Prevalence of Long COVID symptoms in Bangladesh: a prospective Inception Cohort Study of COVID-19 survivors

  1. Mohammad Anwar Hossain
  2. K M Amran Hossain
  3. Karen Saunders
  4. Zakir Uddin
  5. Lori Maria Walton
  6. Veena Raigangar
  7. Mohamed Sakel
  8. Rubayet Shafin
  9. Mohammad Sohrab Hossain
  10. Md Feroz Kabir
  11. Rafey Faruqui
  12. Md Shohag Rana
  13. Md Shahoriar Ahmed
  14. Sonjit Kumar Chakrovorty
  15. Md Anwar Hossain
  16. Iqbal Kabir Jahid

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Abstract

The objective of this study was to identify the prevalence of long COVID symptoms in a large cohort of people living with and affected by long COVID and identify any potential associated risk factors.

Methods

A prospective survey was undertaken of an inception cohort of confirmed people living with and affected by long COVID (aged 18–87 years). 14392 participants were recruited from 24 testing facilities across Bangladesh between June and November 2020. All participants had a previously confirmed positive COVID-19 diagnosis, and reported persistent symptoms and difficulties in performing daily activities. Participants who consented were contacted by face-to-face interview, and were interviewed regarding long COVID, and restriction of activities of daily living using post COVID-19 functional status scale. Cardiorespiratory parameters measured at rest (heart rate, systolic blood pressure, diastolic blood pressure, oxygen saturation levels, maximal oxygen consumption, inspiratory and expiratory lung volume) were also measured.

Results

Among 2198 participants, the prevalence of long COVID symptoms at 12 weeks was 16.1%. Overall, eight long COVID symptoms were identified and in descending order of prominence are: fatigue, pain, dyspnoea, cough, anosmia, appetite loss, headache and chest pain. People living with and affected by long COVID experienced between 1 and 8 long COVID symptoms with an overall duration period of 21.8±5.2 weeks. Structural equation modelling predicted the length of long COVID to be related to younger age, female gender, rural residence, prior functional limitation and smoking.

Conclusion

In this cohort, at 31 weeks post diagnosis, the prevalence of long COVID symptoms was 16.1%. The risk factors identified for presence and longer length of long COVID symptoms warrant further research and consideration to support public health initiatives.

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  1. Version published to 10.1136/bmjgh-2021-006838
  2. ScreenIT

    SciScore for 10.1101/2021.07.03.21259626: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Exclusion criteria were: individuals too sick to participate; those who declined consent and those we were unable to contact.
    Field Sample Permit: The process of finding the contacts of the COVID-19 survivors, contacting them and perform data collection in this pandemic were permitted and approved by the appropriate authority of the Government of the People’s Republic of Bangladesh.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisThe sample size calculation was performed using “EPI INFO” software version 7.4.2.0 developed by the Center for Disease Control in the US.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The sample size calculation was performed using “EPI INFO” software version 7.4.2.0 developed by the Center for Disease Control in the US.
    INFO”
    suggested: None
    Figure 7 presents the associated risk factors identified for LCS using Structural Equation Modeling (SEM) using SPSS AMOS version 24.0 (Figure 7).
    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:
    The limitation of that study was that all participants had been treated as In-patients in hospital, unlike this research study, in which the majority of participants did not receive hospital treatment and remained at home during recovery. Our study adds valuable research knowledge to the gap in understanding the prevalence and nature of LCS in survivors, who have remained at home during their illness. Our study is larger than the two previous studies conducted in Bangladesh13-14 and provides new research knowledge on associated risk factors for LCS, in addition to identifying risk factors associated with a longer time length of these symptoms. In this study, the most common symptom during the acute phase was fever, closely followed by fatigue and upper respiratory tract symptoms. This is consistent with literature that has reported similar symptoms.25-26 The study found eight LCS, with fatigue being the most common symptom closely followed by muscle pain and dyspnea. In another study27, after three to nine months, 14% of individuals had fatigue problems. Most available literature unanimously reports fatigue1,15,16as the most common LCS. After this, many studies reportbreathlessness28,1,6 as the second most common LCS with other studies citing anosmia, cough and myalgia to also be common.29 Augustin et al30, reported a study where non-hospitalized COVID-19 patients had more anosmia (12.4%) and ageusia (11.1%) than fatigue (9.7%) and shortness of breath (8.6%) over a four-to-se...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.07.03.21259626v1 on medRxiv