Evidence map›Paper›PMID 35714183›Full record

ArticleScience advances2022

Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience.

Maxwell Salvatore, Soumik Purkayastha, Lakshmi Ganapathi, Rupam Bhattacharyya, Ritoban Kundu, Lauren Zimmermann, Debashree Ray, Aditi Hazra, Michael Kleinsasser, Sunil Solomon and 2 more

Abstract read
In one paragraph

Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

12 authors.

Maxwell SalvatoreDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0002-3659-1514
Soumik PurkayasthaDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0002-3619-2804
Lakshmi GanapathiDivision of Infectious Diseases, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.ORCID 0000-0001-5055-0834
Rupam BhattacharyyaDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0003-4292-2372
Ritoban KunduDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0003-0967-6755
Lauren ZimmermannDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
Debashree RayDepartment of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-0979-2935
Aditi HazraDepartment of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Michael KleinsasserDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0002-7897-8231
Sunil SolomonDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID 0000-0002-3296-1514
Ramnath SubbaramanDepartment of Public Health and Community Medicine and Center for Global Public Health, Tufts University School of Medicine, Boston, MA, USA.ORCID 0000-0002-2063-943X
Bhramar MukherjeeDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0003-0118-4561

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

India experienced a massive surge in SARS-CoV-2 infections and deaths during April to June 2021 despite having controlled the epidemic relatively well during 2020. Using counterfactual predictions from epidemiological disease transmission models, we produce evidence in support of how strengthening public health interventions early would have helped control transmission in the country and significantly reduced mortality during the second wave, even without harsh lockdowns. We argue that enhanced surveillance at district, state, and national levels and constant assessment of risk associated with increased transmission are critical for future pandemic responsiveness. Building on our retrospective analysis, we provide a tiered data-driven framework for timely escalation of future interventions as a tool for policy-makers.

Identifiers

PMID35714183
PMCPMC9205583

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.