دورية أكاديمية
An alternative estimation of the death toll of the Covid-19 pandemic in India.
العنوان: | An alternative estimation of the death toll of the Covid-19 pandemic in India. |
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المؤلفون: | Guilmoto CZ; Centre des Sciences Humaines, Delhi, India.; Ceped/IRD/Université de Paris/INSERM, Paris, France. |
المصدر: | PloS one [PLoS One] 2022 Feb 16; Vol. 17 (2), pp. e0263187. Date of Electronic Publication: 2022 Feb 16 (Print Publication: 2022). |
نوع المنشور: | Journal Article |
اللغة: | English |
بيانات الدورية: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
أسماء مطبوعة: | Original Publication: San Francisco, CA : Public Library of Science |
مواضيع طبية MeSH: | Mortality*, COVID-19/*epidemiology, Age Factors ; Data Collection ; Humans ; India/epidemiology ; Models, Statistical ; Pandemics ; SARS-CoV-2/isolation & purification ; Sex Factors |
مستخلص: | 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. Competing Interests: The authors have declared that no competing interests exist. |
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تواريخ الأحداث: | Date Created: 20220216 Date Completed: 20220228 Latest Revision: 20240823 |
رمز التحديث: | 20240823 |
مُعرف محوري في PubMed: | PMC8849468 |
DOI: | 10.1371/journal.pone.0263187 |
PMID: | 35171925 |
قاعدة البيانات: | MEDLINE |
تدمد: | 1932-6203 |
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DOI: | 10.1371/journal.pone.0263187 |