Do COVID-19 interventions, such as lockdowns, physical distancing and business closures, actually work? York University researchers conducted a model-based analysis that found Ontario government measures had a substantial and positive effect on mitigating virus transmission.
York University Distinguished Research Professor Jianhong Wu Faculty of Science. Photograph by Paola Scattolon
Faculty of Science Professor Jianhong Wu, corresponding author of the study, and his team found interventions to prevent the spread of COVID-19 reduced people’s social contact rate and altered who they were in contact with, which changed the contact mixing patterns. For example, more people were at home and that disrupted the contacts they otherwise would have had in their workplace and in the community.
Individual contacts decreased from about 12 a day to just under seven a day, while household contacts increased by 51 per cent, from before the lockdown in Ontario until it ended on May 16.
The researchers developed and utilized a novel methodology that looked at variables such as age and setting – workplace, household, school and community – to better understand transmission rates and contact mixing patterns, and the effectiveness of measures on the spread of COVID-19.
“These assessments are essential to avoid increases in transmission in vulnerable populations and to plan a smart relaxation of measures that will still protect these populations and inform expected outcomes. One of these may be a reintroduction of measures, but more targeted and informed by its induced shift of contacts, in the case of a resurgence,” says Wu, director of the Laboratory for Industrial and Applied Mathematics at York.
They found that timely and stringent non-pharmacological interventions are effective in curbing the spread of the outbreak if they are enforced until the transmission has been significantly reduced.
Wu and his team estimate there was a 46 per cent decrease in contact rate after Ontario implemented a series of interventions as contacts shifted to the household.
They also found that susceptibility to SARS-CoV-2 increases with age and those 17 years old and younger have relatively low susceptibility to infection, less than three per cent. Seniors, already more vulnerable, however, are the most susceptible with a more than 50 per cent chance of becoming infected upon contact with the virus.
The four key periods the researchers used provided an escalation of measures from international travel advisories until March 13, public school closures, a state of emergency declaration and physical distancing advisories, and the closure of non-essential workplaces from March 24 to May 16.
The team’s methodology can be adopted in many regions around the world and could yield insights of the transmission risk and the effectiveness of different age- and setting-specific measures in workplaces, schools, the community and households.
“Estimates of age and setting-specific social contact patterns, along with age-specific susceptibility, allows governments to explore different scenarios when considering a staged reopening of the economy,” says Micheletti Alessandra, guest editor of the special COVID-19 issue of the Journal of Mathematics in Industry and a professor at Università degli Studi di Milano Statale. “It provides retroactive evaluation and proactive assessment of the effectiveness of measures.”
The framework can also be used for rotating workforce strategies and to help identify optimal distribution strategies by age should a viable vaccine be available.
The paper, Quantifying the shift in social contact patterns in response to non-pharmaceutical interventions, is published in the Journal of Mathematics in Industry.