Estimating COVID-19‒ Related Mortality in India: An Epidemiological Challenge With Insufficient Data

Zimmermann, Lauren; Salvatore, Maxwell; Babu, Giridhara R; Mukherjee, Bhramar

doi:10.2105/ajph.2021.306419

Cited by 29 publications

(24 citation statements)

References 5 publications

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“…Any reasonable calculation of infection fatality rates will need to incorporate this undercounting into account. A recent paper by Zimmermann et al 36 calculates the Infection Fatality Rate for India to be around 0.1% using observed death counts and 0.4% after incorporating underreporting of deaths and discusses the range of problems associated with underreporting of deaths and cases.…”

Section: Discussionmentioning

confidence: 99%

“…However, such an assumption might not hold in reality. One possible solution is to replace 𝛽 t by 𝛽 t 𝜋(t) as done by Ray et al 37 Here, 𝜋(t) is a time-varying intervention modifier which takes values in [0, 1] for stricter lockdown relative to the last period in the training data. The credible intervals observed in our procedure are extremely narrow, indicating underestimation of uncertainties inherent in the predictions.…”

Section: Discussionmentioning

confidence: 99%

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Extending the susceptible‐exposed‐infected‐removed (SEIR) model to handle the false negative rate and symptom‐based administration of COVID‐19 diagnostic tests: SEIR‐fansy

Bhaduri

Kundu

Purkayastha

et al. 2022

Statistics in Medicine

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False negative rates of severe acute respiratory coronavirus 2 diagnostic tests, together with selection bias due to prioritized testing can result in inaccurate modeling of COVID-19 transmission dynamics based on reported "case" counts. We propose an extension of the widely used Susceptible-Exposed-Infected-Removed (SEIR) model that accounts for misclassification error and selection bias, and derive an analytic expression for the basic reproduction number R 0 as a function of false negative rates of the diagnostic tests and selection probabilities for getting tested. Analyzing data from the first two waves of the pandemic in India, we show that correcting for misclassification and selection leads to more accurate prediction in a test sample. We provide estimates of undetected infections and deaths between April 1, 2020 and August 31, 2021. At the end of the first wave in India, the estimated under-reporting factor for cases was at 11.1 (95%

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Extending the susceptible‐exposed‐infected‐removed (SEIR) model to handle the false negative rate and symptom‐based administration of COVID‐19 diagnostic tests: SEIR‐fansy

Bhaduri

Kundu

Purkayastha

et al. 2022

Statistics in Medicine

Self Cite

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show abstract

“…and other apparent factors (heart attacks, etc.) when the WHO recommends suspected cases of Covid-19 to be reported as such [5][6][7][8][9]. More generally, Covid-19 is a source of shame.…”

Section: Absence Of Reliable Estimates Of Covid-19 Deaths In Indiamentioning

confidence: 99%

An alternative estimation of the death toll of the Covid-19 pandemic in India

Guilmoto

2022

PLoS ONE

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The absence of reliable registration of Covid-19 deaths in India has prevented proper assessment and monitoring of the coronavirus pandemic. In addition, India’s relatively young age structure tends to conceal the severity of Covid-19 mortality, which is concentrated in older age groups. In this paper, we present four different demographic samples of Indian populations for which we have information on both their demographic structures and death outcomes. We show that we can model the age distribution of Covid-19 mortality in India and use this modeling to estimate Covid-19 mortality in the country. Our findings point to a death toll of approximately 3.2–3.7 million persons by early November 2021. Once India’s age structure is factored in, these figures correspond to one of the most severe cases of Covid-19 mortality in the world. India has recorded after February 2021 the second outbreak of coronavirus that has affected the entire country. The accuracy of official statistics of Covid-19 mortality has been questioned, and the real number of Covid-19 deaths is thought to be several times higher than reported. In this paper, we assembled four independent population samples to model and estimate the level of Covid-19 mortality in India. We first used a population sample with the age and sex of Covid-19 victims to develop a Gompertz model of Covid-19 mortality in India. We applied and adjusted this mortality model on two other national population samples after factoring in the demographic characteristics of these samples. We finally derive from these samples the most reasonable estimate of Covid-19 mortality level in India and confirm this result using a fourth population sample. Our findings point to a death toll of about 3.2–3.7 million persons by late May 2021. This is by far the largest number of Covid-19 deaths in the world. Once standardized for age and sex structure, India’s Covid-19 mortality rate is above Brazil and the USA. Our analysis shows that existing population samples allow an alternative estimation of deaths due to Covid-19 in India. The results imply that only one out of 7–8 deaths appear to have been recorded as a Covid-19 death in India. The estimates also point to a very high Covid-19 mortality rate, which is even higher after age and sex standardization. The magnitude of the pandemic in India requires immediate attention. In the absence of effective remedies, this calls for a strong response based on a combination of non-pharmaceutical interventions and the scale-up of vaccination to make them accessible to all, with an improved surveillance system to monitor the progression of the pandemic and its spread across India’s regions and social groups.

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“…Zimmermann et al [74] found that the number of cases in India was under-reported by a factor of 10 to 20, and the number of deaths were under-reported by a factor of 2 to 5. Similarly Jha et al [38] studied and collected data about COVID-19 mortality in India.…”

Section: Related Workmentioning

confidence: 99%

Co-WIN: Really Winning? Analysing Inequity in India's Vaccination Response

Karandikar¹,

Prabhu²,

Mathur³

et al. 2022

Preprint

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The COVID-19 pandemic has so far accounted for reported 5.5𝑀 deaths worldwide, with 8.7% of these coming from India. The pandemic exacerbated the weakness of the Indian healthcare system. As of January 20, 2022, India is the second worst affected country with 38.2𝑀 reported cases and 487𝐾 deaths. According to epidemiologists, vaccines are an essential tool to prevent the spread of the pandemic. India's vaccination drive began on January 16, 2021 with governmental policies being introduced to prioritize different populations of the society. Through the course of the vaccination drive, multiple new policies were also introduced to ensure that vaccines are readily available and vaccination coverage is increased. However, at the same time, some of the government policies introduced led to unintended inequities in the populations being targeted. In this report, we enumerate and analyze the inequities that existed in India's vaccination policy drive, and also compute the effect of the new policies that were introduced. We analyze these potential inequities not only qualitatively but also quantitatively by leveraging the data that was made available through the government portals. Specifically, (a) we discover inequities that might exist in the policies, (b) we quantify the effect of new policies introduced to increase vaccination coverage, and (c) we also point the data discrepancies that exist across different data sources.

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Estimating COVID-19‒ Related Mortality in India: An Epidemiological Challenge With Insufficient Data

Cited by 29 publications

References 5 publications

Extending the susceptible‐exposed‐infected‐removed (SEIR) model to handle the false negative rate and symptom‐based administration of COVID‐19 diagnostic tests: SEIR‐fansy

Extending the susceptible‐exposed‐infected‐removed (SEIR) model to handle the false negative rate and symptom‐based administration of COVID‐19 diagnostic tests: SEIR‐fansy

An alternative estimation of the death toll of the Covid-19 pandemic in India

Co-WIN: Really Winning? Analysing Inequity in India's Vaccination Response

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