Global Assessment of the Relationship between Government Response Measures and COVID-19 Deaths
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Abstract
Objective
To provide an early global assessment of the impact of government stringency measures on the rate of growth in deaths from COVID-19. We hypothesized that the overall stringency of a government’s interventions and the speed of implementation would affect the growth and level of deaths related to COVID-19 in that country.
Design
Observational study based on an original database of global governmental responses to the COVID-19 pandemic. Daily data was collected on a range of containment and closure policies for 170 countries from January 1, 2020 until May 27, 2020 by a team of researchers at Oxford University, UK. These data were combined into an aggregate stringency index (SI) score for each country on each day (range: 0-100). Regression was used to show correlations between the speed and strength of government stringency and deaths related to COVID-19 with a number of controls for time and country-specific demographic, health system, and economic characteristics.
Interventions
Nine non-pharmaceutical interventions such as school and work closures, restrictions on international and domestic travel, public gathering bans, public information campaigns, as well as testing and contact tracing policies.
Main outcomes measures
The primary outcome was deaths related to COVID-19, measured both in terms of maximum daily deaths and growth rate of daily deaths.
Results
For each day of delay to reach an SI 40, the average daily growth rate in deaths was 0.087 percentage points higher (0.056 to 0.118, P<0.001). In turn, each additional point on the SI was associated with a 0.080 percentage point lower average daily growth rate (−0.121 to −0.039, P<.001). These daily differences in growth rates lead to large cumulative differences in total deaths. For example, a week delay in enacting policy measures to SI 40 would lead to 1.7 times as many deaths overall.
Conclusions
A lower degree of government stringency and slower response times were associated with more deaths from COVID-19. These findings highlight the importance of non-pharmaceutical responses to COVID-19 as more robust testing, treatment, and vaccination measures are developed.
Article activity feed
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SciScore for 10.1101/2020.07.04.20145334: (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 study has several limitations. Like any policy intervention, the effect of the responses we measured is likely to be highly contingent on local political and social contexts. For instance, the state-by-state level response in the United States has been heterogeneous, and our data track responses only at the national level. Nor do we …
SciScore for 10.1101/2020.07.04.20145334: (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 study has several limitations. Like any policy intervention, the effect of the responses we measured is likely to be highly contingent on local political and social contexts. For instance, the state-by-state level response in the United States has been heterogeneous, and our data track responses only at the national level. Nor do we measure the extent to which government interventions are successfully implemented. In addition, the effects reported do not account for potential confounders that might have otherwise reduced deaths, such as seasonality and climate. While these factors have not yet been established for COVID-19, if they are, they will need to be accounted for to more reliably estimate the effect of government policies on growth in deaths. In spite of these limitations, our approach offers a global and comprehensive view of governmental response to COVID-19 to date with the best information available. By measuring a range of indicators, composite indices mitigate the possibility that any one indicator may be over- or mis-interpreted. By the same token, composite measures also make strong assumptions about what kinds of information are included. If the information left out is systematically correlated with the outcomes of interest, or systematically under- or overvalued compared to other indicators, such composite indices may introduce measurement bias. Our data are in line with findings of the effects of similar NPIs on previous pandemics. Prior researchers hav...
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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