Last updated on February 21st, 2020 at 12:42 pm

The coronavirus epidemic is “a very grave threat” because “Viruses can have more powerful consequences than any terrorist action”. This is what the WHO Director stressed as an international meeting of 400 scientists and other experts convened in Geneva (Sarah Boseley, “Coronavirus should be seen as ‘public enemy number one’, says WHO“, The Guardian, 11 Feb 2020).

Thus, as for any threat of this magnitude, it is crucial to fully understand the danger to be able to design the right course of actions.

In this regard, this article explains that to understand the new Coronavirus COVID-19 (ex 2019-nCoV) epidemic outbreak and its dynamics, we must consider not only the virus but also move to a larger framework taking into account all actors. This is congruent with the activation of a UN Crisis Management Team on 11 February 2020.

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However the UN team will focus on the “wider social, economic and developmental” implications of the outbreak.

Here what we argue is that the right model for an outbreak must consider all actors and interactions, not only because of non-medical impacts as done by the UN, but also because of feedbacks on the outbreak itself.

We previously highlighted that the new coronavirus 2019-nCoV was apparently surrounded by a mystery. This mystery was generated by confusing signals sent by various actors regarding the severity of the outbreak. There, we pointed out that the very uncertainty stemming from the novelty of the virus was one factor creating the mystery. Meanwhile, these confusing signals were also dangerous and could favour the very spread of the epidemic.

Yet, the story does not stop there. The confusing signals also emerge from the difficulty, for all actors, to handle the epidemic. The heightened difficulty is best understood if we consider all the actors and their interactions. This is the focus of this article.

First we explain that, to understand an epidemic outbreak, we must consider all the actors and their interactions and not focus exclusively on the new Coronavirus COVID-19. Then, we detail further this model. We explain how we can consider and model the interactions among actors to include feedbacks. We notably highlight a couple of key elements, including the importance of conflicting priorities and goals.

Revising our model for understanding an epidemic outbreak

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What is puzzling in the new coronavirus COVID-19 outbreak, is, actually, the reactions of human beings. This is notably the case when these individuals have authority status, be it health authorities, political authorities or CEOs and boards of large international companies.

Looking at this behavioural human dimension is what will give us the key to understanding why actors send confusing information.

Indeed, we have here a strong signal that an outbreak is not exclusively a medical and hard science issue. It is also about human beings and the way they perceive, behave, and react to the disease. This was, for example, already outlined by Lofgren and Fefferman (2007), when the authors highlight the importance of the use of games to validate simulation models in applied epidemiology that allow for incorporating important human behaviours. Similarly, the 2002-2003 SARS epidemics was examined through the lenses of political science, and seen, for example “as a political process, involving political leaders, administrators and health professionals” (Tom Christensen and Martin Painter, “The Politics of SARS“, Policy and Society, 2004).

We are thus faced with a situation where actors interact according to various underlying processes. These processes can be understood through the use of sociological, political and international relations knowledge.

Including politics and political science

We have to include politics because the role of political authorities is crucial. This is exemplified in China, or more recently by the UK “Secretary of State [who] declares that the incidence or transmission of novel Coronavirus constitutes a serious and imminent threat to public health” (Department of Health and Social Care, “Secretary of State makes new regulations on Coronavirus“, gov.uk, 10 February 2020; e.g: The Guardian Live Coronavirus outbreak). Another instance is Singapore raising its threat level on 7 February 2020 (Aradhana Aravindan, John Geddie, “Singapore lifts virus alert to SARS level, sparking panic buying“, Reuters, 7 February 2020).

Taking into consideration international relations

We must also incorporate international relations because an epidemic in general, the COVID-19 outbreak in particular, is by essence potentially global while political authorities are involved. As a result, if we have many political authorities involved that are bound to interact, then we are in the realm of international relations.

The involvement of international organisations, such as the WHO, is an instance of this international relations’ layer. Furthermore, besides its actions, the WHO also promotes a specific agenda related to a multilateralism as the next sentence evidences: “This is exactly what WHO is for – bringing the world together to coordinate the response. That’s the essence of multilateralism, which is very important for the world.” (WHO Director-General’s remarks at the media briefing on 2019-nCoV on 11 February 2020).

Thus, here we see an international actor positioning itself at the international ideological and normative level (see the two schools of international relations, liberalism versus realism, e.g. Korab-Karpowicz, W. Julian, “Political Realism in International Relations“, The Stanford Encyclopedia of Philosophy (Summer 2018 Edition), Edward N. Zalta (ed.); as well as the English School of International Relations theory, e.g. Tim Dunne, The English School, The Oxford Handbook of Political Science, Edited by Robert E. Goodin, Jul 2011).

Out of these interactions among actors, dynamics unfold. This framework will allow for understanding the outbreak and its mutiple impacts, monitoring it properly, warning about it, as well as planning in advance through strategic foresight and scenarios.

The actors’s interactions in the outbreak

Each (collective) actor involved in the outbreak must be understood not only in itself but also in its relationships to all the other actors. For each actor and group of actors, the beliefs and perceptions about oneself, others, the virus and the situation must be taken into account. We must also consider the way the beliefs and perceptions evolve. Indeed, these beliefs and perceptions will condition behaviour and actions.

Ensuring survival under conditions of uncertainty

For instance, initially, we focused on the importance of survival for each actor. Ultimately this remains true. However, we must locate this objective into a more adequate framework. For example, how one reaches survival matters. When actors start thinking in terms of survival is also crucial. Thus, we must factor in the uncertainty related to the novelty of the virus, because this novelty bears upon the actors’ assessment of the situation. As a result, this uncertainty will also weigh upon decisions and actions. Meanwhile, we must also consider competing objectives and the need for actors to balance these needs.

Reducing mobility is the only available strategy to buy time to develop a treatment or a vaccine

Let me explain this further. From the point of view of all political authorities, transmission must be stopped, while a way to cure people or make them safe, even if infected, is developed. Thus, time must be bought to allow scientists to understand the virus and, finally, to develop a vaccine as well as proper treatments.

As a reminder, there no vaccine nor treatment so far for the 2019-nCoV. If a possible vaccine has been found as claimed in Hong Kong, at least one more year will be needed for tests notably to make it ready for human use (David Ho and Cornelia Zou, “Hong Kong researchers develop coronavirus vaccine“, Bioworld, 4 February 2020; Video below by Elaine Ying Ying Ly “Vaccine for new coronavirus unlikely to be ready before outbreak is over, says Sars expert”, SCMP, 10 February 2020).

The WHO confirmed that a vaccine was at best 18 months away, i.e. July 2021 (Remarks 11 Feb 2020). Meanwhile, “Chinese scientists are testing two antiviral drugs” (Yawen Chen, Elaine Lies, “Coronavirus deaths in China spike, Japan has first fatality“, Reuters, 13 February 2020).

Considering this race where time must be bought, a “simple” action would be to stop all travels and contacts between human beings, as well as between human beings and animals. Stopping mobility, as detailed, for example, in Wu et al.’s epidemiologist modeling work is key to control an epidemic (Wu et al. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study, The Lancet, 31 January 2020).

Reducing mobility: how, for how long and how much

This is anyway at the basis for many initial public policies regarding the 2019-nCoV outbreak, but – and the but matters – mobility and contacts are not completely stopped, by design or by incapacity.

Capacity to reduce mobility

First, this simple action is not at all simple to implement in real life, all the more so if contacts with animals must also be taken into account.

For example, Wuhan, the initial epicentre of the epidemic has been all but locked down and in quarantine since 23 January 2020, people being commanded to stay home (CNA, “China halts flights and trains out of Wuhan as WHO extends talks“, 23 january 2020; “Quarantine” Wikipedia). Furthermore, measures to stop mobility were progressively reinforced (Amy QinSteven Lee Myers and Elaine Yu, “China Tightens Wuhan Lockdown in ‘Wartime’ Battle With Coronavirus“, The New York Times, 6 February 2020).

Yet, there has also been the entire period between the possible beginning of the epidemic and the time when it was noticed, then identified, during which mobility has not been stopped and thus during which infection has spread (e.g. Wu et al. Ibid., Lauren Gardner et al., “Update January 31: Modeling the Spreading Risk of 2019-nCoV“, John Hopkins CSSE, 31 January 2020).

Reducing mobility but for how long?

Up to 12 February 2020, the understanding of the disease and its development had led political authorities across the globe to create a system of containment and quarantine that lasted 14 days.

However, Chinese medical doctors and scientists published on 9 February 2020 on MedRVix a new study that could revise the length of the quarantine needed: Clinical characteristics of 2019 novel coronavirus infection in China, doi: https://doi.org/10.1101/2020.02.06.20020974.

This study is not yet peer-reviewed, thus, is considered scientifically as not yet fit to be used for clinical purposes. Yet, in that case, considering the potential impact, can authorities wait? This study “extracted the data on 1,099 patients with laboratory-confirmed 2019-nCoV ARD from 552 hospitals in 31 provinces/provincial municipalities through January 29th, 2020”. Its authors appear to be 30 scientists and doctors from the China Medical Treatment Expert Group for 2019-nCoV. Thus assuming a modicum of check is done by MedRVix, the study so far looks genuine.

According thus to this study, “The median incubation period was 3.0 days (range, 0 to 24.0 days)”. This means, in the word of Prof Paul Hunter, Professor in Medicine, University of East Anglia (UEA) that

“…The suggestion that the incubation period may extend up to 24 days is definitely worrying, especially for people currently in quarantine who may, therefore, expect to spend longer is isolation.

“However, the median incubation period remains very short at 3 days. This means that a half of people who will get ill will have developed their illness within 3 days of the initial contact and the proportion of people with the really long incubation periods will be very small. …”

science media centre ” expert reaction to preprint on the incubation period of the novel coronavirus”, 10 February 2020).

The precautionary principle would demand that now all quarantines last not 14 days anymore but 24 days.

This shows how difficult it is to properly reduce the mobility when one knows so little about the virus.

Reducing Mobility versus other imperatives

Finally, other beliefs and goals also come into play that stop or delay drastic measures regarding mobility.

Let us continue with the telling example of Wuhan.

During the lockdown period between 23 January and 10 February 2020, for example, some high tech manufacturers considered as critical industries did not stop operations. This is in line with the importance of high technology and its development for China, with China’s national interest and objectives (see Helene Lavoix, “Actors and stakes: from IT companies to China and other states” in Artificial Intelligence, the Long March towards Advanced Robots and Geopolitics, The (Red) Team Analysis Society, 13 may 2019). For instance, “Yangtze Memory Technologies Co Ltd (YMTC), a state-backed maker of flash memory chips based in Wuhan” continues operations (Reuters, “Huawei, Chinese chip makers keep factories humming despite coronavirus outbreak“, 3 Feb 2020). Semiconductor Manufacturing International Corp (SMIC), one key chip foundry for China, with “facilities in Tianjin, Shenzhen, Beijing, and Shanghai” also did not stop work (Ibid).

Allowing for other goals when anticipating and modeling the outbreak and its impact

Thus what we see here is the Chinese political authorities trying to achieve three competing goals. They try to stop the infection to spread outside Wuhan and the province of Hubei, yet to save as many as possible in Wuhan and Hubei. Meanwhile they also aim at not endangering industries critical to their national interest.

It is thus clear that we cannot understand the epidemic outbreak and anticipate its spread, its lethality and its multiple impacts if we only focus on the virus and reactions to it.

Modeling the complex set of interactions involved in an epidemic

Thus, the easiest model to follow to map out the complex set of interactions for an epidemic is to look, for each actor or group of actors, at their objectives and needs, as mediated by their beliefs, and at their capabilities, out of which results their actions. These actions will in turn impact the other actors, their perceptions and beliefs, their capabilities and finally their actions. We are here in the framework of complex feedbacks.

As exemplified above, the Chinese political authorities must make sure their citizens survive the epidemic, but also that all the other types of material security are provided, while present and future needs in terms of protection of foreign enemies, as well as domestic peace are ensured (for the mission of political authorities, Barrington Moore, Injustice…, 1978). Hence, for example the decision to reopen factories and to send back citizens to work, progressively, starting on 10 February 2020 (e.g. Bangkok Post, “China stutters back to work as virus deaths soar“, 10 February 2020).

China, most probably, assessed it controlled well enough the outbreak to take the risk to stop the worst kind of mobility reduction. It also could probably not afford any longer a situation with a probably very large cost to its economy, with companies unable to pay salaries and employees starting to be laid off (e.g. Reuters, “Coronavirus Death Toll Surges as Fears Grow for Chinese Economy“, The New York Times, 11 February 2020).

Meanwhile., the situation was also starting to seriously disrupt supply lines across the globe. For example, on 7 February 2020, the South Korean government had to ask Chinese provincial governments to start again production because Hyundai in Korea had to stop automobile production as its supply chain was disrupted (Joyce Lee, “South Korea asks China for help in resuming production at auto parts plants“, Reuters, 7 February 2020). Here the risk for China is also related to a loss of markets, as manufacturers could turn towards other providers, such as Turkey, Bangladesh or Vietnam, for example (e.g. Ceyda Caglayan, “Turkish clothes makers see orders shifting from coronavirus-hit China“, Reuters, 7 February 2020). This would lead to markets lost for a very long period.

In the meantime, these decisions were also accompanied by a 6 February 2020 Chinese decision to amend guidelines on classification. According to the new guidelines, patients who tested positive whilst not exhibiting symptoms would not be counted anymore as “confirmed cases” but only as “positive cases” (Keoni Everington, “China changes counting scheme to lower Wuhan virus numbers“, Taiwan News, 11 February 2020 and tweet below by freelance reporter Alex Lam.

Yet, there is controversy. For example, Sylvie Briand, WHO director of global infectious hazard preparedness “dismissed earlier medical studies of some people having transmitted the disease without showing signs, saying they actually had “minor symptoms” that went undetected.” (Stephanie Nebehay, “WHO working on recommendations for resuming flights to China“, Reuters, 4 February 2020).

On the other hand, we have scientific studies suggesting otherwise, such as Rothe et al. 2020 “Transmission of 2019-nCoV Infection from an Asymptomatic Contact in Germany“, NEJM; Hiroshi Nishiura, et al., and work by Prof Hiroshi Nishiura of the Hokkaido University as mentionned in Kyodo News, “Half of secondary virus infections occur in incubation period: study“, 8 February 2020).

Actually, medical doctors will certainly settle the matter, and Hiroshi Nishiura et al. call for more study on the possibility of asymptomatic infections ( “Estimation of the asymptomatic ratio of novel coronavirus (2019-nCoV) infections among passengers on evacuation flights“, medRxiv 11 February 2020).

In the meantime, we may consider that the problem may also become the detection of symptoms, what is considered as symptom and at which level of strength.

One way or another, contagion by people which did not develop symptoms severe enough to be detected may be a likely explanation for the infection across Europe triggered by what has been called the “super spreader” (Haroon Siddique, “‘Super-spreader’ brought coronavirus from Singapore to Sussex via France“, The Guardian, 10 Feb 2020).

Not counting asymptomatic but infected individuals as confirmed cases would automatically lower the number of confirmed cases. This may be – or not – what led to the improvement in count of cases seen in China.

We may wonder about the rationale behind the Chinese decision. However, we may not exclude that it is linked to the need to see economic objectives met, while infection by individuals with undetected symptoms is assessed as less dangerous than infection with obviously symptomatic individuals. Meanwhile, considering the fact the medical community still does not know that much about the virus, this decision may prove dangerous.

It is nonetheless difficult to infer any intention behind statistical changes because, on 12 February 2020, China also decided to change the way to diagnose those who tested positive and this led to a sharp increase in both confirmed cases and deaths (BBC News, “What is the new diagnosis method?” in Coronavirus: Sharp increase in deaths and cases in Hubei, 13 February 2020).

Interestingly, as for the decision not to count asymptomatic cases, it is a freelance reporter from Hong Kong and then the Taiwan News that relay the information, highlighting too the political and international relations character of the epidemic outbreak.

Actually, China here, with these two changes created a new uncertainty that could have negative impacts. Indeed, as China seeks to see airlines resuming flights (Nebehay, ibid.) and to see activity going back to normal, creating uncertainty may not be the best way to restore confidence.

Thus, each actor must take its decisions regarding the epidemics considering conditions of high uncertainty, factoring in its other missions, while also modeling all the other actors’ perceptions and resulting actions. To be able to do that at best, they thus need to anticipate, and notably to consider timing, which is what we shall see with the next article.

The highly uncertain conditions surrounding an epidemic outbreak and the need to balance properly sometimes conflicting goals all contribute to the diffusion of confusing messages.

It thus enhances the need for proper anticipation using a proper model that is constantly reevaluated and monitored. Meanwhile the importance of the timing of actions increases. This is what we shall see with the next article.

Detailed references and bibliography

Aradhana Aravindan, John Geddie, “Singapore lifts virus alert to SARS level, sparking panic buying“, Reuters, 7 February 2020.

BBC News, “What is the new diagnosis method?” in Coronavirus: Sharp increase in deaths and cases in Hubei, 13 February 2020

Boseley, Sarah, “Coronavirus should be seen as ‘public enemy number one’, says WHO“, The Guardian, 11 Feb 2020.

Caglayan, Ceyda “Turkish clothes makers see orders shifting from coronavirus-hit China“, Reuters, 7 February 2020.

Chen, Yawen, Elaine Lies, “Coronavirus deaths in China spike, Japan has first fatality“, Reuters, 13 February 2020.

Christensen, Tom & Martin Painter (2004) The Politics of SARS – Rational Responses or Ambiguity, Symbols and Chaos?, Policy and Society, 23:2, 18-48, DOI: 10.1016/ S1449-4035(04)70031-4.

Department of Health and Social Care, “Secretary of State makes new regulations on Coronavirus“, gov.uk, 10 February 2020;

Dunne, Tim, The English School, The Oxford Handbook of Political Science, Edited by Robert E. Goodin, Jul 2011

Everington, Keoni, “China changes counting scheme to lower Wuhan virus numbers“, Taiwan News, 11 February 2020.

Gardner, Lauren, et al., “Update January 31: Modeling the Spreading Risk of 2019-nCoV

Korab-Karpowicz, W. Julian, “Political Realism in International Relations“, The Stanford Encyclopedia of Philosophy (Summer 2018 Edition), Edward N. Zalta (ed.);

Kyodo News, “Half of secondary virus infections occur in incubation period: study“, 8 February 2020.

Lavoix, Helene “Actors and stakes: from IT companies to China and other states” in Artificial Intelligence, the Long March towards Advanced Robots and Geopolitics, The (Red) Team Analysis Society, 13 may 2019).

Lofgren, E.T. and N.H. Fefferman. 2007. “The Untapped Potential of Virtual Game Worlds to Shed Light on Real World Epidemics”. The Lancet Infectious Diseases. 7:625-629.

Moore, B., Injustice: Social bases of Obedience and Revolt, (London: Macmillan, 1978).

Nebehay, Stephanie, “WHO working on recommendations for resuming flights to China“, Reuters, 4 February 2020

Nishiura, Hiroshi, Tetsuro Kobayashi, Takeshi Miyama, Ayako Suzuki,  Sungmok Jung, Katsuma Hayashi, Ryo Kinoshita, Yichi Yang, Baoyin Yun, Andrei R. Akhmetzhanov, Natalie M Linton, “Estimation of the asymptomatic ratio of novel coronavirus (2019-nCoV) infections among passengers on evacuation flights”, medRxiv 2020.02.03.20020248; 11 February 2020; doi: https://doi.org/10.1101/2020.02.03.20020248.

Reuters, “Huawei, Chinese chip makers keep factories humming despite coronavirus outbreak“, 3 Feb 2020

Rothe et al. 2020 “Transmission of 2019-nCoV Infection from an Asymptomatic Contact in Germany“, NEJM;

Science media centre ” expert reaction to preprint on the incubation period of the novel coronavirus”, 10 February 2020).

The Guardian Live Coronavirus outbreak.

Siddique, Haroon, “‘Super-spreader’ brought coronavirus from Singapore to Sussex via France“, The Guardian, 10 Feb 2020

WHO Director-General’s remarks at the media briefing on 2019-nCoV on 11 February 2020.

Zhong et al., Clinical characteristics of 2019 novel coronavirus infection in China, doi: https://doi.org/10.1101/2020.02.06.20020974


Featured image: Photo by Zhou Guanhuai – A screen display showing “early discovery, early report, early quarantine, early diagnosis, early treatment” during Wuhan coronavirus outbreak in Hefei, Anhui, China, 8 February 2020 – [CC BY-SA]


About the author: Dr Helene Lavoix (MSc PhD Lond)

Dr Helene Lavoix, PhD Lond (International Relations), is the Director of The Red (Team) Analysis Society. She is specialised in strategic foresight and warning for national and international security issues. Her current focus is on Artificial Intelligence, Quantum Science, and Security. She teaches at Master level at SciencesPo-PSIA.

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