Evaluating the impact of non-pharmaceutical interventions for SARS-CoV-2 on a global scale

  1. Rachel Esra
  2. Lise Jamieson
  3. Matthew P. Fox
  4. Daniel Letswalo
  5. Nkosinathi Ngcobo
  6. Sithabile Mngadi
  7. Janne Estill
  8. Gesine Meyer-Rath
  9. Olivia Keiser

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Abstract

In the absence of a viable pharmaceutical intervention for SARS-CoV-2, governments have implemented a range of non-pharmaceutical interventions (NPIs) to curb the spread of infection of the virus and the disease caused by the virus, now known as COVID-19. Given the associated social and economic costs, it is critical to enumerate the individual impacts of NPIs to aid in decision-making moving forward. We used globally reported SARS-CoV-2 cases to fit a Bayesian model framework to estimate transmission associated with NPIs in 26 countries and 34 US states. Using a mixed effects model with country level random effects, we compared the relative impact of other NPIs to national-level household confinement measures and evaluated the impact of NPIs on the global trajectory of the COVID-19 pandemic over time. We observed heterogeneous impacts of the easing of restrictions and estimated an overall reduction in infection of 23% (95% CI: 18-27%) associated with household confinement, 10% (95% CI: 1-18%) with limits on gatherings, 12% (95% CI: 5-19%) with school closures and 17% (95% CI: 6-28%) with mask policies. We estimated a 12% (95% CI: 9-15%) reduction in transmission associated with NPIs overall. The implementation of NPIs have substantially reduced acceleration of COVID-19. At this early time point, we cannot determine the impact of the easing of restrictions and there is a need for continual assessment of context specific effectiveness of NPIs as more data become available.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.30.20164939: (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

    Software and Algorithms
    SentencesResources
    Using the EpiEstim R package developed by Cori et al.21, Rt was estimated from 1000 samples at each time point using parameter specifications as described 17.
    EpiEstim
    suggested: (EpiEstim, RRID:SCR_018538)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our analysis had a number of limitations. Firstly, our metric of comparison, the time varying Rt based on reported cases, is sensitive to country level differences in testing coverage and strategies. In single country studies, it has been difficult to accurately estimate true infection rates and Rt due to the large number of asymptomatic infections that are assumed to go unreported24. Daily-confirmed cases do not give an accurate depiction of the total infected population at a given point in time. Country and region-specific delays in testing, in addition to differential delays between the reporting of positive and negative cases, result in a lag between daily reported cases and the actual burden of infection. A combination of rapidly evolving testing recommendations25,26, variations in laboratory processing capacities and, reagent shortages have resulted in the implementation of a number of different testing strategies across countries and over time. It is uncertain whether mass testing, shown to successful in the case of South Korea27, is feasible in other contexts, and modelling studies indicate that in the absence of contact tracing, widespread testing will not be sufficient in containing infection rates27,28. Secondly, this study was limited by the epidemiological complexity of ascertaining the impacts of individual COVID-19 NPIs implemented thus far. NPIs have been implemented with overlapping timeframes, at varying levels of severity and have been adhered to with diffe...

    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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  2. Version published to 10.1101/2020.07.30.20164939 on medRxiv