Dialling physical distancing measures up and down may be the best way to prevent COVID-19 from spreading in the long term without crushing Ontario’s economy or overwhelming health-care systems, according to a new disease modelling study involving a University of Guelph epidemiologist.

The research team’s simulation shows that turning physical distancing measures off and on – so-called dynamic physical distancing – will reduce disease spread and keep intensive-care units (ICUs) in Ontario from being overtaxed.

This method will also enable us to shorten overall physical distancing time compared to imposing a fixed period of control measures so people can still be somewhat active in Ontario’s economy, said Prof. Amy Greer, a member of a COVID-19 modelling advisory group for the Public Health Agency of Canada.

This study has been featured in The Canadian Press, with articles appearing across Canada, including Yahoo News.

“Easing off control measures periodically risks disease resurgence,” said the population medicine professor and Canada Research Chair in Population Disease Modelling. “But allowing people and the economy to ‘come up for air’ over the next few months offers a more effective and palatable strategy for fighting COVID-19 while ensuring that ICUs can handle infected cases.”

Dynamic physical distancing – either practised alone or combined with testing and tracing of contacts among infected individuals – proved more effective than imposing a fixed period of physical distancing.

“The model shows that what we need to do is think about a cyclical pattern,” she said. “We need to think about triggers for releasing social distancing or starting again,”

The study was completed by a team involving Greer and led by University of Toronto researchers, supported by COVID-19 funding from the Canadian Institutes of Health Research.

The team submitted its paper to the Canadian Medical Association Journal in late March. The paper is available as a pre-print that has not yet been peer-reviewed. Under a “rapid review” process, the final paper will receive peer review before publication.

Using data from Wuhan, China – the epicentre of the pandemic — the researchers compared a base case of limited testing, quarantine and isolation with three control scenarios: increased testing and isolation of cases; increased social distancing; or a combination of both. In all cases, they compared physical distancing for a fixed period with the projected effect of tightening or relaxing physical distancing requirements.

headshot of Prof. Amy Greer
Prof. Amy Greer

They based their scenarios on keeping COVID-19 ICU admissions to about 200 cases across the province and reinstating social distancing at a certain threshold. Intensive-care units are considered the most limited resource in the current pandemic.

Under the base case, an estimated 56 per cent of Ontario’s population would be infected with the coronavirus. At its peak, this scenario would require 107,000 people to be admitted to hospital and 55,500 people in ICUs, roughly comparable to ICU admissions for COVID-19 infection in other countries.

The team’s mathematical modelling shows that dynamic physical distancing can flatten the curve of disease spread.

“We wanted to look at what kinds of social distancing approaches would be most helpful to keep the health-care capacity in the province from becoming overwhelmed,” said Greer.

“We’re worried about transmission, but the goal is to spread that transmission over a longer time period, so we buy time to build health-care capacity. The key right now is to buy time for development of a vaccine and secure additional personal protective equipment for health-care workers and ventilators for patients.”

The study results have been shared with public health officials across Ontario.

The team hopes to use more current data to refine the model, determine where the province is on the infection curve and learn more about the expected duration of both control measures and the pandemic itself, she said.

Authorities are tracking confirmed infections but don’t know how many people are carrying the virus and have suffered only mild infection.

“If they’re not being tested, we have no way to know how much transmission is occurring in the community that is mild,” she said. “We need to know where we are on the curve.”