Modelling the evolution of COVID-19



According to the CONNECT study led by Marc Brisson, director of the Groupe de recherche en modélisation mathématique des maladies infectieuses at the CHU de Québec-Université Laval Research Centre, in collaboration with the Institut national de santé publique, Quebecers curbed their social contact by 65% during confinement and, in doing so, triggered a decline in the number of cases of COVID-19 as early as April.

 

Since 2018, the study has assessed social interactions between Canadians to better prevent and control infectious diseases and epidemics across the nation.

The downturn was precisely what the researcher's cutting-edge mathematical models had predicted: at least a 60% decrease in social interactions would slow the COVID-19 pandemic in Québec, but a reduction of less than 50% would not be sufficient to flatten the curve.

Augmented daily with data from the Institut national de santé publique, the models also predicted that if the population as a whole adhered to two-metre social distancing, wore masks and used physical barriers such as plexiglass in stores, the number of reported cases and hospitalizations would continue to dwindle as the province resumed its professional and business activities.

Marc Brisson is currently using the recent data collected by CONNECT to boost the models. Since 2018, the study has assessed social interactions between Canadians to better prevent and control infectious diseases and epidemics across the nation. Indeed, over 5 000 Canadians recorded the details of their social contact (e.g. location, ages of the people they met, duration of contact, etc.) before the COVID-19 pandemic. They repeated the exercise during confinement and still document the details today. The researcher and public health authorities are now working to more accurately predict the impact of prevention strategies to avoid or better manage a second wave.