Evidence map›Paper›PMID 35074141›Full record

ArticleThe Indian journal of tuberculosis2022

Pediatric TB detection in the era of COVID-19.

Javeed A Golandaj

Abstract read
In one paragraph

Article in The Indian journal of tuberculosis, 2022. 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. Review
  2. 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

1 author.

Javeed A GolandajPopulation Research Centre, Under Ministry of Health and Family Welfare, GOI, JSS Institute of Economic Research, Dharwad, Karnataka 580004, India. Electronic address: javeediips@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The effect of COVID-19 and measures in response to it on human lives, including healthcare, was enormous. The necessary healthcare services including communicable diseases, such as Tuberculosis (TB) were badly affected. Here an attempt has been made to trace the number of notified Pediatric TB cases during and after COVID-19 lockdown and unlock period, and then compared with the same period of previous year. The epidemic data on notified pediatric TB cases for 2019 and 2020 were extracted from the Health Management Information System (HMIS) database. The absolute numbers of monthly pediatric TB notifications from January to September for the year 2020 were compared to 2019, and the percentage decrease was estimated. The HMIS data shows that there is a significant decrease in pediatric TB notifications during COVID-19 epidemic in India. Especially, when the lockdown and related restrictions in response to COVID-19 was imposed, notifications were significantly decreased compared to the same period during the previous year. Even, the reduction numbers of pediatric TB notifications during post-lockdown are still more worrying. Though, little improvements were observed suddenly after lockdown was removed, but then-after again consisted decrease was reported; and these numbers again substantially lower than the numbers of previous year. Adequate measures to diagnose, control, and prevent TB focusing young children, should be implemented simultaneously with response to COVID-19 pandemic. Further, effective steps should be taken to remove the fear arising due COVID-19 pandemic among masses, so that the healthcare seeking may be improved.

Indexed as

COVID-19TuberculosisChildChild, PreschoolCommunicable Disease ControlHumansPandemicsSARS-CoV-2COVID-19IndiaLockdownPediatricTB notifications

Identifiers

PMID35074141
PMCPMC8099540

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.