Impact of social distancing measures on the daily number of new COVID-19 cases in Côte d’Ivoire: a retrospective cohort study

  1. Teegwende V. Porgo
  2. Khadidja Malloum Boukar
  3. Ezechiel A. Djallo
  4. Richard Quansah Amissah
  5. Coralie Assy
  6. Adama Traore
  7. Gaston Sorgho

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Abstract

Introduction

Côte d’Ivoire is facing a second wave of the novel coronavirus disease 2019 (COVID-19). While social distancing measures (SDM) may be an option to address this wave, SDM may be devastating, especially if they have a minimal impact on the spread of COVID-19, given the other measures in place.

Methods

We conducted a cohort study involving cases that had occurred as at June 30, 2020. We used data from the Government’s situation reports. We established three study periods, which correspond to the implementation and easing of SDM, including a 10-day delay for test results: (1) the SDM (March 11 - May 24), (2) the no SDM (May 25 - June 21), and (3) the pseudo SDM (June 22 - July 10) periods. We compared the incidence rate during these periods using Poisson regression, with sex, age, and the average daily number of tests as covariates.

Results

As at July 10, there were 12,052 cases. The incidence rate was 100% higher during period 2 compared to period 1 (incidence rate ratio = 2.05, 95% confidence interval: 1.75-2.41) and 25% lower during period 3 compared to period 2 (0.75 [0.66-0.86]).

Conclusions

The easing and subsequent reinforcement of SDM had a significant impact on the spread of COVID-19 in Côte d’Ivoire. The other mitigation measures either did not compensate for the easing of the SDM during the no SDM period or were not fully effective throughout the study periods; they should be strengthened before the SDM are reimplemented.

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    SciScore for 10.1101/2021.04.18.21255693: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableWe imputed these data with the mode age; the mode age among men was the same as that among women (31-40 years).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We performed statistical analyses using the STATA software (StataCorp LLC, College Station, TX, version 15.1).
    STATA
    suggested: (Stata, RRID:SCR_012763)
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    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: 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.
    • 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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.04.18.21255693v1 on medRxiv