The science of risk

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The pandemic shows the science of risk shapes our lives.

On March 16, a group of epidemiologists at Imperial College London published the results of a model that showed letting the new coronavirus run unchecked through the population could result in 500,000 deaths in the U.K. and 2.2 million deaths in the U.S. The same day, Prime Minister Boris Johnson urged all citizens to stay at home and President Donald Trump laid out voluntary social distancing measures. Both leaders' advisers had received a copy of the model.

Even if you don't live in the U.K. or the U.S., risk models like the one used by the Imperial team are now governing your life. More than 2.5 billion people are in countries that are on lockdown or face severe restrictions on social gatherings—with the number growing.

Risk models are mathematical representations of complex systems that help show what can happen under specific conditions, and it didn't take a pandemic to introduce them into our lives. Some widely used models have low uncertainties, such as those determining the price of your auto insurance premiums based on demographic data produced from millions of insured drivers. Models projecting how the economy will perform if inflation suddenly rises carry far more uncertainty.

No model always gets it right. "Even I find it tough to judge how much I should believe what comes out of a modeling exercise," said David Spiegelhalter, professor of public understanding of risk at the University of Cambridge.

Public awareness of big problems often starts with modeling. Climate change first entered public consciousness with the help of models that used well-known physics and, initially, little observational data.

But models are only as good as the assumptions they're based on. Climate scientists are still not sure how much of a role clouds, which can trap or reflect sun's heat based on their type and their altitude, play in affecting the planet's warming. And more than three months after Covid-19 emerged in China, scientists still don't know how many people can infect others without suffering from symptoms themselves. Because of the uncertainties, in both cases, current models produce large differences between the lower and upper bounds of forecasts.

"That uncertainty does not mean we don't know what to do," said Spiegelhalter. "It actually is a guide to being more cautious."

That's why drastic steps are sometimes taken after reading risk models. In the case of Covid-19, billions of people remain on lockdown until the growth in the number of infections comes under control. For climate change, where policy responses have never been anywhere near as draconian, models have been used to make the case for painful measures such adopting high carbon taxes now rather than gradually increasing taxes as things get worse.

The highest use of models is to save us from our own habitual blindness to uncertainty and risks, especially when confronted with events that don't always make intuitive sense. "Modeling plays an essential role," said Baruch Fischoff, professor at Carnegie Mellon University and an expert on risk. That's because both pandemics and climate change are "non-linear" events, which humans can't really wrap their heads around.

The non-linear math of the Covid-19 pandemic works like this: Every person infected with the new coronavirus is estimated to infect nearly three others, who will go on to infect nine, who will infect 27 and so on. With climate change, non-linear math means every one-tenth degree Celsius of warming will have a more severe impact on the climate than the previous tenth degree.

After the pandemic is brought under control, there's hope that the experience might lead to more "risk thinking" among leaders in governments and businesses, said Nigel Brooks, a partner at the law firm Clyde & Co who runs their practice on climate risk. Having experienced such an event, Brooks believes it is likely more leaders will consider "tail risks," events that had a low chance of occurring.

For example, extreme flooding the Netherlands experienced in 1953, which caused water levels to rise as much as 18 feet (5.5 meters) above sea level in some parts and killed nearly 2,000 people, led to the creation of Delta Works, the world's largest infrastructure project to protect two-thirds of the country's land mass that is at risk of flooding.

Global risks like pandemics and warming temperatures are qualitatively different from localized catastrophes, such as small epidemics, wars between two countries, or natural disasters. They can't be solved by one country and necessarily need global solutions.

"[Global problems] change the basis on which we can trust in science and trust in institutions, which are charged with managing these risks," said Jamie Wardman, professor of risk management at the University of Nottingham. That's why "risk has become central to our understanding of how the world has been transforming in the past century."

Akshat Rathi writes the Net Zero newsletter on the intersection of climate science and emission-free tech. You can email him with feedback.