COVID-19 lockdown: if, when and how

  1. Lía Mayorga
  2. Clara García Samartino
  3. Gabriel Flores
  4. Sofía Masuelli
  5. María V. Sánchez
  6. Cristián G. Sánchez
  7. Luis S. Mayorga

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Abstract

Background

With the lack of an effective SARS-CoV-2 vaccine, mathematical modeling has stepped up in the COVID-19 management to guide non-pharmaceutical intervention (NPI) policies. Complete lockdown has been characterized as the most powerful strategy for the epidemic; anyhow, it is associated with undeniable negative consequences. Not aware that global panic could make countries adopt premature and lengthy lockdowns, previous studies only warned about the inefficacy of late quarantine sets. Therefore, we proposed ourselves to find the optimal timing and lasting for COVID-19 suppressive measures.

Methods

We used our previously elaborated compartmental SEIR (Susceptible-Exposed-Infected-Recovered) model to scan different timings for lockdown set and various lockdown lengths under different reproduction number (R 0 ) scenarios. We explored healthcare parameters focusing on ICU occupation and deaths since they condition the sanitary system and reflect the severity of the epidemic.

Results

The timing for the lockdown trigger varies according to the original R 0 and has great impact on ICU usage and fatalities. The less the R 0 the later the lockdown should be for it to be effective. The lockdown length is also something to consider. Too short lockdowns (∼15 days) have minimal effect on healthcare parameters, but too long quarantines (>45 days) do not benefit healthcare parameters proportionally when compared to more reasonable 30 to 45-day lockdowns. We explored the outcome of the combination of a 45-day lockdown followed by strict mitigation measures sustained in time, and interestingly, it outperformed the lengthy quarantine. Additionally, we show that if strict mitigation actions were to be installed from the very beginning of the epidemic, lockdown would not benefit substantially regarding healthcare parameters.

Conclusion

Lockdown set timing and lasting are non-trivial variables to COVID-19 management.

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  1. Version published to 10.1101/2020.06.20.20136325v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.06.20.20136325: (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
    To facilitate the use of the model, the simulation was programmed in the free software COPASI (copasi.org), and the corresponding file is provided as supplementary material.
    COPASI
    suggested: (COPASI, RRID:SCR_014260)

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

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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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  3. Version published to 10.1101/2020.06.20.20136325v1 on medRxiv