Complex Systems Theory Explains Why Covid Crushed the World

The more complicated and efficient a system gets, the more likely it is to collapse altogether

Image: zf L/Getty Images

Human history is a long saga of people learning to harness ever-increasing amounts of energy to maintain ever more complex, ordered systems, punctuated by periodic collapses. The Romans, the Maya — when civilizations became more complex than they could maintain, with the energy and technologies they had, in the face of changing conditions.

At that point, small stresses sent overstretched social systems into a rapid downward spiral, which ended with major losses of people and social organization, as one stable complex system made a rapid nonlinear descent to a less complex one. But after a setback, humanity always innovated and rebuilt, a little bigger and more complex than before.

This process is integral to how we should understand pandemics. We now live in the most complex civilization the world has ever seen and the first to encompass the entire planet. Many believe that this makes us resilient to shocks. But, say the complexity theorists, the more complex systems get — the more tightly coupled their component parts, the faster and denser the communication and transport links that keep them all coordinated, the more closely each part relies on many other parts — then the more rigid the system gets overall, the less resilient, the more likely to collapse.

Moreover, complex systems — natural ecosystems as much as human societies — tend to become more efficient, with more specialized components and fewer redundant linkages, because that saves money or energy. Thomas Homer-Dixon, a Canadian expert in complex systems and author of The Upside of Down, notes that a mature forest may have one kind of bacteria fixing its soil nitrogen, whereas at an earlier stage of development, it had a dozen.

Similarly, protective medical gear and the active ingredients for common, emergency drugs used to be produced widely. Michael Osterholm is an epidemiologist who has studied the possible impacts of pandemics. He explained to me that now, a few factories in China make nearly all of these vital supplies, as the global industry takes advantage of low labor costs and economies of scale. This is efficient. Hospitals rely on constant, just-in-time deliveries of these items, too: keeping stocks costs money, so this is also efficient.

During the early days of the Covid-19 pandemic when much of China was affected, there were fears deliveries would stop, either because China needed more of these things than usual or because factories might have to shut down as employees were quarantined. If things had gotten much worse or the shutdown had lasted longer, they might well have. There were no alternate sources. Efficient coupling between parts of the system would have led to a breakdown.

Homer-Dixon says increasing complexity makes societies more resilient only up to a point. Connections between villages might mean one comes to the other’s aid in an attack. But as the villages become more tightly coupled, both may suffer when one is attacked. A loose network absorbs shock; a tightly coupled one transmits it. That is happening in the Covid-19 pandemic.

Countries go into lockdown; people stop shopping, traveling, and producing; and the effects ricochet through a tightly coupled global economy. The global supply chains of money, materials, people, energy, and component parts that underpin industries falter and break.

Airlines go under as they are not set up to weather even a temporary disappearance of travelers. Malaria worsens in Africa as insecticide and antimalarial bed net deliveries falter. Microcredit that underpins small businesses throughout the developing world defaults because payment collectors are locked down, causing ramifications throughout an economy.

The number of people facing starvation threatened to double in April 2020, warned the World Food Programme, even though the same amount of food was available. Lockdowns meant poor people, from tuk-tuk drivers to cleaners to food vendors, could no longer earn money to buy it — and this happened just as restricted global transport made it hard to get donated food to them.

Just the fact that an outbreak in China went pandemic as quickly as it did is a testament to the tight coupling in our global system. For human viruses, the vector is people and airplanes. Scientists tracked this pandemic using computer models and databases of global air passengers. Alessandro Vespignani of Northeastern University calculated that the countries at highest risk of importing a case of Covid-19 were in Asia, followed by North America and Europe — that is exactly how the virus traveled.

Vittoria Colizza of Sorbonne University in Paris calculated that the African country most likely to import a case was Egypt, followed by Algeria. Those countries, in that order, got Africa’s first cases.

The fact that the world is a complex system helps explain how this pandemic happened.

First, it means our system has a management problem. People tend to see things in a simple linear way. That’s not a criticism — we can’t usually control anything but a few, simple, direct interactions within our complex social system. So faced with a problem, those are the solutions on offer. We cannot always anticipate how the rest of the complex system will impinge.

Chinese medical authorities said, “we had a close call with SARS and we have bird flu, let’s have doctors signal any unexplained pneumonia, and we’ll see any clusters of cases faster.” Scientists said, “we have a problem with animal viruses infecting people, let’s swab a lot of animals and see what they’re carrying.” Pandemic planners said, “if we have a flu pandemic, we’ll need ventilators and masks, so we’ll stockpile them.”

All great ideas, and it was a good thing people did or tried to do all of them. But complex interactions took an unexpected hand. In December 2019, when it was clear the unexplained pneumonia wasn’t bird flu, for some reason Wuhan doctors were told not to use the alert system. Scientists found a virus much like Covid-19 in bats and warned of its pandemic potential, but that didn’t nudge research agencies to fund renewed work on coronavirus vaccines. The 2008 market crash — itself a textbook product of complexity and tight coupling in the global financial system — triggered government cuts that tightened health budgets. Then the 2009 flu pandemic was less than catastrophic. Result: hospitals, with few exceptions, did not get the pandemic stockpiles envisioned in 2006.

Western countries have been talking about pandemic preparedness since bird flu rang alarms in the early 2000s. This was especially true in the U.S., which was widely expected to be the country best prepared for something like this. But when Covid-19 hit the U.S., the plan was largely abandoned, while unexpected complications set in everywhere.

Health workers didn’t have enough protective gear and ended up sick or in quarantine. Insurance rules meant people couldn’t afford to get tested. For weeks, they couldn’t get tests in any case because of problems with one test at the U.S. CDC in Atlanta. Employees with no paid vacation came in to work, hoping it was just flu. The virus spread earlier and farther than surveillance systems could detect, partly due to years of cuts to public health.

Pandemic planners actually warned about many of those problems. But no one could change enough of the system to head them off, and when a severe pandemic didn’t materialize after years of warnings, leaders lost interest. We can’t prepare a complex system for events like pandemics with small, linear solutions to local parts of the problem — we also can’t prepare when we lose focus on any given risk after a few years.

Excerpted from COVID-19: The Pandemic That Never Should Have Happened and How to Stop the Next One by Debora MacKenzie. Copyright Debora MacKenzie 2020. All rights reserved.

Writer on infectious disease, complexity, the science of humans. Author of “Covid-19: the pandemic that never should have happened & how to stop the next one”.

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