Initial Assessment of the Impact of the Emergency State Lockdown Measures on the 1st Wave of the COVID-19 Epidemic in Portugal

  1. Vasco Ricoca Peixoto
  2. André Vieira
  3. Pedro Aguiar
  4. Carlos Carvalho
  5. Daniel Rhys Thomas
  6. Alexandre Abrantes

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Abstract

Introduction: Portugal took early action to control the COVID-19 epidemic, initiating lockdown measures on March 16th when it recorded only 62 cases of COVID-19 per million inhabitants and reported no deaths. The Portuguese public complied quickly, reducing their overall mobility by 80%. The aim of this study was to estimate the initial impact of the lockdown in Portugal in terms of the reduction of the burden on the healthcare system.Material and Methods: We forecasted epidemic curves for: Cases, hospital inpatients (overall and in intensive care), and deaths without lockdown, assuming that the impact of containment measures would start 14 days after initial lockdown was implemented. We used exponential smoothing models for deaths, intensive care and hospitalizations and an ARIMA model for number of cases. Models were selected considering fitness to the observed data up to the 31st March 2020. We then compared observed (with intervention) and forecasted curves (without intervention).Results: Between April 1st and April 15th, there were 146 fewer deaths (-25%), 5568 fewer cases (-23%) and, as of April 15th, there were 519 fewer intensive care inpatients (-69%) than forecasted without the lockdown. On April 15th, the number of intensive care inpatients could have reached 748, three times higher than the observed value (229) if the intervention had been delayed.Discussion: If the lockdown had not been implemented in mid-March, Portugal intensive care capacity (528 beds) would have likely been breached during the first half of April. The lockdown seems to have been effective in reducing transmission of SARS-CoV-2, serious COVID-19 disease, and associated mortality, thus decreasing demand on health services.Conclusion: An early lockdown allowed time for the National Health Service to mobilize resources and acquire personal protective equipment, increase testing, contact tracing and hospital and intensive care capacity and to promote broad prevention and control measures. When lifting more stringent measures, strong surveillance and communication strategies that mobilize individual prevention efforts are necessary.

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  1. Version published to 10.20344/amp.14129
  2. ScreenIT

    SciScore for 10.1101/2020.05.26.20098244: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We used SPSS expert modeler to consider different types of exponential smoothing and ARIMA models for specific time-series12, and find the best fitting models for the time series to March 31.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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:
    Despite being useful, there are some limitations in the quality of surveillance data we used in these models. Early in the epidemic there was likely to be an under-ascertainment of cases leading to our forecast being more conservative. On the other hand there may have been some delays in reporting, for example, resulting in a peak in reporting of cases on April 9 which is otherwise unexplained. Data on Covid-19 deaths, and occupied Hospital (overall) and ICU beds are of reasonable quality. In Portugal, COVID-19 deaths are reported by clinicians using an online national platform and these data are available in real time. Deaths in patients who were suspected cases of COVID-19 where a lab result was not available are tested post-mortem15 (suspect case definition stopped including epidemic link with a confirmed case on March 26). Prevalent ICU and overall hospitalized cases in each day are reported from each hospital to the Regional level and to DGS that collates and communicates the data and as such we assume a high level reporting quality. However, data on new cases are likely to be biased, reflecting testing strategies and tests availability. There was likely to be a high level of under ascertainment in the early phase of the epidemic. As the testing strategy changed in Portugal from March 26 and testing became more widespread (everyone with cough or fever tested). Our model made a number of assumptions based on data presented in the published literature, which varies 16,17,1...

    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.

    About SciScore

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  3. Version published to 10.1101/2020.05.26.20098244v1 on medRxiv