Evidence map›Paper›PMID 33610777›Full record

ArticleInternational journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases2021

Geographic information system-based analysis of COVID-19 cases in India during pre-lockdown, lockdown, and unlock phases.

Hari Shankar Gangwar, P K Champati Ray

Abstract read
In one paragraph

Article in International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. The face behind the Covid-19 mask - A comprehensive review.Environmental technology & innovation · 2022
    Review
  5. Epidemiological investigation of the COVID-19 outbreak in Vellore district in South India using Geographic Information Surveillance (GIS).International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
    Article
  6. Article
  7. Review
  8. Article
  9. Air pollution in five Indian megacities during the Christmas and New Year celebration amidst COVID-19 pandemic.Stochastic environmental research and risk assessment : research journal · 2022
    Article
  10. 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

2 authors.

Hari Shankar GangwarIndian Institute of Remote Sensing, Dehradun, 248001, India. Electronic address: harishankar@iirs.gov.in.
P K Champati RayIndian Institute of Remote Sensing, Dehradun, 248001, India. Electronic address: champati_ray@iirs.gov.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe World Health Organization formally announced the global COVID-19 pandemic on March 11, 2020 due to widespread infections. In this study, COVID-19 cases in India were critically analyzed during the pre-lockdown (PLD), lockdown (LD), and unlock (UL) phases.

methodAnalyses were conducted using geospatial technology at district, state, and country levels, and comparisons were also made with other countries throughout the world that had the highest infection rates. India had the third highest infection rate in the world after the USA and Brazil during UL2.0-UL3.0 phases, the second highest after the USA during UL4.0-UL5.0 phases, and the highest among South Asian Association for Regional Cooperation (SAARC) countries in PLD-UL5.0 period.

resultsThe trend in the number of COVID-19 cases was associated with the population density where higher numbers tended to be record in the eastern, southern, and west-central parts of India. The death rate in India throughout the pandemic period under study was lower than the global average. Kerala reported the maximum number of infections during PLD whereas Maharashtra had the highest numbers during all LD and UL phases. Eighty percent of the cases in India were concentrated mainly in highly populous districts.

conclusionThe top 25 districts accounted for 70.99%, 69.38%, 54.87%, 44.23%, 40.48%, and 38.96% of the infections from the start of UL1.0 until the end of UL phases, respectively, and the top 26-50 districts accounted for 6.38%, 6.76%, 11.23%, 12.98%, 13.40%, and 13.61% of cases in these phase, thereby indicating that COVID-19 cases spread during the UL period. By October 31, 2020, Delhi had the highest number of infections, followed by Bengaluru Urban, Pune, Mumbai, Thane, and Chennai. No decline in the infection rate occurred, even in UL5.0, thereby indicating a highly alarming situation in India.

Indexed as

Geographic Information SystemsPandemicsSpatial AnalysisCommunicable Disease ControlCOVID-19Geographic MappingHumansIndiaRibosomal Protein L3SARS-CoV-2Ribosomal Protein L3COVID-19 pandemicGIS analysisGIS mappingLockdown and unlock phasesPreventive measures

Identifiers

PMID33610777
PMCPMC7891046

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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.