Did the National lockdown lock COVID-19 down in India, and reduce pressure on health infrastructure?

  1. Zakir Husain
  2. Arup Kumar Das
  3. Saswata Ghosh

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Abstract

Background & objectives: The spread of COVID19 in India has posed a major challenge for policy makers. Policy response in form of imposition of a prolonged national lockdown has imposed substantial costs on the entire population. But the extent to which it has contained the spread of the epidemic needs to be assessed. Methods: We use an Interrupted Time Series model to assess the success of lockdowns in containing COVID-19. In the second step, we use four variants of the SIR models to develop a counterfactual- what would have happened without the lockdown. These results are compared with actual data. The analysis is undertaken for India, and Maharashtra, Gujarat, Delhi, and Tamil Nadu. Results: Lockdown has reduced the number of COVID-19 cases by 23.65 to 337.73 lakh in Class I cities and towns, where COVID has mainly spread. It has averted about 0.01 to 0.10 lakh deaths. At the regional level, however, lockdown has averted a health crisis as existing ICU and ventilator facilities for critically ill patients would have been inadequate. Interpretation & conclusions: Overall, the results for three of the four models reveal that lockdown has a modest impact on spread of COVID-19; the health infrastructure at the national level is not over strained, even at the peak. At the regional level, on the other hand, lockdowns may have been justified. However, given that identification of new cases is limited by levels of daily testing that are low even by Asian standards, analysis based upon official data may have limitations and result in flawed decisions.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.27.20115329: (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
    It is estimated in STATA Version 15, using the ITSA module18, followed by testing for appropriate lag19, after adding two sets of extra terms for lockdowns 2 and 3. 2.3 SIR Model and related assumptions: In this study we use the SIR model to project the spread of COVID-19 in the absence of lockdowns.
    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:
    3.3 Influence of daily testing: The exercise, however, has a major limitation. The SIR model is based upon initial values of the epidemic, and assumes an exponential growth. In India, however, the number of new cases seems to follow a linear fit, with periodic changes in intercept and slope. While this may reflect the impact of containment policies, another possibility is that the trend in cases may reflect, not the spread of disease, but the increase in daily testing. Regression results (Table 3) indicate a positive and statistically relation between testing and new cases. If we eliminate the possible confounding effect of daily testing—by regressing new cases and time upon daily testing, estimating the residuals from each model (thereby eliminating the testing effect), and regressing residual of new cases upon residual of time —a significant and positive relation with time is still observed. It indicates that, even after accounting for the increase in testing, the number of new cases has a statistically significant time trend.

    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.

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  2. Version published to 10.1101/2020.05.27.20115329v1 on medRxiv