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Timely COVID Restrictions Can Slow A Surge, Data Show : Shots ...

the University of Pittsburgh
Carnegie Mellon University
the Department of Statistics and Data Science
RTI International
the Johns Hopkins Center for Health Security

Selena Simmons-Duffin
Mike Stewart
Seema Lakdawala
Rebecca Nugent
Melissa McPheeters
Crystal Watson


the East coast

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South Dakota
South Dakota's
the Upper Midwest
West Virginia
New Hampshire."I

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The New York Times
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But for those looking to the scientific evidence for guidance, here are some things a team of researchers at the University of Pittsburgh and Carnegie Mellon University have learned since the pandemic began that can help.The overall message from their analysis of state-by-state U.S. data is this: Even moderate restrictions on the size of gatherings, and some level of mask requirements can help help slow a surge of COVID-19 cases, if implemented at the right time.The scientists have kept a detailed database of statewide restrictions from March 2020 to March 2021, documenting when they went into effect, when they were lifted and the impact they had on case and death numbers in each state. It just might mean bringing back some level of masking requirements and gathering restrictions to help keep transmission under control.As communities and policymakers consider how to manage the threat of this delta surge, here are some lessons to keep in mind that Lakdawala's team and their collaborators at Carnegie Mellon University have learned from the first 18 months of pandemic restrictions.Throughout the pandemic, states — and even counties and cities within those states — have often done their own thing. Especially in the beginning, it was a real grab bag, says Lakdawala."A lot of states were putting [restrictions] on and then taking them off and then putting them on and taking them off — it was really haphazard," she says.To understand whether — and how — each type of restriction was making an impact on case trajectories, Lakdawala's team divided them into categories — stay-at-home orders, nonessential business restrictions, indoor gathering limitations, restaurant or bar restrictions, and mask mandates — and assessed how stringent each of the measures were.Then, with the help of Rebecca Nugent, the head of the Department of Statistics and Data Science at Carnegie Mellon University, they created graphs of each state's cases and deaths, showing the dates when restrictions were put into place or lifted.The first clear takeaway from the analysis of all this data from all these states, Nugent says, "is that these types of restrictions work — that they have an impact, that they are contributing to the control of the spread, and that we should be holding them on probably a little bit longer than we think."The timing of interventions is really important, Lakdawala says. It pays off to get a jump on restrictions before cases have really started to accelerate and to wait at least four weeks before lifting them.In analyzing states' total numbers of COVID-19 cases over time at various levels of restrictions, the researchers found there seemed to be a sweet spot: Places that had several kinds of moderate restrictions in combinations did really well in damping down viral spread.Perhaps surprisingly, "states that tended to have [more stringent] interventions weren't necessarily doing drastically better than those with moderate interventions," Lakdawala explains.What seemed to work just right — what they called the "Goldilocks" combination — was "some level of masking, some level of restaurant or bar restrictions and some level of gathering-size bans," she says.

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