Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave
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- Evaluated articles (ScreenIT)
- Evaluated articles (Rapid Reviews Infectious Diseases)
Abstract
The novel coronavirus (SARS-CoV-2) has rapidly developed into a global epidemic. To control its spread, countries have implemented non-pharmaceutical interventions (NPIs), such as school closures, bans of small gatherings, or even stay-at-home orders. Here we study the effectiveness of seven NPIs in reducing the number of new infections, which was inferred from the reported cases of COVID-19 using a semi-mechanistic Bayesian hierarchical model. Based on data from the first epidemic wave of n = 20 countries (i.e., the United States, Canada, Australia, the EU-15 countries, Norway, and Switzerland), we estimate the relative reduction in the number of new infections attributed to each NPI. Among the NPIs considered, bans of large gatherings were most effective, followed by venue and school closures, whereas stay-at-home orders and work-from-home orders were least effective. With this retrospective cross-country analysis, we provide estimates regarding the effectiveness of different NPIs during the first epidemic wave.
Article activity feed
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Nick Ruktanonchai
Review 1: "Estimating the Effects of Non-Pharmaceutical Interventions on the Number of New Infections with COVID-19 During the First Epidemic Wave"
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Strength of evidence
Reviewers: N Ruktanonchai (Virginia Tech) | 📗📗📗📗◻️
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SciScore for 10.1101/2020.04.16.20062141: (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: Thank you for sharing your code.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our analysis is subject to limitations. First, our analysis is limited by the type of data utilized and by the need to make modeling assumptions. Using the number of documented cases implies that documentation practices may have an influence on the results. In particular, definitions and documentation practices differed between countries and over time. However, since the rate of new cases was investigated, many deviations from an optimal …
SciScore for 10.1101/2020.04.16.20062141: (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: Thank you for sharing your code.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our analysis is subject to limitations. First, our analysis is limited by the type of data utilized and by the need to make modeling assumptions. Using the number of documented cases implies that documentation practices may have an influence on the results. In particular, definitions and documentation practices differed between countries and over time. However, since the rate of new cases was investigated, many deviations from an optimal documentation practice will affect both the number of new cases and the number of existing cases in a similar manner and may thus cancel out. Short-term fluctuations were considered by including day-of-the-week effects and allowing for overdispersion. Moreover, it was taken into account that countries had to develop their documentation practices by starting with at least 100 cases for each country. However, there may still remain an undue influence of country-specific changes in documentation practices over time. Second, a fundamental issue with our modeling approach is the implicit assumption that any deviation from a constant rate of new cases is explained by the NPIs. It is possible that additional measures or an increasing general awareness encouraged social distancing and hence lead to less infections. If this is the case, such effects will erroneously be assigned to the NPIs and possibly overstate their overall impact. Third, we could not follow the more correct approach to relate the number of new cases to the number of non-recovered c...
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.
- No funding statement was detected.
- No protocol registration statement was detected.
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SciScore for 10.1101/2021.01.15.21249884: (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: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:4.4 Limitations: Our analysis is subject to limitations. First, our modeling assumptions do not allow for (random) variation in the effect of NPIs across countries and assume a fixed effect. Brauner et al.11 demonstrated that, in principle, it is feasible to allow for country-specific variation in the effects. However, the specific parametrization chosen in our model (i.e., to take into account regional variation in the implementation …
SciScore for 10.1101/2021.01.15.21249884: (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: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:4.4 Limitations: Our analysis is subject to limitations. First, our modeling assumptions do not allow for (random) variation in the effect of NPIs across countries and assume a fixed effect. Brauner et al.11 demonstrated that, in principle, it is feasible to allow for country-specific variation in the effects. However, the specific parametrization chosen in our model (i.e., to take into account regional variation in the implementation of NPIs via the population share) made it challenging to incorporate random variation of the NPI effect θm across countries. Brauner et al observed in the sensitivity analysis of their study that assuming a fixed effect does not alter the main conclusions that they discussed regarding the effectiveness of NPIs. Second, any approach of explaining changes in the observed number of cases solely by specific NPIs makes the implicit assumption that these changes were not the result of some other factors. For instance, it is possible that additional measures or an increasing general awareness encouraged social distancing and hence lead to less infections. If this is the case, such effects will erroneously be assigned to the NPIs and possibly overstate their overall impact. Third, it is challenging to distinguish between the effects of single NPIs due to their concurring introduction in many countries (Supplement Tbl. 4). This is reflected by wide credible intervals and a negative association between effects (Supplement Fig. 3.2), suggesting that the ef...
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.
- No funding statement was detected.
- No protocol registration statement was detected.
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