Projections by specialists suggest that periodical physical distancing measures may become a necessity if the new coronavirus becomes a seasonal occurrence.
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A new study from the Harvard T. H. Chan School of Public Health in Boston, MA has used mathematical models to project SARS-CoV-2 transmission dynamics throughout the pandemic and beyond.
In the study paper, which appears in the journal
This being the case, the authors suggest that physical distancing may become an intermittent requirement until 2022.
“We found that one-time [physical] distancing measures are likely to be insufficient to maintain the incidence of SARS-CoV-2 within the limits of critical care capacity in the United States,” says lead study author Stephen Kissler, Ph.D.
To understand how transmission patterns of SARS-CoV-2 might evolve, the researchers looked to the dynamics of two seasonal coronaviruses: beta-coronaviruses OC43 and HKU1. These are two
According to the team’s simulation, infections with SARS-CoV-2 might also become a seasonal occurrence, as is the case with the other beta-coronaviruses that infect humans.
Because there are currently no vaccines or targeted treatments for infections with the new coronavirus, the researchers project that on-and-off physical distancing may be a necessary measure over the next couple of years. This is to prevent hospitals from becoming overwhelmed.
“What seems to be necessary in the absence of other sorts of treatments are intermittent [physical] distancing periods,” says Kissler.
The investigators emphasize the need to strike a balance between healthcare capacity and economic resources on a case-by-case basis.
On the one hand, they say that some transmission of the virus may create a level of herd immunity, which could reduce its impact.
“By permitting periods of transmission that reach higher prevalence than otherwise would be possible, they allow an accelerated acquisition of herd immunity,” notes study co-author Prof. Marc Lipsitch.
On the other hand, too-stringent physical distancing measures might mean that humans cannot establish herd immunity at all, which would make a resurgence of the virus particularly problematic.
According to the study paper, “longer and more stringent temporary [physical] distancing did not always correlate with greater reductions in epidemic peak size.”
For example, the authors write:
“In the case of a 20-week period of [physical] distancing […] the resurgence peak size was nearly the same as the peak size of the uncontrolled epidemic: [T]he [physical] distancing was so effective that virtually no population immunity was built.”
However, the researchers point out that they faced an important drawback while making their projections: How strong immunity might be for people who have already contracted the virus, and how long this immunity may last for, remains unknown.
Their estimations, based on their knowledge of other human coronaviruses, suggest that immunity to SARS-CoV-2 may last for up to 2 years.
They also hypothesize that people who contract a common beta-coronavirus, for instance, and build up immunity to that virus may also become more resistant to contracting SARS-CoV-2 thanks to a phenomenon called “cross immunity.”
Nevertheless, the investigators’ projection is that immunity to SARS-CoV-2 will not be long-lasting enough to cause the waves of infection to die out completely, as in the case of the SARS-CoV outbreak in 2002.
They hope that, in the future, tests that can determine whether or not a person has formed antibodies against SARS-CoV-2 will help inform researchers and public health strategies.
Commenting on the study paper, infectious disease epidemiologist Prof. Mark Woolhouse — from the University of Edinburgh in the United Kingdom — commends the new research.
“This is an excellent study that uses mathematical models to explore the dynamics of COVID-19 over a period of several years, in contrast to previously published studies that have focused on the coming weeks or months,” he says.
However, he stresses that the researchers based their projections on working hypotheses that future studies still need to verify.
“It is important to recognize that it is a model; it is consistent with current data but is nonetheless based on a series of assumptions — for example about acquired immunity — that are yet to be confirmed,” he adds.
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