Spread of infection and treatment interruption among Japanese workers during the COVID-19 pandemic: A cross-sectional study

  1. Jun Akashi
  2. Ayako Hino
  3. Seiichiro Tateishi
  4. Tomohisa Nagata
  5. Mayumi Tsuji
  6. Akira Ogami
  7. Shinya Matsuda
  8. Masaharu Kataoka
  9. Yoshihisa Fujino

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Abstract

The COVID-19 pandemic has resulted in treatment interruption for chronic diseases. The scale of COVID-19 in Japan has varied greatly in terms of the scale of infection and the speed of spread depending on the region. This study aimed to examine the relationship between local infection level and treatment interruption among Japanese workers.

Methods

Cross-sectional internet survey was conducted from December 22 to 26, 2020. Of 33,302 participants, 9,510 (5,392 males and 4,118 females) who responded that they required regular treatment were included in the analysis. The infection level in each participant's prefecture of residence was assessed based on the incidence rate (per 1,000 population) and the number of people infected. Age-sex and multivariate adjusted odds ratios (ORs) of regional infection levels associated with treatment interruption were estimated by multilevel logistic models, nested by prefecture of residence. The multivariate model was adjusted for sex, age, marital status, equivalent household income, educational level, occupation, self-rated health status and anxiety.

Results

The ORs of treatment interruption for the lowest and highest levels of infection in the region were 1.32 [95 % confidence interval (CI) were 1.09–1.59] for the overall morbidity rate (per 1,000) and 1.34 (95 % CI 1.10–1.63) for the overall number of people infected. Higher local infection levels were linked to a greater number of workers experiencing treatment interruption.

Conclusions

Higher local infection levels were linked to more workers experiencing treatment interruption. Our results suggest that apart from individual characteristics such as socioeconomic and health status, treatment interruption during the pandemic is also subject to contextual effects related to regional infection levels. Preventing community spread of COVID-19 may thus protect individuals from indirect effects of the pandemic, such as treatment interruption.

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  1. Version published to 10.3389/fpubh.2022.921966
  2. ScreenIT

    SciScore for 10.1101/2021.07.21.21260691: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: This study was approved by the Ethics Committee of the University of Occupational and Environmental Health, Japan (reference No. R2-079 and R3-006).
    Consent: Participants provided informed consent by completing a form on the survey website.
    Sex as a biological variableOf the 27,036 remaining participants, data from 9,510 (5392 males and 4118 females) who stated they needed regular treatment or hospital visits were analyzed.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All analyses were conducted using Stata (Stata Statistical Software: Release 16; StataCorp LLC, TX, USA).
    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: We detected the following sentences addressing limitations in the study:
    However, this study also had several limitations. First, because we conducted a cross-sectional study, causality could not be determined. However, since it is theoretically unlikely that treatment interruption experienced by an individual will increase the COVID-19 infection rate in a region, we think it is likely that high regional infection rates cause treatment interruption. Second, we did not identify workers’ reasons for discontinuing treatment in this study. As discussed above, there are various possible causes of treatment interruption, which may vary by region. Third, we did not inquire about the diseases being treated. Treatment interruption may vary depending on the presence or absence of symptoms and the potential disadvantages of discontinuing treatment for a particular disease.

    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.

    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 10.1101/2021.07.21.21260691v1 on medRxiv