Modelling the impact of isolation measures is what authorities turn to when making decisions concerning COVID-19. UCLouvain researcher Emmanuel Hanert has adapted a mathematical model developed by Chinese researchers in order to predict the evolution of the health situation in Belgium according to several scenarios.
Faced with the COVID-19 pandemic, countries are adopting different and variable strategies: collective immunity, social distancing, partial or total confinement … Like UK Prime Minister Boris Johnson, leaders adapt these strategies based on predictions of the health and economic impact of the measures in question. Predictions are possible thanks to mathematical models configured according to the data (demographic, hospital, etc.) specific to each country.
Emmanuel Hanert, professor and researcher at the UCLouvain Earth and Life Institute, used a mathematical model, developed by Chinese researchers, to predict the effect of containment measures on the course of the epidemic in Belgium: Do the measures limit the epidemic? How soon does the epidemic disappear? And with what mortality rate? ‘It’s important to note that the models allow us to predict an order of magnitude and a trend,’ Prof. Hanert says, ‘but don’t give exact figures. There’s a lot of uncertainty, it’s not a crystal ball.’
Three social distancing scenarios
He analysed the possible repercussions of different actions over 18 months beginning 7 March, including the following scenarios :
No social distancing/confinement measures.
Mild containment that doesn’t prevent a rise in new cases, as applied in the Netherlands.
Strict containment aimed directly at decreasing the number of new cases, as applied in Belgium.
In the first case, with no measures at all, the mathematical model predicts a peak in the epidemic after about a month. After 96 days, almost 100% of the population has been infected and emerged immune, but COVID-19 inflicts a very heavy toll: 80,000 deaths. The principle of this approach is to let the virus circulate widely so that the surviving population is quickly immunised. But at great cost. And this estimate of deaths is based on the current death rate, which would certainly be higher in this scenario given the saturation of our hospitals (with 3% of the Belgian population in hospital) after only a few days.
Mild containment, which involves isolating the most vulnerable and reducing contact, leads to a broader epidemic curve over time, resulting in a decrease in the number of hospitalisations. It’s a method of collective immunity that allows a significant part of the population to be infected. ‘By properly measuring the degree of isolation,’ Prof. Hanert explains, ‘we could achieve just what it takes to have collective immunity while minimising deaths. But hospitals would be saturated after 50 days, tens of thousands of deaths would occur, and the epidemic would end only after several months or even a year. So it's a pretty risky strategy.’
With strict containment, such as currently imposed in Belgium, the number of people exposed to the disease decreases from the start. The number of hospitalisations is very small and barely beyond the capacity of intensive care. The number of deaths remains below 1,000 but a large majority of the population remains susceptible to the disease, that is, they don’t develop immunity against it. ‘Suddenly, the disease disappears after a few months. But the catch is that after this delay, if we remove the containment measures, it’s enough for this or that infectious person to circulate in the general population – which is very likely given the different measures in neighbouring countries – for a second wave to occur in epidemic proportion and generating figures comparable to what we would have had in the first wave without containment measures, because the vast majority of the population isn’t immunised.’
So: the more we decrease contacts between people, the more the peak of the epidemic is spread over time and the fewer the victims. But with fewer people immunised against the disease, the risk of a second wave just as devastating as the first is very real.
To escape a second wave, Prof. Hanert modelled a scenario with successive periods of confinement. ‘You could imagine confining people for as long as hospitalisations take above a certain percentage of the capacity of the hospital system and easing confinement when those hospitalisations fall below that percentage. If we do that, the disease spreads more gradually while allowing hospitals to care for those with more serious symptoms.’ This is a scenario that’s difficult to control since it implies imposing confinement in overnight fashion several times in the coming months.
As long as there’s no vaccine, governments will be faced with this dilemma: isolating to reduce mortality versus achieving immunisation for a large fraction of the population in order to escape a second wave. Current measures, in addition to avoiding the breakdown of the hospital system, save time. ‘This last point is very important because progress is being made very rapidly for both potential treatments and diagnostic methods, and, in the longer term, a vaccine’, Prof. Hanert concludes. ‘All this will allow us to deal with a possible second wave by being much better prepared!’