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Published in: BMC Public Health 1/2022

Open Access 01-12-2022 | Vaccination | Research

On the effectiveness of COVID-19 restrictions and lockdowns: Pan metron ariston

Author: Leonidas Spiliopoulos

Published in: BMC Public Health | Issue 1/2022

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Abstract

Background

Early evaluations of the effectiveness of non-pharmaceutical intervention (NPI) mandates were constrained by the lack of empirical data, thereby also limiting model sophistication (e.g., models did not take into account the endogeneity of key variables).

Methods

Observational analysis using a behavioral four-equation structural model that accounts for the endogeneity of many variables and correlated unobservable country characteristics. The dataset includes information from 132 countries from February 15, 2020, to April 14, 2021, with data on confirmed cases and deaths, mobility, vaccination and testing rates, and NPI stringency. The main outcomes of interest are the growth rates of confirmed cases and deaths.

Results

There were strongly decreasing returns to more stringent NPI mandates. No additional impact was found for NPI mandates beyond a Stringency Index range of 51–60 for cases and 41–50 for deaths. A nonrestrictive policy of extensive and open testing constituted 51% [27% to 76%] of the impact on pandemic dynamics of the optimal NPIs. Reductions in mobility were found to increase, not decrease, both case \(\left( -0.0417,\left[ -0.0578,-0.0256\right] ,p<0.001\right)\) and death growth rates \(\left( -0.0162,\left[ -0.03,-0.002\right] ,p=0.025\right)\). More stringent restrictions on gatherings and international movement were found to be effective. Governments conditioned policy choices on recent pandemic dynamics, and were found to be more hesitant in de-escalating NPIs than they were in imposing them.

Conclusion

At least 90% of the maximum effectiveness of NPI mandates is attainable with interventions associated with a Stringency Index in the range of 31–40, which impose minimal negative social externalities. This was significantly less than the average stringency level of implemented policies around the world during the same time period.
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Footnotes
1
Unfortunately, a more rigorous game-theoretic analysis would require significantly more data to effectively infer or observe expectations of agents and the multitude of ways to react to said information.
 
2
If anything this underestimates the possible range of nonsignificantly different SI ranges, as it ignores the uncertainty associated with whether the range 61–70 is truly the most effective range.
 
3
I infer that the restriction on gatherings of 100–1,000 people is not the main driver of mandatory behavioral change because the median level of restrictions on gatherings for the next less stringent range, 21–30, is zero, that is, no restrictions whatsoever. Yet the mean estimate of NPI impact for the 31–40 range is -12.945, compared to -10.173 for the 21–30 range. Some of this difference will also be due to other policies that are stricter on average in the former compared to the latter.
 
4
That is, comparing the baseline of no testing to the first level (\(\chi ^{2}\left( 1\right) =12.42,p=0.0013\)), the first to the second level (\(\chi ^{2}\left( 1\right) =38.55,p<0001\)), and the second to the third level (\(\chi ^{2}\left( 1\right) =7.83,p=0.0153\)).
 
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Metadata
Title
On the effectiveness of COVID-19 restrictions and lockdowns: Pan metron ariston
Author
Leonidas Spiliopoulos
Publication date
01-12-2022
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2022
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-022-14177-7

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