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.
- How China Could Win the War against the Covid-19 Pandemic
- The Red Team Analysis Weekly – 14 January 2021
- Is the COVID-19 Second Wave coming to China?
- France and 3 Scenarios for the COVID-19 Second Wave
- Arctic China: Towards New Oil Wars in a Warming Arctic?
- Scenarios to Navigate the COVID-19 Pandemic and its Possible Futures (1)
- Scenarios for the Covid-19 and Post-Covid-19 Worlds – a Bibliography
- Chimerica 3: The geopolitics of the U.S.-China turbo-recession
- COVID-19 Vaccine and Uncertainty Early Warning
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.
- How China Could Win the War against the Covid-19 Pandemic
- The Red Team Analysis Weekly – 14 January 2021
- Is the West Losing the Warming Arctic?
- Adapting to the Burning World?
- Global Apocalypse Now, the California Way
- Arctic China: Towards New Oil Wars in a Warming Arctic?
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:
|Disease||If left untreated||With treatment|
|Middle East respiratory syndrome coronavirus (MERS-CoV) 2012-ongoing|| 34,4%|| No known treatment|
|Severe acute respiratory syndrome coronavirus (SARS-Cov) 2002-2003||9,6% (WHO)||
|Plague||50-60% (WHO)||Africa 9.2% Americas 6.2% World average (last 45 years) 11.8%|
|Yellow fever||15%||only supportive care – no treatment Vaccination available|
|2019-nCoV||1/ between 2,01% and 2,8720% – 3,0617%|
2/ between 2,2697% and 2,7175%
|1/ estimates from global and Hubei, 2 to 4 February 2020|
2/ estimates from global and Hubei, 13 February 2020
|seasonal influenza epidemics||0.03% to 1,75%||ECDC Factsheet about seasonal influenza|
|Malaria (falciparum)||0.3% (Other regions) – 0.45% (Africa)||
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:
|Cholera||1.1 to 2.7 (Bangladesh & Zimbabwe outbreak)||Direct: person-to-person Indirect contact: water|
|2019-nCov||2.2 (Qun Li et al.)|
2.68 (Wu et al.)
|(estimates end January 2020)|
|SARS epidemic 2002-2003||2-4 (WHO 11/2003)||Respiratory droplets|
|Influenza H1N1 (1918)||2-4||Direct: airborne Indirect: touching infected surface and bringing hand to mouth or nose|
|EVD 2016||2.18 median (1.24-3.55)||Direct: bodily fluids Indirect: contaminated material|
|Plague (pneumonic – bacteria)||1.3||Airborne infectious droplets|
|MERS||0.7||ECDC (31 January 2020)|
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
Abbott S, Hellewell J, Munday J, Funk S, Funk S. The transmissibility of novel Coronavirus in the early stages of the 2019-20 outbreak in Wuhan: Exploring initial point source exposure sizes and durations using scenario analysis. Wellcome Open Res, 2020 Feb 3.
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.
Hale, Lonsdale, The Fog of War, 1896.
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.
Liu T, Hu J, Kang M, Lin L, Zhong H, Xiao J, et al. Transmission dynamics of 2019 novel coronavirus (2019-nCoV). bioRxiv. 2020 Jan 26;2020.01.25.919787.
Lodish H, Berk A, Zipursky SL, et al. Molecular Cell Biology. 4th edition. New York: W. H. Freeman; 2000. Section 6.3, Viruses: Structure, Function, and Uses.
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.
Nasir, Arshan et al. “Viral evolution: Primordial cellular origins and late adaptation to parasitism.” Mobile genetic elements vol. 2,5 (2012): 247-252. doi:10.4161/mge.22797.
Qun Li et al., “Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia“, New England Journal of Medicine, 29 January 2020.
Read JM, Bridgen JR, Cummings DA, Ho A, Jewell CP. Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictions. medRxiv, 2020; 2020.01.23.20018549.
Rothe et al., “Transmission of 2019-nCoV Infection from an Asymptomatic Contact in Germany“, NEJM, 30 January 2020.
Shen, S., Qu, X., Zhang, W. et al. “Infection against infection: parasite antagonism against parasites, viruses and bacteria“. Infectious Diseases of Poverty, volume 8, Article number: 49 (2019).
The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team. The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19) — China, 2020[J]. China CDC Weekly 2020. – 18 February 2020.
WHO, Consensus document on the epidemiology of severe acute
respiratory syndrome (SARS), November 2003.
WHO, Summary of probable SARS cases with onset of illness from 1 November 2002 to 31 July 2003, 21 April 2004.
WHO, MERS update, December 2019.
Wu, Joseph T 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.
Zhong et al., Clinical characteristics of 2019 novel coronavirus infection in China, doi: https://doi.org/10.1101/2020.02.06.20020974.