

As COVID cases continue to rise across the US and Europe, we teamed up with complexity theory expert Dr Yaneer Bar-Yam to gain a mathematical perspective. Bar-Yam is the founder and president of the New England Complex Systems Institute, where his research focuses on the application of complexity science in social, political, and economic spheres. Bar-Yam previously worked on the Ebola containment effort in 2014 and has written on the Zika outbreak in 2018.
What is Complexity Theory, and Why Does It Apply to Pandemics?
In a nutshell, complexity science provides alternative sets of assumptions to conventional mathematics as a foundation for mathematical modelling. This can result in meaningfully different outputs compared with conventional counterparts. In particular, it finds systems behave differently at different scales, which is especially when analysing pandemics. According to Bar-Yam, this is because the severity of symptoms causes the continuity of the outcome distribution to break down, and changes in the scale of the pandemic alter its behaviour and responsiveness to policy action.
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As COVID cases continue to rise across the US and Europe, we teamed up with complexity theory expert Dr Yaneer Bar-Yam to gain a mathematical perspective. Bar-Yam is the founder and president of the New England Complex Systems Institute, where his research focuses on the application of complexity science in social, political, and economic spheres. Bar-Yam previously worked on the Ebola containment effort in 2014 and has written on the Zika outbreak in 2018.
What is Complexity Theory, and Why Does It Apply to Pandemics?
In a nutshell, complexity science provides alternative sets of assumptions to conventional mathematics as a foundation for mathematical modelling. This can result in meaningfully different outputs compared with conventional counterparts. In particular, it finds systems behave differently at different scales, which is especially when analysing pandemics. According to Bar-Yam, this is because the severity of symptoms causes the continuity of the outcome distribution to break down, and changes in the scale of the pandemic alter its behaviour and responsiveness to policy action.
Bar-Yam explains that a pandemic cannot be thought of in continuous terms. Instead, we ought to view the disease as a discrete variable which is either 0 (clean or small number) or 1 (continuous spread). The nature of the two phases is also discontinuous. The former can be easily managed, while the latter cannot and has dire consequences on the current and future health of the population.
Analysing Conventional Health Policy Thinking With Complexity Theory
Bar-Yam views health experts in many Western countries to have incorrectly used the conventional framework of a flu outbreak to explain COVID’s spread, adjusting parameters for transmissibility and other minor variables. But Bar-Yam thinks this approach may be inappropriate given the severity of the outbreak’s consequences, which he labels a Black Swan scenario. He cautions against comparing COVID to the flu, since scientists have shown COVID causes lasting organ damage in addition to higher death rates.
Due to this policy bias and mis-comparison of COVID to the flu, Bar-Yam believed many Western countries have responded with public health policies aimed at disease containment and treatment. On the other hand, regions such as Asia and Africa with recent experience of severe disease outbreaks have followed a different policy path of strong early intervention aimed at disease prevention.
Short and Complete Lockdown Better than Repeated Partial Lockdowns.
On the economic side of the equation, Bar-Yam argued that many Western countries have tended to embrace a policy of compromise between disease containment and economic support. He argues that instead of getting the best of both worlds, this has resulted in the ‘worst of both worlds’.
The cost of a hard and soft lockdown is similar. By aiming for containment rather than elimination, a soft lockdown policy actually sets the economy up for higher total costs. This is because governments must repeatedly implement soft lockdowns to contain infections within an acceptable range. By lengthening the timeframe of analysis, policymakers will discover that there is no trade-off between disease containment and economic cost. Rather, they become correlated variables.
The Way Forward: Complexity Theory’s Answer to Ending the COVID Crisis
From a complexity theory approach, the key policy recommendation is to aim for disease elimination rather than containment. Using the alternate framework provided by complexity theory, the two key variables that explain and can control the spread of the disease are 1) ‘green’ zones of 0 (or close to 0) infections and 2) long-range transportation. As such, Bar-Yam recommends that policymakers focus on creating zones of 0 infection and cutting nonessential travel to prevent reinfection.
A Call to Action: The Business Community Must Lead the Response
Bar-Yam also believes that elimination is the key to combatting the COVID crisis and that local communities have a fundamental role to play in ensuring their own safety. If you are interested in joining Bar-Yam and others in their work to contain COVID, reach him here. He and his group have published many resources and data analyses on the current spread of COVID and recommendations for communities to contain its spread locally. For more information, visit EndCoronavirus.org.
Angela Xu, CFA has had four years of experience investing in macro, emerging markets, and quantitative hedge funds. She holds a BSFS in International Politics from Georgetown University.

(The commentary contained in the above article does not constitute an offer or a solicitation, or a recommendation to implement or liquidate an investment or to carry out any other transaction. It should not be used as a basis for any investment decision or other decision. Any investment decision should be based on appropriate professional advice specific to your needs.)