A CSH overview on the COVID-19 pandemic
UPDATED ON JANUARY 6th 2021
The COVID-19 epidemic:
The year 2020 will be forever associated to the COVID-19 epidemic, and will for this reason become a landmark in the history of the human kind. Surprisingly enough, it is not so much the health consequences of the epidemic itself – however severe these may seem – that will make 2020 famous in the history. COVID-19 is estimated indeed to have killed a little less than 1.9 million people worldwide since its beginning a year ago. While this is certainly not the final health assessment of the epidemic, there is now some hope that the vaccination process that has started in the beginning of December and that is gaining momentum will reduce the spread of the disease and bring many regions of the world to a herd immunity, at least for a while. Indeed, the current graph seems to be suggesting that the world is entering in a peak of the daily number of COVID-19 death. Yet this peak, which is associated to the third wave of the epidemic, has seen a much larger number of daily death than any of the two preceding ones.
While the death toll of COVID-19 may thus seem to be impressive, it is quite modest when compared to those of past epidemics, be they relatively recent, or more ancient. The Hong Kong flu epidemic of 1968-1969 for instance is estimated to have killed from 1 to 4 million people worldwide, for a world population of 3 billion (as compared to the 7 billion people who live on Earth nowadays). The 1957-1958 H2N2 pandemic is also estimated to have killed around 1.1 million people worldwide, for a world population of 2.5 billion. And these figures are obviously very low when compared to the 20-50 millions of death caused by the Spanish Flu in 1918-1923 (over a population of 1.5 billions), or to the third of the European population that was apparently killed by the Black death of 1346-1353. The health consequences of COVID-19 are also modest when compared to those of other major causes of death – many of them avoidable – that the human kind is facing. According to the World Health Organization, in 2017, 1.3 million people worldwide died from road accidents, 15.2 million people died from cardiovascular diseases, and 9.6 million died from cancers.
The main reason why COVID-19 will become an episode of significant importance in the human history is the astonishing fear it has caused, and which is responsible for the adoption of policy measures of unprecedented stringency to prevent its spreading. While the actual impact of those measures on mitigating the health consequences of COVID-19 is far from clear, their dire economic and social consequences are amazing, and unprecedented in the last century. The following table, showing some recent estimations of the economic growth rate for 2020 in some of the largest economies, is amazingly clear from that perspective.
|Country name|| |
Estimated GDP growth rate 2020 (%)
(source: The Economist, December 5th 2020)
If we except China, all countries on the table are therefore expected to experience a severe reduction in their national income. India for example is expected to see its GDP drop by almost 10%, something that has never happened in the country since its independence. France, whose GDP is also expected to fall by more than 9% this year, will also witness the most severe recession of its history. Behind these (spectacularly) negative numbers lie the dire realities of 150 million people worldwide who have been plunged into the hell of extreme poverty (defined by an income of less than 1.9 US dollars per day in purchasing power parity) according to the most recent estimate of the World Bank. It is the first time in the last 20 years that the world is experiencing an increase in the rate of extreme poverty. India, which concentrates one-third of the world’s population of extremely poor people is obviously heavily concerned by this descent into hell.
The COVID-19 is hurting us. The policies that we have put into place to prevent its adverse health consequences are hurting us even more. This is what makes the COVID-19 epidemic so exceptional.
The next table provides numbers describing the current state (as of January 4th 2021) of the COVID epidemic in East Asian countries as well as in a few others that are “salient” in terms of their population size, severity of the COVID, or their geographical localization. Countries in this table are ranked decreasingly in terms of the lethality rate of the COVID-19. As can be seen, countries are extremely diverse on this matter. In the world’s most severely affected country so far, Belgium, more than 1700 people per million have died from COVID-19. Italy and Peru are two other countries that have paid a heavy death toll of above a thousand deaths per million people to COVID-19. The Peruvian death toll is all the more impressive as it is observed in a country that has implemented one of the toughest lockdown in the world, and whose inhabited by a relatively young population (half of the Peruvians are below 28). Latin American countries have all paid a surprisingly severe death toll to COVID-19, despite the fact of having a rather young population. At the other extreme, one finds East Asian countries such as Bhutan, Cambodia, Laos, Sri Lanka, Taiwan, Thailand and Vietnam who have seen less than 1 person out of a million dying from COVID-19. If one excepts Hong Kong, Myanmar, Japan and the countries of the Indian subcontinent, the overall lethality of COVID-19 in East Asia is everywhere below 10 deaths per million, which is extremely low (in average a hundred time lower than what is observed in Latin American countries). India is certainly one of the Asian countries who has paid the highest death toll to COVID-19 (a little more than 100 deaths per million) so far, even though this death toll is 10 times lower than what is find in the most affected European and Latin American countries.
|Country||Number of cases||Number of deaths||Population||Median age||Number of tests / million people||Number of deaths / million people|
A common explanation put forth to explain the diversity of the countries in terms of their COVID-19 death toll is their age structure. COVID tend to hit severely old people, and it was recently recalled by the French president Emmanuel Macron that 90% of the French people who die from COVID are above 65. Hence, one could expect countries with a young population to pay a lower dead toll to COVID than countries with an older age structure. Figure 2 below shows that this impression is corroborated by the existing data, even though the relation between the countries’ age structure – measured by median age – and the lethality of COVID is far from perfect. For one thing, Latin America countries have a very young population structure and yet they pay an impressive death toll to COVID-19. At the other extreme, countries like Taiwan and Japan have a rather aged population structure and do not suffer much from the direst consequences of COVID mortality.
Another frequently heard explanation for the amazingly different performances of the countries in avoiding COVID-19 mortality is their differing testing capacities. Yet, there does not seem to be a significant correlation between a country’s testing capacity – measured by the number of tests performed per million people – and its performance in avoiding COVID-19 test. As shown on Figure 3 below, countries who pay the largest dead toll to COVID tend to be those who test the most, even though the relationship is extremely weak. The reason for this lies in the simultaneous determination of COVID epidemic and the testing policy. On the one hand, a wide and generous testing policy may reduce the death toll from COVID by easing the tracking of people, and preventing therefore the spreading of the disease. This direction of causality would suggest a negative impact of testing capacity on COVID lethality. On the other hand, when COVID is very active and people get infected and develop symptoms, they want to be tested. This demand-induced testing goes in the direction of a positive relationship between the intensity of COVID and the number of tests done. The balance between the two effects is what is captured on Figure 3.
Are lockdown policies effective? a cross-comparison of France and India
A widely discussed issue pertaining to the management of COVID-19 is the impact of lockdown policies implemented in various countries to limit the spread of the virus. France for instance is currently finishing a second lockdown, that it has alleviated a bit on November 28th and, then on December 15th. Moreover, the French government does not rule out the possibility of imposing a third lockdown if the number of daily contamination does not go down more significantly. India is still in the process of eliminating the last restrictions of the very severe lockdown it has implemented on March 22 2020.
How successful have been these lockdowns in reducing COVID mortality? Answering a question like this is not easy, because we don’t know the counterfactual situation that would have prevailed in absence of those lockdowns. However, the historical juxtaposition of the timing at which the lockdown policies have been implemented and the daily number of COVID death provides some useful insights on those matters. Figure 4 below shows the daily number of COVID deaths observed in India since March 1st 2020, along with the various steps of the lockdown policies implemented by the Modi government, starting from the first stringent lockdown initiated on March 22nd to the current phase 5 and 6 of the “un-lockdown”.
This figure is suggestive of a failure of the Indian lockdown episodes to affect the lethality of the COVID. Any policy restricting the contact between individuals and the circulation of the virus at time t will see its effect on COVID lethality some 20 to 25 days later. Indeed, it takes between 5 to 7 days to be contaminated by the virus and it takes another 10 days after the beginning of the symptoms for the disease to evolve into the dangerous and potentially lethal phase. Hence, this graph suggests that the first phase of the lockdown has slowed down a bit the daily lethality of the COVID (one can see a little drop in the number of death roughly in the first two weeks of April). However, the progressive alleviation of the lockdown initiated on April 14th and after seem to have generated a continuous upsurge of the daily deaths that has peaked in mid-September without any clear connection to the severity of the lockdown (which has regularly decreased over the period).
Hence, except perhaps at the very beginning of the epidemic, lockdown policies in India seem to have had no visible effect on the dynamic of the daily number of daily deaths. To the contrary, it looks as if the reduction in the severity of the lockdown initiated on August 1st with the Unlock 3.0 has contributed to decrease the rate of growth of those daily deaths, thus leading to the mid-September peak. Again, one must be careful in over-interpreting this juxtaposition, because we do not know what would have been the dynamic of daily Covid deaths in India had the lockdown policies be different.
The French situation, described in the following figure, is more suggestive of a relative success of the first lockdown in reducing the number of daily COVID death. Indeed, 21st day or so after the implementation of the first lockdown on March 16th, the number of daily COVID death reached a peak (a bit before April 15th) and start to decrease. Following that decrease, the French government has announced an alleviation of the lockdown whose effect have all been eliminated on June 11th.
However, the second lockdown implemented on October 28th to fight the second wave of the COVID does not seem to have had much effect on the number of daily deaths. Indeed, the peak in the number of those deaths observed around November 15th has taken place much too early to be explainable by the lockdown. It seems therefore that the dynamics of the second wave of COVID in France has been largely independent from the implementation of the second lockdown.
Nicolas Gravel, Director of the CSH.
Regarding the CSH scientific production linked to the topic:
- Olivier Telle‘s contribution to the CNRS podcast series on COVID-19 (in French): http://www.csh-delhi.com/news/olivier-telle-part-of-the-cnrs-podcast-series-on-covid-19-in-french/
- Olivier Telle and Samuel Benkimoun (co-written with Eric Denis from CNRS), article on The Conversation on mapping the lockdown effects in India: https://theconversation.com/mapping-the-lockdown-effects-in-india-how-geographers-can-contribute-to-tackle-covid-19-diffusion-136323
- The same approach was applied to France: https://theconversation.com/evolution-des-mobilites-et-diffusion-du-covid-19-en-france-ce-que-les-donnees-facebook-devoilent-137846
- Some CSH researchers want to understand from a more qualitative perspective the impact of the Indian lockdown on the underprivileged segments of the Indian population, and more generally on the Indian economy. A brief description of the impact of the Indian lockdown on the migrant workers and Indian agriculture written by Bruno Dorin can be found here: https://www.cirad.fr/en/news/all-news-items/articles/2020/science/covid-19-and-food-security-india-and-its-jobs-crisis
- An interview of Bina Agarwal, an associate member of the CSH, suggesting alternative ways to fight the epidemic can be listened to here: https://www.facebook.com/brutindia/videos/836890173484449/
- Bina Agarwal in The Indian Express about labour during the lockdown period: https://indianexpress.com/article/explained/expert-explains-working-with-lockdown-create-green-worker-pools-not-green-zones-6376360/
- A crossed study of Kerala and Uttar Pradesh response to the COVID threat, co-authored by CSH member Anmol Seghal: https://www.counterview.net/2020/04/uttar-pradesh-and-kerala-preparedness.html
- An excellent description of the social impact of the Indian lockdown, co-authored by the associate member of the CSH Marine Al-Dahdah and former CSHer Mathieu Ferry, can be found here: https://booksandideas.net/The-Covid-19-Crisis-in-India.html
- Marine Al-Dahdah did also write on the tracing apps used to monitor Covid-19 progression: https://booksandideas.net/Tracing-Apps-to-Fight-Covid-19.html
- Here is a recent political analysis of the Indian national lockdown by CSH member Jean-Thomas Martelli, and Christophe Jaffrelot: https://indianexpress.com/article/opinion/columns/india-covid-19-coronavirus-lockdown-narendra-modi-6383721/
- A paper co-written by CSH member Rémi de Bercegol and colleagues from the IFP, about the marginalized populations of Indian cities during the lockdown: https://journals.openedition.org/echogeo/19357
- Bina Agarwal in a Mint podcast talking about the impact of the pandemic on inequalities in India: https://www.htsmartcast.com/single-episode/business/covid-19-widens-indias-inequality-divide–7722867/
- Another excellent and detailed analysis can be found here: https://cepr.org/sites/default/files/policy_insights/PolicyInsight102.pdf
- Nicolas Gravel also gave an interview about the application of economical science tools to help decision making in that pandemic era, in the French newspaper Le Monde (in French): https://www.lemonde.fr/idees/article/2020/09/04/on-peut-s-interroger-sur-l-adoption-de-politiques-de-confinement-qui-paralysent-les-economies_6050976_3232.html