Evidence map›Paper›PMID 38710715›Full record

ArticleScientific reports2024

Conventional and frugal methods of estimating COVID-19-related excess deaths and undercount factors.

Abhishek M Dedhe, Aakash A Chowkase, Niramay V Gogate, Manas M Kshirsagar, Rohan Naphade, Atharv Naphade, Pranav Kulkarni, Mrunmayi Naik, Aarya Dharm, Soham Raste and 11 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Abhishek M DedheJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA. adedhe@andrew.cmu.edu.ORCID 0000-0002-3881-8129
Aakash A ChowkaseJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.ORCID 0000-0001-6990-4698
Niramay V GogateJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.ORCID 0000-0002-7218-3323
Manas M KshirsagarJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.ORCID 0000-0001-6523-974X
Rohan NaphadeJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.
Atharv NaphadeJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.
Pranav KulkarniJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.ORCID 0000-0002-1461-0948
Mrunmayi NaikJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.ORCID 0009-0006-8699-4246
Aarya DharmJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.
Soham RasteJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.
Shravan PatankarJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.ORCID 0009-0004-3230-2756
Chinmay M JogdeoJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.ORCID 0000-0003-0018-1684
Aalok SatheJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.ORCID 0000-0002-5248-7557
Soham KulkarniJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.
Vibha BapatJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.
Rohinee JoshiJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.ORCID 0009-0004-8304-9754
Kshitij DeshmukhJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.ORCID 0000-0001-9367-4650
Subhash LeleJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA.
Kody J Manke-MillerDepartment of Psychology, Carnegie Mellon University, Pittsburgh, PA, USA.ORCID 0000-0002-2485-6538
Jessica F CantlonDepartment of Psychology, Carnegie Mellon University, Pittsburgh, PA, USA.
Pranav S PanditJPF Analytics, Jnana Prabodhini Foundation, Murrieta, CA, USA. pspandit@ucdavis.edu.ORCID 0000-0001-7649-0649

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Across the world, the officially reported number of COVID-19 deaths is likely an undercount. Establishing true mortality is key to improving data transparency and strengthening public health systems to tackle future disease outbreaks. In this study, we estimated excess deaths during the COVID-19 pandemic in the Pune region of India. Excess deaths are defined as the number of additional deaths relative to those expected from pre-COVID-19-pandemic trends. We integrated data from: (a) epidemiological modeling using pre-pandemic all-cause mortality data, (b) discrepancies between media-reported death compensation claims and official reported mortality, and (c) the "wisdom of crowds" public surveying. Our results point to an estimated 14,770 excess deaths [95% CI 9820-22,790] in Pune from March 2020 to December 2021, of which 9093 were officially counted as COVID-19 deaths. We further calculated the undercount factor-the ratio of excess deaths to officially reported COVID-19 deaths. Our results point to an estimated undercount factor of 1.6 [95% CI 1.1-2.5]. Besides providing similar conclusions about excess deaths estimates across different methods, our study demonstrates the utility of frugal methods such as the analysis of death compensation claims and the wisdom of crowds in estimating excess mortality.

Indexed as

COVID-19Epidemiological ModelsHumansIndiaPandemicsSARS-CoV-2COVID-19Excess mortality estimationFrugal scienceStatistical modelingWisdom of crowds

Identifiers

PMID38710715
PMCPMC11074152

What OpenQuestion holds

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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.