Understanding the dynamics and counting the cost of the coronavirus

The spread of the coronavirus (Covid-19) is currently the number one concern among healthcare specialists, policymakers, journalists, economic and market analysts and ordinary citizens alike.  

The elucidation of the disease’s dynamics, death toll and impact on the Chinese and on the global economy are mobilising experts and analysts both in the economics and healthcare communities. However, these two communities are seldom used to collaborate. The outcome of this “silo approach” is mostly detrimental to economists as epidemiologists are primarily concerned with understanding the disease dynamics in order to fight it more efficiently. Economists for their part often lack a basic understanding on this subject. This leads most of them to integrate erroneous assumptions and parameters in their models and forecasts.

My aim in this post is to participate modestly to the ongoing debate by trying to close this gap. First, I will outline a few basic points and useful insights drawing from infectious disease models and what they tell us about the current 2019 coronavirus outbreak. Second, I will discuss the economic impact of this epidemic.

Infectious Disease Modelling 101 and the spread of the coronavirus

My entry point into this fascinating subject is an article written by Sharon Begley for the website statnews.com, which gives an overview of the subject and recaps the ongoing scientific effort that is being displayed to understand the dynamics of the Covid-19. I strongly encourage anybody interested in this subject to read Sharon’s very insightful article.

Contemporary infectious disease modelling owes much to the seminal work of Kermack & McKendrick published in 1927. Their original framing of the problem set the foundation for the so-called ‘compartmental models‘ which are nowadays widely used by epidemiologists across the world. These models split a population into individuals susceptible of being infected (S), exposed individuals (E) which have been infected but are not yet infectious, infected individuals which are infectious (I) and formerly infected individuals who have been removed (R) from the infection’s reach – either due to immunisation or to death – individuals. All comportemental models formalise in one way or another the relationships between these different groups, or compartments, within a given population.

It appears from these models that the key parameter to consider when studying the dynamics of an infectious disease is the basic reproductive ratio R0, which is the average number of secondary infections by an originally infected individual. An epidemic occurs when this ratio exceeds one, which means that every infected person transmits the disease on average to more than one person).

Building on Kermack-McKendrick, R0 is traditionally expressed as the product of three independent factors or of two transition parameters (“in” and “out” of the infectious state), according to the following formula:

R0 = rho * c * D = beta / gamma

In this formulas, rho stands for the probability of the disease being transmitted from one infected individual to a susceptible individual, c is the expected number of contacts between susceptible and infected individuals per unit of time (beta = rho * c is the transition probability from the susceptible to infected states), and D is the latency period of the infection (i.e. the time during which the infection can be transmitted) – the latter can also be expressed as the inverse of gamma (D = 1 / gamma), the probability of leaving the infectious state in every time period (either through recovery or death).

It stems from the above definition that when R0 > 1 an infectious disease reaches an epidemic stage, as the rate of infection (“beta”) is higher than the exit rate from the infection (“gamma”). The opposite holds through when R0 < 1 (or beta < gamma), in which case the disease loses its infectious force and fades out.

In the case of the new coronavirus, a study published in The Lancet medical review on January 30 indicates that during the first weeks of the epidemic the basic reproductive ratio for the new coronavirus  was between 2.47 and 2.86 – with a 95% confidence interval –  and that the doubling time of the epidemic was comprised between 5.8 and 7.1 days. This is consistent with other estimations which indicate a high infectious force of this new coronavirus. The doubling time of SARS for example was much higher, comprised between 4 and 12 days.

What about the fatality rate of this new coronavirus ? 

It has been stated early on that the fatality rate from the 2019 coronavirus (the number of people dying out of total infected cases) stood at 2% – which is much higher than for a seasonal flu (0,1% to 0,2%) but much lower than the fatality rate that was observed for the 2003 SARS outbreak which stood at 10%, and a magnitude lower than for the 2012 MERS-COV outbreak in Saudi Arabia which reached a record 34% (one person out of every three infected by that virus died). The initially reported 2% casualty rate was by all accounts an overestimation of the actual rate. Although the total number of casualties reached 2000. In fact, assuming that there are already 100.000 or more infected individuals by Covid-19 this would translate into a casualty rate of 0,2%, which is close to the casualty rate of a seasonal flu (0,1%) and much lower than that of the Spanish flu of 1917 (2,5%), not to mention SARS and MERS-COV.

The more an infectious disease is deadly, the less it gives its host a ‘window of opportunity” to infect other potential hosts, and vice versa. According to epidemiologists, parasites aim to create the condition for optimal virulence by adjusting their fatality rate to their transmission rate. For example, 19 millions people were infected by the seasonal flu in the United States in this winter season, which has resulted in 10.000 registered deaths. At the other end of the spectrum, the very deadly MERS-V outbreak in Saudi Arabia in 2012 had a reproductive ratio below one. Hence, it was a violent disease outbreak which faded very quickly. In this regard, the fatality rate of the Covid-19 indicates that its virulence strategy is somewhere between a seasonal flu and SARS, but it is much closer to the former than to the later. 

Have the Chinese authorities managed to contain the spread of the disease ? 

It follows from the framework described above that there are three ways to contain the spread of an infectious disease :

1. To reduce the probability of transmission of the virus through the use of masks and other devices
2. To reduce the number of potential contacts of exposed individuals through quarantine and confinement measures
3.  To reduce the latency period of the infection by administering preventive drugs to the susceptible individuals and curative drugs to the exposed/infected individuals

According to a modelling exercise of the epidemic by a group of researchers based at the University of Lancaster,

Researchers at the University of Toronto show that the response of the Chinese authorities have allowed them to significantly reduce the level of the basic reproduction ratio, from 2.5-2.3 down to 1.5, which translates into an cumulated number of around 100.000 actual cases as of the end of February (cf. the figure below). In comparison, the SARS outbreak in 2002-2003 resulted in only 8.000 cases, of which 774 were fatal. Without those containment measures, the number of infected cases from the new coronavirus might have reached over half a million people as of the end of February. The main challenge is now to reduce as quickly as possible the basic reproduction ratio toward its unitary threshold, in order to remove the epidemic nature of the disease.

However, there are no silver bullets. The effectiveness of the quarantine and confinement measures might sometimes be questioned. Sometimes might lead to an increase in the number of infections by increasing the number of contacts within the confined population, especially when there is already an important number of infected individuals. This is blatantly evident in the case of the Diamond Princess cruise ship, which claims the largest number of reported Covid-19 cases outside China. The decision taken by the Japanese authorities to quarantine and confine the cruise ship’s passengers’ inside their cabins did not prevent their infection and that in fact led to a recrudescence of the number of infected persons among the quarantined passengers. Hence, the most important thing to do to slow down the number of infections is to reduce the number of susceptible individuals (S), by ensuring that they are not in contact in a way or another with the virus and by shortening the latency period, D. This is precisely what the Chinese authorities did.

The economics of the coronavirus: disentangling the material and the psychological effects

After downplaying the incidence of the disease, the outbreak of the number of individuals infected by the coronavirus pushed the Chinese authorities to recognise its epidemic nature and the health emergency situation that was quickly developing in the Wuhan province before spreading to other Chinese provinces and cities and to other countries outside China.

The material cost of the disease containment policies

The direct economic costs are the consequence of the aforementioned measures taken by the authorities to contain the spread of the disease, especially the quarantine and confinement measures and the precautionary measures taken to decrease contact opportunities between potentially infected (i.e. exposed) and non infected individuals.

The closing of factories, offices and retail outlets all across China in the wake of the infections outbreak hit the second largest economy in the world, an economy that was already slowing down over the last few years – since 2014-2015 actually -, and one which had to respond reluctantly, starting from 2017-2018, to a nasty trade war and to a set of protectionist measures initiated by the Trump administration, targeting key sectors such as the IT sector (Huawei, ZTE) while pursuing a years-long consolidation in more traditional industrial sectors such as steel, cement and aluminium.

The impact on the economy might be estimated using real time economic data such as transportation numbers, carbon emission figures and electricity consumption. Accordingly Economists from Morgan Stanley estimates that the coronavirus outbreak could shave off as much as 1% of Chinese GDP in H1 2020 (cf. the chart below compiled by CNBC). The impact on the Q1 growth figures are obviously the most dramatic. The question is whether the epidemic will recede and fade out in Q2, with rising temperatures playing a mitigating effect on the virulence and on the infectious force of the virus much like it is the case for other viruses. For example, in 2003 the SARS outbreak which was more virulent than Covid-19 faded out after six months. Another scenario is that the coronavirus becomes endemic and that its virulence reasserts itself every winter season, although with milder effects much like the flu.

Despite the disruption to economic activity caused by the temporary containment measures, the IMF Managing Director, Christalina Georgieva, expects a V shaped recovery for the Chinese economy as soon as the epidemic stabilises and eventually, recedes. It might well be the case, especially given the Chinese government determination to do “whatever it takes” to overcome this crisis and whatever shortcomings it revealed. But there are also downside risks to this rosy scenario.

The ‘fear factor’ and the confidence undermining effect

The Shanghai stock exchange and other “Greater China” stock exchanges (Hong Kong, Taiwan, Singapore) have all taken a hit following the epidemic outbreak, with negative performances since the start of 2020. So far, outside Asia, the major financial markets have not been substantially impacted by the coronavirus.

The cancellation of major business, cultural and sports events in China and around the world, such as the Mobile World Congress in Barcelona will have a tangible impact on the cities organising those events, but the most important impact of these cancelations is their effect on confidence. The “fear factor” has been compounded by the global media coverage of the epidemic which at times lacked any rationality.

The global economy was already expected to witness a muted expansion in 2020 ,according to many forecasters, as a consequence of the trade war, geopolitical tensions in the Middle East, and uncertainty over the forthcoming policy mix in Europe and in the United States. In Europe, Germany is particularly exposed to a Chinese slowdown, as are the commodity exporting countries in Africa and the Middle East which may suffer from falling Chinese imports and from subsequent downward pressures on commodities prices.

What to expect next ? 

Looking forward, there might as well be a return to “Business as usual” in the coming months – much like in 2003, following the SARS epidemic outbreak -, with an upsurge in production and consumption in S2 2020 in China, that would be supported by a fiscal and monetary stimulus. Some measures in this direction have already been taken y the Chineses authorities to help local companies cope with the impact of the sanitary crisis on their production schedules and balance sheets.

This crisis will certainly prompt major global companies such as Apple, IBM, Toyota, BMW and the like to accelerate the restructuring of their global manufacturing and supply chains, by moving some of their most critical components out of China and by reducing their dependance on the Chinese market. This strenuous restructuring process already started in 2007-2008, following the rise of anti-China sentiment in the United States, and increasingly in the European Union, although in a more muted and technocratic manner (through the EU Commission’s response to China’s Silk road initiative and through the project of a new EU-border tax targeting carbon emitters). According to the President of the European chamber of commerce in China, many European companies are starting to acknowledge that they put too many eggs in China’s basket.

The 2008-2009 financial crisis was a moment of truth for the United States and for other western countries. It brought to an end the turbo-charged financially driven capitalism of the 1990s and the 2Ks. However, it did not result in a radical overhaul and in a resorption of the social inequalities that have undermined confidence in the traditional elites in the western democracies. It unleashed a wave of populism across both sides of the Atlantic. In a similar fashion, some commentators argue that the techno-authoritarian model that underpinned for decades the Chinese growth miracle might come to an end following the mishandling of the new coronavirus epidemic.

The slow initial reaction of the central government and the mismanagement of the epidemic at the local provincial (Hubei) and city (Wuhan) level during its early stage might have sowed the seeds of distrust between the people and the ruling elite, especially following the death of one major whistleblower who tried unsuccessfully to alert  the authorities early on on the severity of the crisis. However, it would be premature to draw any definitive conclusions from this sequence of unfolding events.  One FT editorialist did not hesitate to dub the situation Xi’s “Chernobyl moment”. This is grossly exaggerated. The sacking of the Hubei province and Wuhan city party secretaries shows that Beijing understood the people’s demand for accountability. The WHO has also repeatedly praised the Chinese government’s strong response to the crisis.

However, the containment of the epidemic is only one part of the difficult equation facing the country’s leadership in the coming months, as the economic forced slowdown that resulted from the adopted health emergency measures might be more damaging to its reputation than the epidemic itself, which has already shown some signs of stabilization.