Evaluating the impacts of tiered restrictions introduced in England, during October and December 2020 on COVID-19 cases: a synthetic control study
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Abstract
To analyse the impact on SARS-CoV-2 transmission of tier 3 restrictions introduced in October and December 2020 in England, compared with tier 2 restrictions. We further investigate whether these effects varied between small areas by deprivation.
Design
Synthetic control analysis.
Setting
We identified areas introducing tier 3 restrictions in October and December, constructed a synthetic control group of places under tier 2 restrictions and compared changes in weekly infections over a 4-week period. Using interaction analysis, we estimated whether this effect varied by deprivation and the prevalence of a new variant (B.1.1.7).
Interventions
In both October and December, no indoor between-household mixing was permitted in either tier 2 or 3. In October, no between-household mixing was permitted in private gardens and pubs and restaurants remained open only if they served a ‘substantial meal’ in tier 3, while in tier 2 meeting with up to six people in private gardens were allowed and all pubs and restaurants remained open. In December, in tier 3, pubs and restaurants were closed, while in tier 2, only those serving food remained open. The differences in restrictions between tier 2 and 3 on meeting outside remained the same as in October.
Main outcome measure
Weekly reported cases adjusted for changing case detection rates for neighbourhoods in England.
Results
Introducing tier 3 restrictions in October and December was associated with a 14% (95% CI 10% to 19%) and 20% (95% CI 13% to 29%) reduction in infections, respectively, compared with the rates expected with tier 2 restrictions only. The effects were similar across levels of deprivation and by the prevalence of the new variant.
Conclusions
Compared with tier 2 restrictions, additional restrictions in tier 3 areas in England had a moderate effect on transmission, which did not appear to increase socioeconomic inequalities in COVID-19 cases.
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SciScore for 10.1101/2021.03.09.21253165: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our analysis has some limitations. Firstly, we were only able to adjust for variation in the case detection rate using a relatively crude measure estimated at the LA level. This estimate assumes that the infection hospitalisation rate and the infection fatality rate does not vary between places that have similar prevalence of underlying …
SciScore for 10.1101/2021.03.09.21253165: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our analysis has some limitations. Firstly, we were only able to adjust for variation in the case detection rate using a relatively crude measure estimated at the LA level. This estimate assumes that the infection hospitalisation rate and the infection fatality rate does not vary between places that have similar prevalence of underlying health conditions and does not vary over the study time periods. Our analysis also assumes that the case detection rate is constant across MSOAs within each LA. We do however find larger effects when not applying our estimated case detection rate and we also adjusted for differences in the amount of testing carried out in each area. However differential changes in the case detection rate between intervention and control groups not accounted for in our estimates could bias our results. Secondly, although we were able to match areas to ensure a good balance of wider number of potential confounding factors prior to the intervention, there is still the potential that unmeasured variables could still contribute to biasing the results. Thirdly, we were only able to use data on small neighbourhood areas, rather than on individuals and therefore were unable to investigate how effects of control measures varied by individual or household characteristics – e.g. ethnicity, occupation or household size. As countries such as the UK continue the battle to control COVID-19 cases, with large regional differences in transmission, tiered restrictions as well as...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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