Age Pattern of Premature Mortality under varying scenarios of COVID-19 Infection in India

  1. Sanjay K Mohanty
  2. Umakanta Sahoo
  3. Udaya S Mishra
  4. Manisha Dubey

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

India is vulnerable to community infection of COVID-19 due to crowded and poor living condition, high density, slums in urban areas and poor health care system. The number of COVID 19 infection has crossed 300,000 with over 7,500 deaths despite a prolonged period of lock down and restrictions in public spaces. Given the likely scale and magnitude of this pandemic, it is important to understand its impact on the age pattern of mortality under varying scenarios.

Objective

The main objective of this paper is to understand the age pattern of mortality under varying scenarios of community infection.

Data and Methods

Data from the Sample Registration System (SRS), covidi19india.org and country specific data from worldmeter is used in the analyses. Descriptive statistics, case-fatality ratio, case fatality ratio with 14 days delay, abridged life table,years of potential life lost (YPLL) and disability adjusted life years (DALY) is used.

Results

The case fatality ratio (CFR) with 14 days delay for India is at least twice higher (8.0) than CFR of 3.4. Considering 8% mortality rate and varying scenario of community infection by 0.5%, 1% and 2%, India’s life expectancy will reduce by 0.8, 1.5 and 3.0 years and potential life years lost by 12.1 million, 24.3 million and 48.6 million years respectively. A community infection of 0.5% may result in DALY by 6.2 per 1000 population. Major share of PYLL and DALY is accounted by the working ages.

Conclusion

COVID-19 has a visible impact on mortality with loss of productive life years in working ages. Sustained effort at containing the transmission at each administrative unit is recommended to arrest mortality owing to COVID-19 pandemic.

What is known?

The case fatality rate associated with COVID-19 is low in India compared to many other countries. The mortality level is higher among elderly and people with co-morbidity.

Contribution

The case fatality ratio is illusive in the sense that the same with 14 days delay for India is at least twice higher (8.0). The COVID-19 attributable mortality has the potential to reduce the longevity of the population. Unlike developed countries, about half of the COVID-19 attributable mortality would be in the working age group of 45-64 years. With any level of community infection, the years of potential life lost (YPLL) and disability adjusted life years (DALY) world be highest in the working age group (45-64 years).

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.06.11.20128587: (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

    No key resources detected.

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The study suffers from following limitations. We believe that our estimates for elderly is underestimated as missing data is likely to be higher among elderly compared to younger population. Our assumption of all deaths due to COVID-19 would have been avoided if there were no COVID-19 cases may not always hold true and the assumption of SRS death rate of 2013-17 would prevail is illustrative. Despite these limitations, we believed that this study offers a reasonable understanding of the impact of COVID-19 on longevity in India. It has demonstrated the scope to replicate similar analyses elsewhere and guide the impact assessment of the epidemic in the national and global scene. Research Ethics Approval: The study does not involve human participation. It used secondary data available in public domain and research ethics approval not required.

    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.

  2. Version published to 10.1101/2020.06.11.20128587v1 on medRxiv