Taking Control over the Coronavirus Outbreak: Challenges and Opportunities

Taking Control over the Coronavirus Outbreak: Challenges and Opportunities

Efforts to contain the outbreak of the coronavirus can be compared by attempts to shoot a moving target with various weapons at the same time, with ammunition whose effectiveness is not clear, and this under conditions with limited visibility.

Due to the coronavirus outbreak, daily life (and much more) is now severely disturbed; we are faced with new challenges: How to respond, and what the effects of these responses will (eventually) be, is not clear.

There is much uncertainty.

Important questions that concern us include: What is achievable, can the outbreak be regulated? What is the best strategy to achieve certain objectives? And how should this process – the fight against the coronavirus outbreak and its consequences – be managed to achieve the required results?

This is uncharted water that must be navigated wisely, and unavoidably, this is also a matter of trial and error. But that is no excuse to take actions without sufficiënt consideration.

In a couple of articles, I discuss some issues and ideas.

I focus on the last question: How should this process – the fight against the coronavirus outbreak – be managed to achieve the required results, i.e. a regulated outbreak? What kind of control paradigm can help us manage this challenge? It is possible to identify some principles that could be helpful.

I will discuss a control paradigm that is based on a cybernetics and a system dynamics approach.

Cybernetic systems are self-regulating, goal-directed systems that adapt to their environment. Societies can be considered cybernetic systems, that can normally maintain a certain balance, and make corrections in respons to perturbations.

The capacity of societies and their governments to deal with this particular perturbation (the outbreak of the coronavirus) and its consequences, is too limited, at this stage it seems. We lack certain instruments, and the information to apply them efficiently.

To achieve and maintain a certain balance, a cybernetic system’s operation depends crucially on the ability to predict outcomes and time lags to corrective actions (like government interventions), or on the cancelling out of random changes.

A society is a dynamic system, and the balance (equilibrium) that can normally be maintained is now disturbed; consequently; societies are now (at least in some respects) unstable.

The coronavirus outbreak not only puts enormous pressures on health care systems, but also has unprecedented economic and political consequences.

We are now collectively involved in efforts to adapt ourselves to the consequences of the coronavirus outbreak. This requires new steering measures and instruments.

Before I discuss a control paradigm in more detail, it is necessary to have a good understanding of the nature of the disruption (the outbreak) and the control challenges that face us.

The phenomenon of a pandemic in itself presents the necessary challenges, which make effective control difficult (such as a long incubation period, uncertainty about contamination mechanisms, etc.). In addition, societies, in which the virus spreads and that must be managed, are complex adaptive systems that have a tendency to show nonlinear behavior, especially when it has to deal with a distortion it is not ‘equipped’ to handle.

Because the effect and effectiveness of government measures may not be known directly (there is a delay, which is caused by the incubation period, for example), oscillations may occur (which are also partly anticipated).

Cybernetics is an approach to explore control or regulatory systems. It focuses on the structure of control systems, constraints that must be considered (like the incubation time of the coronavirus in this particular case) and possibilities. Feedback is crucial for cybernetic systems to achieve and maintain control.

From a cybernetics perspective, a distinction can be made between various components of a system, including: (1) the regulatory (or control) system, (2) the system that must be controlled, (3) the controllability of the system concerned, (4) the environment, (5) steering measures that are available to the regulatory system, and (6) feedbacks.

In this case, the system that must be controlled is the society as a whole, including the state and the government.

A government is an important part of a societal regulatory system. A government has the instruments (at least some) to influence the behavior of its citizens ‘top down’, and if necessary, it can enforce them. The society itself (the system that must be controlled) has also regulatory capabilities (and is part of the regulatory system); their bottom up control measures are in some cases more effective then centralized control.

In this case, governments also must promote self-regulation, to achieve results. Top down and bottom up control measures must reinforce each other.

Steering measures concern the set of instruments that are available to the regulatory system. Lock-downs, measures to ensure social distancing, shopping hours for elderly people, etc. are examples of steering measures. One of the problems is that their (exact) effectiveness is not (yet) clear, a limitation that is reinforced by delays caused by the long incubation time of the virus. It is also problematic, because of these conditions, to determine what effects can be attributed to what measures.

Efforts to contain the outbreak can be compared by an attempt to shoot a moving target with various weapons at the same time, with ammunition whose effectiveness is not clear, and this under conditions with limited visibility.

In cybernetics the term requisite variety is sometimes used. In case of requisite variety adequate steering measures are available to respond effectively to disturbances of a system. In this particular case, we lack requisite variety, so to speak.

Feedbacks that are at play must be identified and if possible be controlled. Hoarding of toilet paper, the abrupt closing of borders without giving these decisions the consideration they deserve, is an example of a positive feedback loop that spontaneously controls our behavior and decsions, that spread as a social infection.

System dynamics is a very useful perspective to better understand the dynamics of a dynamic system, like a society. According to this approach, feedback processes, stock and flow structures, time delays and nonlinearities (Sterman), determine the dynamics of system’s, like societies.

 A distinction can be made between positive or self-reinforcing feedbacks, and negative or self-correcting (balancing) feedbacks.

All systems, no matter how complex, consist of networks of positive and negative feedbacks, and all dynamics arise from the interaction of these loops with one another (Sterman).

The exponential spread of coronavirus infections shows that a self-reinforcing (positive) feedback structure is dominant. A negative feedback structure that is sufficiently strong to counteract the exponential growth of infections is (still) too weak.

According to Sterman (Business Dynamics, Systems Thinking and modeling for a Complex World). Three fundamental modes of behavior can be distinguished in dynamic systems:

 (1) Exponential growth that arises from positive (self-reinforcing) feedback, (2) goal-seeking, when negative feedback loops act to bring the state of the system in line with a goal or desired state, and (3) oscillation, the third fundamental mode of behavior observed in dynamic systems.

Like goal-seeking behavior, oscillations are caused by negative feedback loops. In an oscillatory system, the actual state of the system constantly overshoots its goal or equilibrium state, reverses, then undershoots and so on. The overshooting arises from the presence of significant time delays in the negative loop. The time delays cause corrective actions to continue even after the state of the system reaches its goal, forcing the system to adjust too much, and triggering a new correction in the opposite direction. There are many types of oscillations, including damped oscillations, limit cycles and chaos. A chaotic system fluctuates irregularly, never exactly repeating, even though its motion is completely deterministic.

Because of delays in the effectiveness of certain measures, it is not only difficult to determine their effectiveness, but there is also a risk for chaotic oscillations.

Such a risk not only concerns our efforts to contain the outbreak of the virus, but also the economic emergency measures that are taken to dampen the economic effects of this crisis, and their consequences.