COVID-19: Are local closures as effective as provincial lockdowns?


Travelers could spread the virus from major cities, which were travel hotspots and COVID-19 cases

This article, written by Vadim Karatayev, University of Guelph; Chris Bauch, University of Waterloo, and Madhur Anand, University of Guelph, originally appeared in The Conversation and have been republished here with their permission.

During the COVID-19 pandemic, policymakers around the world have questioned whether to reopen counties and cities at the same time or allow less affected places to reopen first. Our research suggests that with sufficient testing and coordination, reopening schools and businesses in areas of Ontario without an active outbreak can be as effective as a long provincial lockdown in minimizing total infections while reducing closures. .

It may surprise many readers that we arrived at this project from a study of climate change negotiations and underwater giant kelp forests.

It is known that lush kelp stands can be quickly grazed on rocky heathlands by sea urchins – animals little more than spine-covered balls with a mouth. Yet we have found that the collective behavior of sea urchins is of the utmost importance: sometimes sea urchins stay close to their shelters and keep only small barren patches, while at other times sea urchins invade and transform rapidly moorland kelp forests over large stretches of the coast.

Inspired by this, we asked whether local activism or global negotiations is the fastest way to reduce greenhouse gas emissions around the world. The answer turned out to be between the two: move from regional climate coalitions to binding global agreements once several – but not yet all – regions have committed to reducing their emissions. We found the same principle applied when the spring outbreak of COVID-19 began to recede in Ontario and sparked debates about reopening.

Some argued that areas with lowercase numbers should be allowed to open earlier, while others argued that a patchwork of open and closed areas would only cause individuals to move from areas. closed to open areas in order to access services, thus spreading the virus in the areas. it had more under control.

Additionally, travelers could spread the virus from major cities, which were travel hot spots and cases of COVID-19. Therefore, we decided to approach this question with a mathematical model that is not unlike the models we use to study kelp forests and climate change, all concerned with populations distributed over the plots.

This kind of accidental insight, where researchers working on a problem can see applications of their methods or concepts in another seemingly unconnected field, happens all the time in the mathematical sciences. And it might not be so accidental, after all, because mathematical modeling can provide a unifying framework for discovering commonalities in seemingly different systems.

What we found

Our study in the Proceedings of the National Academy of Sciences used actual commuting models to account for daily trips between census divisions and modeled the county-to-county differences in the travel and transmission of COVID-19, the presence of symptoms and recovery time. We also used the daily number of cases for each public health unit to estimate how the rate of COVID-19 transmission is increasing in more densely populated areas. These data show that in Ontario’s four largest urban areas, COVID-19 spreads quickly, is difficult to eliminate, and is 250 percent more prevalent than in the province as a whole.

The prevalence of COVID-19 is concentrated in urban centers and is disproportionately lower in less densely populated areas. Author provided

But in many less populous counties, we’ve found that outbreaks are less intense and subside more quickly once schools and workplaces close. By closing as needed when local cases start to increase, municipalities in our model stay on top of the outbreak and cases imported by travelers – even when we have doubled travel rates from previous years.

Therefore, the local strategy also provides the flexibility to extend closures in areas where outbreaks are still active – primarily more populous counties with higher outbreak rates – without sustaining the rest of the province. locked up.

Act fast and act locally, coordinate globally

For this local approach to work, however, sufficient testing capacity and rapid turnaround times are required to detect local outbreaks on time. In addition, taking decisive action by shutting down schools and workplaces as soon as the detected cases per 100,000 exceed a critical threshold reduces the total number of days locked out. Both of these things were difficult to achieve in Canada at the start of the outbreak (March-May), and therefore a province-wide lockdown was the best approach at the time.

These results do not mean that individual counties can go it alone. In the United States, we have seen how poor federal coordination led to very late closings or premature reopenings in some states, which then became a source of COVID-19 cases nationwide.

Therefore, in Ontario, our model shows that county-by-county closures are most beneficial when testing and closing / reopening criteria are coordinated by the province. Otherwise, travelers from counties who open cases prematurely spread the cases to open areas, forcing them back into lockdown.

And the reclosure?

Cases of COVID-19 have been increasing steadily since summer 2020. The trend is likely to accelerate exponentially now that schools have reopened and temperatures are dropping, forcing people to spend more time indoors .

Our projection models for the current phase show that local county and city reclosure will continue to perform better than a province-wide shutdown, subject to our coordination and rapid testing conditions. As fall and winter dawn, greater testing capacity, swift action and a flexible county-by-county approach will continue to be the keys to reducing the economic and social impacts of the pandemic while minimizing COVID-19 infections.

Vadim Karatayev, Postdoctoral Fellow, School of Environmental Sciences, University of Guelph, University of Guelph; Chris Bauch, Professor of Applied Mathematics, University of Waterloo, and Madhur Anand, Professor and Director, Global Ecological Change & Sustainability Laboratory, University of Guelph

This article is republished from The Conversation under a Creative Commons license. Read the original article.


Please enter your comment!
Please enter your name here