Urban Sprawl of Covid-19 Epidemic in India: Lessons in the First Semester

  1. Rajeev Gupta
  2. Kiran Gaur
  3. Raghubir S Khedar
  4. Rajinder K Dhamija

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Abstract

Background & Objective

The covid-19 epidemic is rapidly escalating in India and unlike developed countries there is no evidence of plateau or decline in the past 6 months. To evaluate association of state-level sociodemographics with incident cases and deaths we performed an ecological study.

Methods

Publicly available data sources were used. Absolute number of covid-19 cases and deaths were obtained and cases and deaths/million in each state calculated from February to July 2020. To assess association of state level disease burden with sociodemographic variables (urbanization, human development, healthcare availability, healthcare access and quality etc.) we determined Pearson’s correlation and logarithmic trends.

Results

Covid-19 in India has led to >2,000,000 cases and 45,000 deaths by end July 2020. There is large variation in state-level cases/million ranging from 7247 (Delhi), 3728 (Goa) and 3427 (Maharashtra) to less than 300/million in a few. Deaths/million range from 212 (Delhi), 122 (Maharashtra) and 51 (Tamilnadu) to 2 in north-eastern states. Most of the high burden states (except Delhi) are reporting increasing burden and deaths with the largest increase in July 2020. There is a significant positive correlation of urbanization with covid-19 cases (r=0.65, R 2 =0.35) and deaths (r=0.60, R 2 =0.28) and weaker correlation with other sociodemographic variables. From March to July 2020, stable R 2 value for urbanization is observed with cases (0.37 to 0.39) while it is increasing for deaths (0.10 to 0.28).

Conclusions

Covid-19 epidemic is escalating in India and cases as well as deaths are significantly greater in more urbanized states. Prevention, control and treatment should focus on urban health systems.

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    SciScore for 10.1101/2020.08.17.20176537: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study has been conducted using publicly available data.9,14 The project proposal was submitted to institutional ethics committee as part of covid-19 registry being maintained at our centre.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    SPSS Statistical Package was used to calculate univariate and multivariate regression association statistics.
    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: 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

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  2. Version published to 10.1101/2020.08.17.20176537 on medRxiv