Low uptake of COVID-19 prevention behaviours and high socioeconomic impact of lockdown measures in South Asia: Evidence from a large-scale multi-country surveillance programme

  1. Dian Kusuma
  2. Rajendra Pradeepa
  3. Khadija I. Khawaja
  4. Mehedi Hasan
  5. Samreen Siddiqui
  6. Sara Mahmood
  7. Syed Mohsin Ali Shah
  8. Chamini K. De Silva
  9. Laksara de Silva
  10. Manoja Gamage
  11. Menka Loomba
  12. Vindya P. Rajakaruna
  13. Abu AM Hanif
  14. Rajan Babu Kamalesh
  15. Balachandran Kumarendran
  16. Marie Loh
  17. Archa Misra
  18. Asma Tassawar
  19. Akansha Tyagi
  20. Swati Waghdhare
  21. Saira Burney
  22. Sajjad Ahmad
  23. Viswanathan Mohan
  24. Malabika Sarker
  25. Ian Y. Goon
  26. Anuradhani Kasturiratne
  27. Jaspal S. Kooner
  28. Prasad Katulanda
  29. Sujeet Jha
  30. Ranjit Mohan Anjana
  31. Malay K. Mridha
  32. Franco Sassi
  33. John C. Chambers

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Abstract

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  1. Version published to 10.1016/j.ssmph.2021.100751
  2. ScreenIT

    SciScore for 10.1101/2020.11.12.20229898: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: The study was approved by IRBs in each country, and consent was obtained from all participants for each round of data collection.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableThe surveillance sites include 52,813 South Asian men and women aged 18 years and above with comprehensive information on baseline health collected immediately prior to the COVID-19 pandemic (November 2018 to March 2020).

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We conducted all analyses in STATA 15.
    STATA
    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: We detected the following sentences addressing limitations in the study:
    Strengths and limitations: We have assessed the impact of COVID-19 on behaviours, health, and wellbeing in a large representative sample of South Asians from 93 sites across four countries. This brings precision and generalisability to our findings. We benefited from the existence of comprehensive data from participants collected just before the onset of the pandemic, enabling us to accurately assess people’s changing situation. We used internationally validated questionnaires to ensure comparability with other studies. Although we recognise that the use of telephone surveys may introduce bias in recruitment, the characteristics of responders and non-responders were similar. Telephone surveys may also lead to response bias, however reliable baseline data collected pre-pandemic provided opportunities for validation in several instances. Our study was carried out at the height of the implementation of control measures, and restrictions have been eased in some countries thereafter. However, our results provide objective evidence of the impact of control measures on the population, and can inform the design and implementation of further local or national restrictions, for COVID-19 or emerging viral pandemics. Conclusions: Our study provides a comprehensive assessment of South Asian communities during the COVID-19 pandemic. We found a low uptake of recommended preventive measures among people from lower educational and socio-economic backgrounds, in women and in older age groups, ...

    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.

  3. Version published to 10.1101/2020.11.12.20229898v1 on medRxiv