The Covid-19 outbreak that has spread around the world is putting societies and governments around the world to the test. Currently, there is no drug or vaccine available to fight the emerging SARS-CoV-2 virus that causes the disease. Moreover, since no human has been in contact with this virus in the past, no one is immune. Even so, with the data currently available, it is difficult to estimate whether people who have been infected and have recovered are acquiring immunity, to what degree it will protect them, and for how long. Under these conditions, what strategy should be chosen to protect populations, control the spread of the virus, adjust to the capacities of health systems, and limit the impact on the activity of societies?
The approaches used to address the epidemic vary from country to country, and may even follow one another over time. In addition to raising awareness about masks and barrier gestures, which are the responsibility of individual initiatives but remain highly effective in reducing the likelihood of transmission during contact, governments must choose between two broad population-based approaches to reduce contact rates.
The first is to mitigate the epidemic while allowing the virus to spread in the population. The second strategy is to break the transmission completely by quarantining and confining cities or even entire countries. Let's look at these two options.
Based on the epidemiological parameters estimated with data from the first few weeks of the epidemic, in the absence of control measures for Covid-19 and in the absence of behavioural changes (which still seems unlikely), the models predicted that a large majority of the world's population would have been infected.
Despite the rather low case-fatality rates of Covid-19 (less than 1 % of the infected individuals, approximately 0.5 % in France according to the calculations of the Pasteur Institute), such a massive infection would lead to a saturation of the hospitals by a part of the sick people of Covid-19 requiring intensive care.
This would make it impossible to assist not only other Covid-19 patients, but also people with different pathologies who would have been admitted to the intensive care units. It should be pointed out that in the United States, nearly 4 million people a year are usually admitted to intensive care unitsand nearly 500,000 die there despite the care they receive (an average mortality rate of 8 to 19 %). Congestion in hospitals would therefore have catastrophic consequences, leading to a dramatic, but difficult to quantify, collateral mortality.
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The R0 as a cornerstone of decision making
In general, the objective of control measures put in place to control an infectious agent such as CoV-2-SARS is to reduce its circulation in the population. This is achieved by reducing the value of the "baseline reproductive rate", or R0. This defines the average number of secondary cases generated by a primary case in a population susceptible to the infection, i.e. that has never encountered the virus before. In other words, it is the average number of people an infected individual will infect.
This parameter is important to know if one wishes to anticipate the epidemic risk. Indeed, if the R0 is higher than 1, an epidemic will probably set in (the higher it is, the more the pathogen will spread in the population), whereas if it is lower than 1, the infections will extinguish themselves and the epidemic will not take hold.
The R0 is the product of three parameters: the contact rate (i.e. the number of contacts an individual will have with other people in a day, for example), the probability of transmission of the infectious agent during contact, and the length of time an infected individual is able to transmit the infectious agent (i.e. the duration of the infectious period).
Each of these parameters is a lever to bring the R0 below 1. Thus, social distancing, school closure and confinement reduce the rate of contact, barrier gestures and the wearing of a mask reduce the probability of transmission during contact, drug treatment reduces the duration of the infectious period, etc.
Decreasing the R0 to a value below 1 is the suppression strategy: an infected person infects on average less than one person, leading to a cessation of transmission and extinction of the virus. Reducing the R0 to a value close to 1 (but still higher) is the mitigation strategy: the virus continues to spread in the population at a slower rate, thus avoiding overloading health systems.
The mitigation strategy is to keep the spread of the virus in the population under control, trying to protect the most vulnerable people. The objective of this strategy is twofold. Firstly, to slow down the spread of the virus in order to reduce and delay the epidemic peak. The aim is to "flatten the curve", i.e. to limit as far as possible the sudden appearance of a large number of infected individuals in order to limit the high risk of saturation of health systems.
The second objective of this strategy is to ensure that a large number of individuals eventually become immune, thus preventing the virus from continuing to spread over the long term. With a R0 of 2.35In a population of approximately 60 %, nearly 60 % of the population would have to become immune before the virus would no longer be able to spread.
This mitigation strategy is the one chosen by the Dutch government and presented by the Prime Minister on March 16, 2020. The measures put in place in these mitigation strategies are varied. They include isolation of sick people (but not asymptomatic infected people), quarantine of known infected outbreaks, closure of schools and universities, social distancing for the most vulnerable (but not for others), etc.
The suppression strategy
The suppression strategy is to "hit harder", i.e. to strengthen mitigation measures to reduce the R0 to values below 1, thus preventing the spread of the virus.
The aim is to ensure that the epidemic curve is rapidly reversed, health systems are not saturated and the virus is eradicated. The main measures put in place are global social distancing and containment of the entire population (not just people with clinical signs). In this way, the daily contact rate is drastically reduced and reduced to a number that does not allow the virus to spread beyond the family home.
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This is the strategy that the Chinese government is implementing very quickly in the main cities of Hubei province. During the first weeks of the outbreak, in the city of Wuhan, the R0 was most likely above 2. When the city was placed under quarantine and social distancing was implemented, the average daily contact rate was decreased by a factor of 7 to 9The R0 is now well below 1 in Wuhan and Shanghai.
This strategy has also been implemented in a number of European countries (France, Italy, Spain, Germany, etc.), in more or less flexible versions, but much later than in China, i.e. after a much higher number of cases had been detected. At present, at least in the world, at least 42 countries or territories have implemented general population containment, bringing the total size of the world's contained population to 2.5 billion people.
Another measure that can lead to the suppression of virus transmission is the mass screening of infected individuals in risk areas and their immediate quarantine, such as establishment in South Korea.
Advantages and disadvantages
Deciding on a mitigation or suppression strategy for managing such a crisis is extremely difficult, each with its own major interests and drawbacks. While the mitigation strategy offers the hope of achieving herd immunity, thus preventing a second wave of contamination in the event of a return of the virus, it does not fully protect populations at risk of severe forms. There is therefore a significant risk that health systems will become overwhelmed and that the number of deaths caused by the epidemic will be extremely high.
The suppression strategy saves time to organize to develop therapeutic treatments (such as antivirals for example), implement large-scale serological screening to estimate the proportion of potentially immunized individuals in the population, or even advance the development of a preventive vaccine (although making a vaccine available would probably require at least 18 months of research and development).
However, although apparently successful in China or South Korea, this strategy has significant social and economic costs, which could impact the health and well-being of populations in the longer term. Moreover, if implemented too late, elimination may not be sufficient to prevent the saturation of intensive care units, as demonstrated in the case of Italy. Finally, unlike mitigation strategies, suppression strategies greatly limit population infection. As a result, they prevent immunity from becoming widely established. In the absence of vaccination of the population, there is therefore a risk that the virus will return to active circulation when the measures are lifted.
How to choose?
To help governments resolve this dilemma, groups of experts with different backgrounds are trying to provide them with reasoned advice on the strategies for combating it and their political, social and economic consequences. In France, the government is guided by two committees of experts, the scientific comity and Research Analysis and Expertise Committee.
The predictions of the models mathematics are very important and increasingly used because they are of major interest in this delicate context. They make it possible to identify and prioritize transmission routes, to anticipate the number of cases that will be detected in the coming weeks, and to compare the effectiveness of different control strategies.
But to be useful, these models must be parameterized with reliable epidemiological data, and be able to take into account changes in the behaviour of individuals. In a context of health crisis where decisions must be taken very quickly, these data are complicated to obtain.
Improving the models
Whether it is the suppression strategy that brings an entire country's activity to a halt but contains the epidemic, or the mitigation strategy that puts health systems at risk of collapse and hundreds of thousands of deaths but maintains activity, the economic consequences of these control strategies will likely be different but probably dramatic, in different time steps.
However, it is still too early to draw conclusions on the effects of either approach, especially as the countries that have implemented them often have different case definitions. Moreover, socio-economic prospective is limited by the fact that the epidemiological models used to guide political decisions do not take into account either the economic repercussions or the increase in social inequalities generated by containment, which could further destabilize an already heavily impacted economy.
This is one of the many lessons of this crisis: it is essential to promote collaborations between epidemiologists, economists and sociologists so that the next generation of mathematical models used in public health integrates these dimensions.
Timothée VergneEpidemiologist and lecturer in veterinary public health at the National Veterinary School of Toulouse, UMR ENVT-INRAE " Interactions Host-agents pathogènes ", Inrae. The author warmly thanks Gaël Beaunée (Oniris, UMR Oniris-INRAE BIOEPAR) and Benjamin Roche (IRD, UMR IRD-CNRS-UM MIVEGEC) for the discussions that shaped this article.