Summary: Despite the push for the country to reopen, researchers warn social distancing measures should remain in effect until the summer to avoid a potential deadly resurgence of coronavirus. A new model shows that as more emphasis is placed on relaxing social distancing, a resurgence of COVID-19 infections becomes more likely and will be more difficult to control later in the year.
Source: University of Notre Dame
A new study by epidemiologists at the University of Notre Dame suggests social distancing measures at current levels in many states may need to be maintained until the summer to avoid a potentially deadly resurgence of the coronavirus.
Results were particularly concerning when the model was used to evaluate the consequences of relaxing control measures in May, which researchers say puts the nation at a critical juncture in its response to the pandemic.
“Our results indicate that control measures that are in place right now may need to be maintained at a fairly high level until the summer if we want to lower transmission,” said Alex Perkins, Eck Family Assistant Professor in the Department of Biological Sciences, an expert in infectious disease epidemiology and population biology and the lead of the study. “At that point, we may be able to dial back those protective measures somewhat, but we will not be able to relax them completely until we have a vaccine.”
Those protective measures, Perkins added, need to include increased testing, contact tracing, and case isolation, in addition to social distancing.
Studies have shown that social distancing measures, including stay at home orders, are the most effective strategy currently available to reduce transmission of the highly infectious virus. But those measures have been significantly disruptive to the economy, leaving state officials, business leaders and decision-makers wondering how long to keep such measures in effect, and at what pace to relax them.
The goal of the study was to determine how to strike a balance between two key objectives: minimizing deaths from the virus and relaxing social distancing measures over time. Perkins’ model uses a technique called optimal control theory, which identifies how control measures should be applied over time to achieve a certain objective. The technique is widely used in scientific and engineering research to understand how to control the behavior of a system over time. In this work, Perkins used it to understand how relaxing social distancing measures at different points in time would affect the progress of the pandemic in the United States until a vaccine is available.
“The major takeaway is what we do in the short term has a big impact on what happens in the long term,” Perkins said. “If we keep social distancing measures in place through the short term, and reduce transmission, we’ll have greater flexibility and more options for relaxing them later. If we get into a situation where things are twice as bad as they are now, it’ll require a full-scale effort of lockdowns and tighter social distancing measures to get transmission levels down and prevent a catastrophe.”
Guido Espana, also at Notre Dame was co-author on the study. Perkins is an affiliated member of the Eck Institute for Global Health.
Funding: The study was supported by the National Science Foundation through a Rapid Response Research (RAPID) grant.
About this coronavirus research article
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University of Notre Dame
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Jessica Sieff – University of Notre Dame
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Original Research: Closed access
“Optimal control of the COVID-19 pandemic with non-pharmaceutical interventions”. by Alex Perkins, Guido Espana.
medRxiv doi:10.1101/2020.04.22.20076018
Abstract
Optimal control of the COVID-19 pandemic with non-pharmaceutical interventions
The COVID-19 pandemic has forced societies across the world to resort to social distancing to slow the spread of the SARS-CoV-2 virus. Due to the economic impacts of social distancing, there is growing desire to relax these measures. To characterize a range of possible strategies for control and to understand their consequences, we performed an optimal control analysis of a mathematical model of SARS-CoV-2 transmission. Given that the pandemic is already underway and controls have already been initiated, we calibrated our model to data from the US and focused our analysis on optimal controls from May 2020 through December 2021. We found that a major factor that differentiates strategies that prioritize lives saved versus reduced time under control is how quickly control is relaxed once social distancing restrictions expire in May 2020. Strategies that maintain control at a high level until summer 2020 allow for tapering of control thereafter and minimal deaths, whereas strategies that relax control in the short term lead to fewer options for control later and a higher likelihood of exceeding hospital capacity. Our results also highlight that the potential scope for controlling COVID-19 until a vaccine is available depends on epidemiological parameters about which there is still considerable uncertainty, including the basic reproduction number and the effectiveness of social distancing. In light of those uncertainties, our results do not constitute a quantitative forecast and instead provide a qualitative portrayal of possible outcomes from alternative approaches to control.
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