ReviewIndian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine
Systematic Review of Excess Mortality in India during the Covid-19 Pandemic with Differentiation between Model-Based and Data-Based Mortality Estimates.
Review in Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 4 citations in OpenAlex.
- Conventional and frugal methods of estimating COVID-19-related excess deaths and undercount factors.Scientific reports · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: COVID-19 has proven to be the worst pandemic in the history of mankind. While the pandemic still continues to perplex scientists globally, attempts are being made to quantify the mortality caused by the pandemic. Official COVID-19 figures in India grossly understate the true scale of the pandemic in the country. Fatality rates help us understand the severity of a disease, identify at risk populations, and evaluate quality of healthcare. Official COVID-19 mortality figures in India grossly understate the true scale of the pandemic in the country. A COVID-19 death is defined for surveillance purposes as a death resulting from a clinically compatible illness in a probable or confirmed COVID-19 case, unless there is a clear alternative cause of death that cannot be related to COVID-19 disease (e.g., trauma) and excess mortality is defined as the difference in the total number of deaths in a crisis compared to those expected under normal conditions. Materials and Methods: We did a systematic review of multiple papers on PubMed, Medline, Embase, MedRxiV pre print on excess mortality. Differentiation between model based estimated excess mortality and data based excess mortality was studied. Results: All the studies showed that the excess mortality was to the tune of almost three times the official figures. The model based excess mortality assumptions showed higher deaths as compared to the data based one. However, there were a lot of discrepancies in the data provided by various states along with variations observed between the two waves as well. Health survey data suggested higher mortality rate as compared to data compiled from the civil registration system. Additionally, in the second wave, a small but a significant number of deaths occurred due to non availability of oxygen and beds in the hospitals. Conclusions: Official COVID-19 deaths have entirely failed to capture the scale of pandemic excess mortality in India. If most excess deaths were, indeed, from COVID-19 then under ascertainment of COVID-19 deaths has been high, with around 8-10 excess deaths for every recorded COVID-19 death.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.