On the impact of early non-pharmaceutical interventions as containment strategies against the COVID-19 pandemic

  1. Andrés Hernández
  2. Esteban Correa-Agudelo
  3. Hana Kim
  4. Adam J. Branscum
  5. F. DeWolfe Miller
  6. Neil MacKinnon
  7. Diego F. Cuadros

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Abstract

Background

The novel coronavirus SARS-CoV-2 (COVID-19) emerged in December 2019 in Wuhan, China and has spread since then to around 210 countries and territories by April 2020. Consequently, countries have adopted physical distance measures in an attempt to mitigate the uncontrolled spread of the virus. A critical question for policymakers to inform evidence-based practice is if and how physical distance measures slowed the propagation of COVID-19 in the early phase of the pandemic.

Methods

This study aims to quantify the effects of physical distance mitigation measures on the propagation of the COVID-19 pandemic. Data from John Hopkins University on confirmed cases and testing data from the Our World in Data were used in an interrupted time series analysis to estimate the effects of physical distance measures on the growth rates of the pandemic in 12 countries of Asia, Africa, and Europe.

Findings

We found that physical distance measures produced a significant decrease in the growth rates of the COVID-19 pandemic in five countries (Austria, Belgium, Italy, Malaysia, and South Korea). The test-positivity rate was significant in understanding the slowing growth rate of COVID-19 cases caused by the mitigation measures, as it provides important context that is missing from analysis based only on confirmed case data.

Interpretation

Physical distance interventions effectively slowed the progression of the COVID-19 pandemic. The results of this study could inform infectious disease mitigation policies based on physical distance measures by quantifying the differential health outcomes of a pandemic with and without physical distance interventions.

RESEARCH IN CONTEXT

Evidence before this study

The SARS-CoV-2 is a new virus identified in December 2019 in the province of Wuhan, China and as never before, a remarkable number of studies and reports have been released since the start of the pandemic. Several studies have used confirmed COVID-19 cases to estimate the growth rate of the pandemic. However, many studies have discussed limitations of including only confirmed cases attributable to the lack of information about testing protocols and testing rates among different countries. Finally, some researchers proposed the analysis of reported deaths by COVID-19 as a potential solution. However, this metric results in biased estimates because deaths by COVID-19 are known to be underreported.

Added value of this study

We designed and implemented analytic methods based on our previous research applied to different infectious disease epidemics, to add evidence related to the impact of non-pharmaceutical containment strategies on the temporal progression of the COVID-19 pandemic. Specifically, this study adds quantitative evidence about the effects of physical distance measures on limiting the propagation of COVID-19 pandemics in different countries. Additionally, we included testing data in the analysis to assess intra- and inter-country variation in testing growth rates. We hypothesized that the test-positivity rate is an approximation to the incidence of the COVID-19 pandemics in countries with high testing rates. Additionally, we hypothesize that a significant decrease in the pandemic over time could be identified by a significant decrease in the confirmed cases along with a significant decrease in the test-positivity rate. Our results quantified the potential effects of physical distance interventions on the COVID-19 pandemic progression under different levels of testing and enforcement of mitigation policies.

Implications of all the available evidence

Our analysis could lead to better approaches for estimating the effects of physical distance measures on the time course of infectious diseases. In addition, our analysis highlights the potential bias of estimated COVID-19 growth rates based only on confirmed cases. The results from our study could inform strategies for mitigating the COVID-19 or other future pandemics, especially in countries in an earlier stage of a pandemic.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.05.20092304: (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
    Statistical analyses were conducted using R version 3.5.213 (R Project for Statistical Computing), statistical significance was set at P< 0.05 where P is the Bayesian one-sided tail-area posterior probability, and graphs of times series were created using the R package ggplot214
    R Project for Statistical
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)

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

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Despite our findings several limitations of our study are worth noting. Assumptions of our time series analysis include that the temporal trends are stable during the pre and post NPI periods11. In our case, this assumption is not completely accurate as the temporal trend was exponential only in the early phase of the pandemic (below 36% of total population infected16). This limits our analysis to short time periods after the implementation of NPI policies. Additionally, the accuracy of TPR as an approximation to COVID-19 incidence decreases if the relationship between TPR and incidence is nonlinear, which in turn would affect our interpretations regarding the impact of NPIs on COVID-19 incidence. Finally, we limited our analysis to countries with sufficient testing data to enable interpolation, and we did not consider other aspects of NPI implementations such as cultural values, level of enforcement, and frequency or magnitude of group events that could affect the propagation of the COVID-19 pandemic. Notwithstanding these limitations, our study estimated the positive effects of NPI measures such as physical distancing orders and lockdowns in slowing the speed of the spread of the COVID-19 pandemic3. However, the effectiveness of NPI measures depends on the level of enforcement and intensity of the implemented interventions, and relaxed low-level enforcement of NPI measures may have a modest or even close to no impact in the course of the COVID-19 pandemic15. The results gen...

    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 10.1101/2020.05.05.20092304v1 on medRxiv