Evidence map›Paper›PMID 36962176›Full record

ArticlePLOS global public health2022

Assessment of COVID-19 data reporting in 100+ websites and apps in India.

Varun Vasudevan, Abeynaya Gnanasekaran, Bhavik Bansal, Chandrakant Lahariya, Giridara Gopal Parameswaran, James Zou

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Article in PLOS global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

6 authors.

Varun VasudevanInstitute for Computational & Mathematical Engineering, Stanford University, Stanford, California, United States of America.ORCID https://orcid.org/0000-0001-5013-6836
Abeynaya GnanasekaranInstitute for Computational & Mathematical Engineering, Stanford University, Stanford, California, United States of America.ORCID https://orcid.org/0000-0001-7088-9261
Bhavik BansalAll India Institute of Medical Sciences, New Delhi, India.ORCID https://orcid.org/0000-0002-8041-7302
Chandrakant LahariyaPublic Policy and Health Systems Specialist, New Delhi, India.ORCID https://orcid.org/0000-0003-2603-7090
Giridara Gopal ParameswaranCenter for Disease Dynamics, Economics & Policy, New Delhi, India.
James ZouDepartment of Biomedical Data Science, Stanford University School of Medicine, Stanford, California, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

India is among the top three countries in the world both in COVID-19 case and death counts. With the pandemic far from over, timely, transparent, and accessible reporting of COVID-19 data continues to be critical for India's pandemic efforts. We systematically analyze the quality of reporting of COVID-19 data in over one hundred government platforms (web and mobile) from India. Our analyses reveal a lack of granular data in the reporting of COVID-19 surveillance, vaccination, and vacant bed availability. As of 5 June 2021, age and gender distribution are available for less than 22% of cases and deaths, and comorbidity distribution is available for less than 30% of deaths. Amid rising concerns of undercounting cases and deaths in India, our results highlight a patchy reporting of granular data even among the reported cases and deaths. Furthermore, total vaccination stratified by healthcare workers, frontline workers, and age brackets is reported by only 14 out of India's 36 subnationals (states and union territories). There is no reporting of adverse events following immunization by vaccine and event type. By showing what, where, and how much data is missing, we highlight the need for a more responsible and transparent reporting of granular COVID-19 data in India.

Identifiers

PMID36962176
PMCPMC10022220

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Registered trials

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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.