Negative-Binomial and quasi-poisson regressions between COVID-19, mobility and environment in São Paulo, Brazil

  1. Sergio Ibarra-Espinosa
  2. Edmilson Dias de Freitas
  3. Karl Ropkins
  4. Francesca Dominici
  5. Amanda Rehbein

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Abstract

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  1. Version published to 10.1016/j.envres.2021.112369
  2. Version published to 10.1101/2021.02.08.21250113v3 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.02.08.21250113: (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
    The Google data is based on the use of smart devices such as cellphones, vehicle trackers, and other GPS enabled systems2.
    Google
    suggested: (Google, RRID:SCR_017097)

    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:
    However, we present findings and caveats, to provide early evidence on the transmission of COVID-19, and as part of efforts to highlight the potential value of the recently developed mobility indices. We found statistical associations between RMI and COVID-19 cases and a lower RMI (i.e., the increase of residents staying-at-home) increase COVID-19 cases. Likewise, increased RMI or less outdoor activities decreases COVID-19 cases. The median RMI after quarantine started was 45.28%, which represents most of the period of study. Under this RMI, we would expect 1,212 cases (95% CI: 1,189 to 1,235) and 44 deaths (95% CI: 40 to 47). São Paulo’s COVID-19 median values are 1,214 and 46 for cases and deaths, which means that our predictions align with our observations and previous literature regarding COVID-19 cases (Martins et al. 2020). We analyzed RMI values to provide policymakers with several options to mitigate the number of COVID-19 cases and deaths and support public health system. Then, if the mobility is reduced by increasing the RMI SIMI-SP index from 45.28% to 50.00%, we would expect 774 (95% CI: 751 to 797) cases and 23 (95% CI: 19 to 26) deaths, representing a reduction 438 cases and 21 deaths by only increasing the RMI 5%. Therefore, a policymaker can use this information and define RMI targets based on the capacity of their health system. We evaluated the effect of moving average air pollution on COVID-19 cases and deaths and we found strong associations. The average o...

    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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  4. Version published to 10.1101/2021.02.08.21250113v2 on medRxiv
  5. Version published to 10.1101/2021.02.08.21250113v1 on medRxiv