, we’ve learned that the timing of the data release from China and the World Health Organization was delayed and some of it unreliable. Articles in Chinese academic journals were purged and epidemic commentary is now subject to government oversight.

Second, the epidemic models have updated their input with more, and newer data; the more data, the lower the deaths forecast. Moreover, the models lack an accurate base of how much the general population has been exposed. The more that have been exposed, the less severe the modeling of the epidemic is.  

We can see why federal and state officials were misled — in part by misleading and incorrect data, and second by the unknowns of how far the epidemic spread. Both of these potential errors raise serious questions about the model forecasts. Forecasts that have led to major disruption of lives.

Are the models necessary? Dr. Anthony Fauci, who was caught off guard early on in the spread of COVID 19, answered this question as much as for himself as the reporter. “Data is real. The model is hypothesis.” Fauci says all he needed to do was to look at what was happening in Italy and China, the models were unnecessary.

Still, we have a fascination for epidemic and other models. Why is that? We need to grasp why we are fascinated by such models to avoid a too facile illusion of their importance.

Climate scientist Dr. Judith Curry, who understands models from her work, describes what epidemic models are supposed to do:  “The experience with the COVID19 epidemic models, and their rapid evaluation, highlight that the value of models of a complex system is not for predictive purposes, but rather for learning and for contemplating future scenarios. We should not be fooled into thinking that just because some model calculation has completed, that we have any certainty about what is going to happen in the future. Models are best used as tools to help us explore our understanding and think carefully about uncertainties.”

My essay could easily end here. However, there is important next step in looking at models. Some think this temporary apocalypse is a bountiful experience. We are reading from climate change activists that this is a grand learning moment, especially for applying their own models for coercing individual behavior change as well as wide-scale economic change. But for me, this is the moment to draw a deep breath and consider the factors of risk, of sacrifice and the probability of being wrong, very wrong.

Yet there is ever hope in a fantastical future. Consider this passage from a recent article:

“The more we are forced to quarantine and isolate, paradoxically, the more we become cognizant of the need for mutuality and social relations and social conscience.  .  .

“[W]e can within a few years act on a far grander scale to erect, say, a million wind turbines, insulate and solarize a hundred million buildings, carve ribbons of bicycle paths throughout our cities and suburbs, and so on.”

Visions of utopian change are not uncommon. But being inspired by our temporary apocalypse is a damaging lesson, especially if it results in a permanent apocalypse. With epidemic models, we can test them over weeks and days and make quick adjustments. And we have. Climate models can only be tested in decades to come with permanent damage to supply chains, industries, social life, and the like.

Consider Dr. Curry’s long and deep understanding about how these climate models work, and more importantly, do not work — at least not in the way many of the visionaries would desire them to: “The challenge with climate models is more complex, owing to important climate factors not predicted by the climate models, long time scales and deep uncertainties in many aspects of the climate system. While climate models are useful tools for exploring our understanding of the climate system, they are inadequate to an unknown degree as predictive tools.”

Many, of course, are willing to live with this uncertainty and even impose their illusion of a new social order on an unwilling society.

Am I being too skeptical of how social change illusions work?

Consider my parents. Living in Brooklyn in the 1950s and being fascinated with what they believed to be the great healthcare system in the Soviet Union. Much better, they believed than the U.S. healthcare system. They went to the Soviet consulate and inquired about emigrating. Fortunately, there was a thoughtful Soviet counselor:  ‘Perhaps you think the grass is greener on the other side.’

The Soviet counselor was a bit sly in piercing my parents’ illusion. But honest.

We need similar honesty in what these models are and what they are not. We’ve learned about epidemic models — their value and limitations. Apparently, those fascinated with climate change models have not. Instead, they look to a permanent apocalypse to save the world.

Joe Nalven is a former associate director of the Institute for Regional Studies of the Californias at San Diego State University.