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.

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

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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

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 is 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 Qin, Steven 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]

The new Coronavirus 2019-nCoV epidemic outbreak is a mystery. Indeed, since it became a concern in China at the end of December 2019 and in the early days of January 2020 (WHO timeline), the various actors and authorities involved have been sending contradictory signals regarding the outbreak. This is perplexing, and all the more so considering the potential severity of the situation.

What is truly happening? Strategic foresight and risk analysis, i.e. analysis made specifically to anticipate and evaluate future dangers and threats and their impacts, is more than ever necessary. Strategic foresight and risk analysis will help us considering all factors involved while being as objective and impartial as possible.

In this first article, we shall first detail further the mystery and perplexing ways the outbreak appears to trigger. Then, we shall check a couple of the “truths” spread to have a baseline assessment of what is happening, using scientific and reliable official data.

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In the next articles we shall offer an explanation regarding the reasons for the cacophony we hear. Finally, we shall highlight major uncertainties that need to be considered to assess the impacts of the new Coronavirus epidemic outbreak as a global threat, i.e. using all available knowledge to look at multiple impacts across domains.

The COVID-19 (ex 2019-nCoV) Mystery or how to confuse people with contradictory signals

On the one hand, we receive signals according to which the outbreak is very serious and a global public emergency. For example, on 30 January 2020 the World Health Organization (WHO) declared we faced a Public Health Emergency of International Concern (PHEIC). China and notably the epicentre of the epidemic, the city of Wuhan in the province of Hubei, is close to a complete lock down and quarantine. Many countries repatriate their citizens from China and put them under quarantine. International companies operating in China close down their offices and airlines stop their flights with China. The list of these decisions lengthens by the day (Reuters, “Companies feel impact of coronavirus outbreak in China“, 5 Feb 2020).

On the other hand, even though it declared a PHEIC on 30 January, the WHO “does not recommend any travel or trade restriction based on the current information available.” Some media, relaying experts’ analysis underline the need not to panic, and that, despite uncertainty, the new coronavirus is “not more dangerous than a seasonal flu epidemic” (e.g. Dan Vergano, “Don’t Worry About The Coronavirus. Worry About The Flu.’ Buzzfeeds, 28 January 2020; Maciej F. Boni, Associate Professor of Biology, Pennsylvania State University, “Is the coronavirus outbreak as bad as SARS?” LiveScience, 30 January 2020).

Officials and elected political authorities, such as U.S. President Trump, outside China also stress their control over the virus and that the risk to their country is minimal (e.g. Michael Wayland, “Trump says coronavirus outbreak is ‘all under control’ and a ‘very small problem’ in US“, CNBC, 30 January 2020).

This 4 February piece of video by the BBC is a perfect case in point:

The beginning of the video is ambivalent. It tries to reassure and put the outbreak into perspective, meanwhile it also tends to minimize the epidemic. Furthermore it is done with a measure of irony and sarcasm, that could aim at ridiculing thus silencing any other analysis.

Then, one switches angle. Now, on the contrary, the video focuses on this Chinese Doctor who did identify a serious epidemic outbreak… but was silenced. Ironically, what is reproached to the Chinese authorities – we shall learn only at the end that it was actually the provincial police, and not the central authorities who were guilty of misjudgement – is to have silenced someone… which is exactly what the first part of the video does.

Nonetheless, at the end of the video, the overall message one get is that yes, it is serious but only in China. And that, anyway, all this is more or less related to the type of Chinese regime. Thus we may assume that one is expected to believe that outside China, such outbreak would never develop. We are not very far from seeing something akin to scapegoating China. This is is likely counter-productive, and also a well-known cognitive bias that mars analysis and understanding (“Bias Favoring Perception of Centralized Direction”, Heuer, Psychology of Intelligence Analysis, pp. 131-132; Module on biases in our online course Geopolitical Risks and Crisis Anticipation: Analytical Model). Meanwhile, the final message is that wherever, in China or elsewhere everything is for the best as the courageous Chinese Doctor turned whistleblower is about to be cured.

Unfortunately Dr Li Wenliang died on 7 February 2020. This sadly highlights even more the absurdity and danger of trying to deliver upbeat messages when facing a deadly epidemic outbreak.

Faced with such varied and often contradictory signals across platforms and actors, what should we believe? Is the situation dangerous and should we adapt our behaviour accordingly? Or could such a change of behaviour be ridiculous, even counter-productive? Is the new coronavirus outbreak just, in fact, business as usual? How can we be best prepared for the future if the possible futures look so uncertain? Are these conflicting signals sent creating, in themselves, anxiety? Do they favour polarisation as everyone tries to handle anxiety as s/he can? Why, finally, are such contradictory signals sent?

It is all about survival … within the “fog of epidemic”

Fundamentally the new Coronavirus epidemic outbreak, as any outbreak, is about only one thing: survival.

It is about survival for individuals. How likely am I to catch the disease? How likely are my loved ones to catch the disease? And most importantly, how likely are we to die if we catch it? Meanwhile, what to do to prevent being infected and then dying?

And it is about collective survival. How many and where can catch the disease? How many and where are likely to die? What can be done about infection and death, and by whom?

The collective questions and answers are actually more complex, as we shall see in the next article. But let us come back, for now, to the fundamental survival question.

We shall use data and measures given by official and recognised bodies and stemming from scientist work (see Resources to monitor the new Coronavirus COVID 19 (ex 2019-nCoV) Epidemic Outbreak and bibliography below).

Evolving and uncertain answers

The first and crucial element to highlight is that whatever the efforts of scientists and authorities involved, knowledge and measures about the epidemics are bound to change and evolve. Especially for new viruses, such as the COVID-19, when the first infections take place, our knowledge is close to nought. We do not even know if we are about to face an epidemic outbreak or not.

Thus, answers we get are uncertain. It is only when an epidemic is over that one can hope obtaining a completely clear understanding of it. And even once it is over, new discoveries and understanding can take place days, months, decades even centuries after it is over. For instance, there are still debates and new findings regarding the way the Black Death, the plague epidemic that devastated Europe in the 14th century and subsequent epidemics of plague until the 19th century, spread (e.g. Katharine R. Deanet al. “Human ectoparasites and spread of plague in Europe” PNAS, Feb 2018; Kristi Rosa, “Black Death May Have Spread Via Human Fleas & Lice, Not Rats“, Contagionlive, 19 January 2018; ).

When one is in the midst of an epidemic, it is as with war. We have to accept something akin to the fog of war, i.e. fundamental uncertainty (Colonel Lonsdale Hale, The Fog of War, 1896).

Indeed, if we look at an epidemic as an ideal-type we can also see it as a war of a sort. On the one hand, we have the virus or the pathogen that races to infect as many hosts as possible to replicate itself. On the other, we have human beings who try to defend themselves and defeat the aggressor. Human beings develop understanding of what is happening through scientific actors, try to keep death at bay through medical actors, while all other actors try to do what is best according to the understanding provided by science. And this is done within the framework of a race, because scale and capability matters.

Considering this uncertainty, how can we answer our fundamental questions on survival?

How fatal is the new Coronavirus?

First estimative case-fatality rates for the COVID-19 (ex 2019-nCoV)

We can get an estimative answer to this question by looking at what is called the case-fatality rate. The case-fatality rate is a statistical measure that is calculated by taking the number of death and dividing it by the number of confirmed cases for a specific disease (Encyclopaedia Britannica). In other words, the case-fatality rate tells us how many people who are infected die.

Unfortunately, as long as the outbreak lasts, our knowledge of the fatality rate is uncertain. This is why the fatality rate must be constantly monitored to adapt actions in case of evolution.

On 2 February 2020 18:10 (CET), for the 2019-nCoV, the global case-fatality rate is 362/17489 = 2,069% (data John Hopkins’ time series). On 3 February, it is 427/20701 = 2,1236% and on 4 February 494/24597= 2,01%(ibid.)

On 13 February 2020, the case-fatality rate is 1370/60360=2,2697%

However, if we look at the sole Hubei province in China, where the outbreak originated and is so far most serious, we have as fatality rate for 2, 3 and 4 February 2020 350/11177 = 3,1314%, 414/13522 = 3,0617%, 479/16678=2,8720% (data ibid). These are the lowest rates for the province since fatalities have been recorded and tested for the new coronavirus.

On 13 February 2020, for the Hubei province, the case-fatality rate is 1310/48206=2,7175%.

18 February 2020 Chinese CDC center Study: overall case fatality rate of 2.3%, with wide differences according to age (the oldest, the more at risk), health (comorbid conditions) and exposure (health workers) (The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team, “The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19)“, …).

Comparing case-fatality rates

If we compare with other diseases and outbreaks, to have an idea of the severity in terms of fatality, we have the following table:

We clearly see that the epidemic is so far more dangerous than the seasonal influenza epidemics, even though it is indeed less lethal than other coronavirus such as the SARS or other diseases such as the Yellow Fever.

On the danger of not taking the outbreak seriously when infection takes place as symptoms are mild and cases asymptomatic

Find an update on asymptomatic cases in our next article: The Coronavirus COVID-19 Epidemic Outbreak is Not Only about a New Virus.

Of course, “more fragile” people are more at risks but that is not an argument is it? Furthermore, the lump case-fatality rate calculated for the seasonal influenza epidemics also includes “more fragile” people. As a result, arguments trying to dismiss risks by comparison with the seasonal influenza epidemics are wrong. They could even be dangerous if they led people not to take the outbreak seriously.

Indeed, one of the potentially dangerous characteristics of the new Coronavirus 2019-nCoV, if we consider the early German cases, is that infected individuals are contagious while they are both asymptomatic and symptomatic, and that symptoms indicating infection can be very mild. In the video below pulmonologist Dr. Seheult, using Rothe et al. 2020 “Transmission of 2019-nCoV Infection from an Asymptomatic Contact in Germany“, NEJM, explains very clearly the situation as understood on 30 January 2020.

On 5 February 2019, the Chinese online professional community of physicians, medical institutions etc. confirmed that “Asymptomatic infection can also be a source of infection”. However, asymptomatic cases would be less infectious than symptomatic ones (ibid).

Thus, minimising or even mocking the outbreak, encouraging people not to get tested, not to seek medical advice and not to adopt basic hygiene gestures then could favour the spread of the infection. In turn, this directly heightens the number of death. In the meantime, it increases the burden on medical facilities, which can both favour infection and also, potentially, indirectly increase the case-fatality rate.

This leads us to wonder about contagion.

How contagious is the virus and how many people could be infected?

In epidemiology, a couple of measures are used to evaluate the propensity to propagation of a virus and the ease or difficulty to control an epidemic.

Estimated basic reproduction number for 2019-nCoV

R0 (R-nought) or basic reproduction number of an infectious disease is a measure that represents “the expected number of secondary cases produced by a typical infected individual early in an epidemic” (O Diekmann; J.A.P. Heesterbeek and J.A.J. Metz (1990). “On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations”, Journal of Mathematical Biology 28: 356–382).

The larger the value of R₀, the harder it is to control the epidemic.

On 29 January 2020, Qun Li et al. estimated that R₀=2.2 (“Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia“, New England Journal of Medicine). This means that one infected individual is expected to contaminate 2.2 other individuals.

Joseph T. Wu et al. in their study published on 31 January 2020 use a R₀=2.68 (Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study, The Lancet).

Other R₀ found in the literature are:

• Read et al. R₀= 3,8 (3,6 to 4) – 23 Jan 2020
• Abbott et al. R₀= 2 to 2,7 – 3 Feb 2020
• Kucharski et al. R₀= 1,6 to 2,9 – quoted by Danon et al. 12 Feb 2020
• Liu et al. R₀= 2,9 (2,3 to 3,7) – 25 January 2020

The efforts and the actions of the actors aim to reduce the R₀ so that it falls below 1, which means the virus stops propagate (Qun Li et al., Ibid.). Once this objective is reached, then the epidemic is contained.

Comparing basic reproduction numbers

If we compare the new Coronavirus with other contagious diseases, we have the following table:

Incubation and transmission of the 2019-nCoV

Meanwhile, we know that “the mean incubation period is estimated to be 5.2 days (95% CI, 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days, which supports using 14 days as an operational definition for contact tracing and monitoring” (ECDC update, 31 January 2020). The Chinese Medical Association highlights on 5 February 2020 that the “Incubation period is generally 3 to 7 days, up to 14 days, during which infectious period may exist”.

However, later studies (9 February 2020) suggests that “the median incubation period was 3.0 days (range, 0 to 24.0 days)” (Zhong et al., Clinical characteristics of 2019 novel coronavirus infection in China, doi: https://doi.org/10.1101/2020.02.06.20020974).

The possibility of contagion as the individual is asymptomatic, as seen, also favours contamination (see update in The Coronavirus COVID-19 Epidemic Outbreak is Not Only about a New Virus).

New possible ways to become infected are also identified, tested, then confirmed or not, daily, and thus should be monitored.

As of 4 February 2020, the virus “can be transmitted through respiratory droplets or through contact. There is a possibility of fecal-oral transmission (see notably Coronavirus dedicated website). Meanwhile, the possibility of transmission through surfaces must also be taken into account.

Specific measures of hygiene as recommended by most countries’ official websites should thus be observed, as here, for example by the U.S. CDC.

All these are however only partial and potentially temporary answers to the question. The virus is not yet understood enough to give a simple answer to a simple question. Furthermore, it does not seem that there is such a thing as a simple answer in epidemiology. Indeed, results depend upon various actors’ behaviours.

First modelling of the epidemic outbreak

Regarding the potential number of cases, Joseph T Wu et al. (Ibid.) published estimates from a first modelling study focusing on China on 31 January 2020. Their results, reproduced below, are expressed for major cities in China in daily incidence rates, i.e. the probability of occurrence of seeing a confirmed case of 2019-nCoV in a population – here per 1000 people – in one day. Various hypotheses are made to consider diverse measures of control.

To conclude, we shall quote Wu et al final assessment at length. It reads:

“Vaccine platforms should be accelerated for real-time deployment in the event of a second wave of infections. Above all, for health protection within China and internationally, especially those locations with the closest travel links with major Chinese ports, preparedness plans should be readied for deployment at short notice, including securing supply chains of pharmaceuticals, personal protective equipment, hospital supplies, and the necessary human resources to deal with the consequences of a global outbreak of this magnitude.”

Joseph T 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.

We thus now have a better and more honest answer to our fundamental survival questions. Yes, the new Coronavirus outbreak is serious and should not be underestimated. All actors, including individuals should behave accordingly.

This explains, for example, the European Centre for Disease Prevention and Control 31 January threat assessment cautiousness and conditional evaluation. The ECDC highlights low risks for the EU if detection and “appropriate infection prevention and control (IPC) practices” are implemented. Meanwhile, it warns that should the EU/EEA fail in its detection and IPC practices, then the risk of secondary transmission is high.

Thus, one possible factor creating the mystery of the contradictory signals is uncertainty. This uncertainty is in-built into the emergence of a new virus. However, it is also, most probably, the inability of our societies to handle peacefully this very uncertainty that favours these contradictory messages.

Another major factor triggering those confusing signals, as we started outlining, is that individual and collective survival are not exactly similar. This is what we shall see next.

References and bibliography

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Danon, Leon, Ellen Brooks-Pollock, Mick Bailey, Matt J Keeling, “A spatial model of CoVID-19 transmission in England and Wales: early spread and peak timing“, medRxiv, 2020.02.12.20022566.

Dean, Katharine R., Fabienne Krauer, Lars Walløe, Ole Christian Lingjærde, Barbara Bramanti, Nils Chr. Stenseth, Boris V. Schmid, “Human ectoparasites and spread of plague in Europe” Proceedings of the National Academy of Sciences, Feb 2018, 115 (6) 1304-1309; DOI: 10.1073/pnas.1715640115.

Diekmann, O.; J.A.P. Heesterbeek and J.A.J. Metz, “On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations”, Journal of Mathematical Biology 28, 1990: 356–382.

DXY (DXY.cn): Coronavirus dedicated website.

European Centre for Disease Prevention and Control 31 January threat assessment.

ECDC Factsheet about seasonal influenza.

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Heuer, “Bias Favoring Perception of Centralized Direction”, Psychology of Intelligence Analysis.

John Hopkins CSSE: Tracking the 2019-nCoV spread in real-time – map and graphs.

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Featured image: Image by Gerd Altmann from Pixabay [Public Domain]