Evidence map›Paper›PMID 41166290›Full record

ArticlePLOS global public health2025

Active case-finding for TB in India: Assessment of scale and quality benchmarks, time taken and use of rapid molecular diagnostic tests.

Hemant Deepak Shewade, S Kiran Pradeep, Prabhadevi Ravichandran, G Kiruthika, Amar N Shah, Bhavin Vadera, R Sabarinathan, Venkatesh Roddawar, Sanjay K Mattoo, Swati Iyer and 43 more

Abstract read
In one paragraph

Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

53 authors.

Hemant Deepak ShewadeICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.ORCID https://orcid.org/0000-0002-8242-1911
S Kiran PradeepICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Prabhadevi RavichandranICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.ORCID https://orcid.org/0000-0001-9221-2251
G KiruthikaICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.ORCID https://orcid.org/0000-0002-9431-2042
Amar N ShahUSAID India, New Delhi, India.
Bhavin VaderaUSAID India, New Delhi, India.
R SabarinathanICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Venkatesh RoddawarJohn Snow India Private Limited, New Delhi, India.ORCID https://orcid.org/0000-0001-5748-0349
Sanjay K MattooCentral TB Division, Ministry of Health and Family Welfare, New Delhi, India.ORCID https://orcid.org/0000-0001-9711-321X
Swati IyerOffice of the World Health Organization (WHO) Representative to India, WHO Country Office, New Delhi, India.
Dheeraj TumuOffice of the World Health Organization (WHO) Representative to India, WHO Country Office, New Delhi, India.
Aniket ChowdhuryOffice of the World Health Organization (WHO) Representative to India, WHO Country Office, New Delhi, India.
Shanmugasundaram DevikaICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Joshua ChadwickICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.ORCID https://orcid.org/0000-0002-8636-0634
Rakesh R VaidyaState TB Cell, Government of Gujarat, Ahmedabad, India.
Prasanta Kumar HotaState TB Cell, Government of Odisha, Bhubaneshwar, India.
Asha FrederickState TB Cell, Government of Tamil Nadu, Chennai, India.
Pankaj SinghState TB Cell, Government of Uttarakhand, Dehradun, India.
Bayarilin ShanpruEast Khasi Hills District TB Cell, Government of Meghalaya, Shillong, India.
Gunjan KhungerGanganagar District TB Cell, Government of Rajasthan, Ganganagar, India.
Subrata Kumar PandaOffice of the World Health Organization (WHO) Representative to India, WHO Country Office, New Delhi, India.
Mohamed Arif BaigOffice of the World Health Organization (WHO) Representative to India, WHO Country Office, New Delhi, India.
K V SumaOffice of the World Health Organization (WHO) Representative to India, WHO Country Office, New Delhi, India.
Mahendran SulekaICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Amit Kumar DigalICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Debobrata BanerjeeICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Machupalli Lakshmi PrasannaICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Divya Yashpal WaghelaICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
A KrishnarajICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Pratibha KashyapICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Jayeshbhai Sendhabhai ParmarICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Sushmita DasICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Ajit KumarICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Ajay KumarICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.ORCID https://orcid.org/0009-0005-3605-1496
Sunny YadavICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Shradha ChetriICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Subhashree Suchismita MahapatraICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Amit KumarICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Monu PathakICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Sachin SinghICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Shams TabrezICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.
Piyush MehraICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.ORCID https://orcid.org/0009-0008-7891-6787
Bipra BishnuOffice of the World Health Organization (WHO) Representative to India, WHO Country Office, New Delhi, India.
G MaheshOffice of the World Health Organization (WHO) Representative to India, WHO Country Office, New Delhi, India.
Biswabihari MohantyAnugul District TB Cell, Government of Odisha, Anugul, India.
A RajeshamState TB Cell, Government of Telangana, Hyderabad, India.
Bal Krishna MishraState TB Cell, Government of Bihar, Patna, India.
Dinesh N BarotKheda District TB Cell, Government of Gujarat, Nadiad, India.
Umesh Chandra TripathiOffice of the World Health Organization (WHO) Representative to India, WHO Country Office, New Delhi, India.
Khalid Umer KhayyamNational Institute of Tuberculosis and Respiratory Diseases, Government of India, New Delhi, India.
Kiran RadeOffice of the World Health Organization (WHO) Representative to India, WHO Country Office, New Delhi, India.ORCID https://orcid.org/0000-0001-7601-0780
Raghuram RaoCentral TB Division, Ministry of Health and Family Welfare, New Delhi, India.
Manoj V MurhekarICMR-National Institute of Epidemiology (ICMR-NIE), Chennai, India.

Funding

World Health Organization 001
6 · The paper itself

Abstract

Since 2017, tuberculosis active case-finding (TB ACF) has been implemented within the routine framework of India's national TB elimination program. Symptom screen of high-risk population followed by confirmation of TB among symptom-screen positive is the algorithm. ACF scale and quality assessments hitherto were predominantly local or based on aggregate program data with limited details on all the scale and quality indicators, the time taken and the extent of use of rapid molecular diagnostic tests in ACF care cascade. In this cohort study from high-risk populations in 30 randomly sampled districts (nine states), we assessed one ACF cycle (intention to screen the high-risk population once) during January-September 2023 using prospectively collected individual level data. 581 633 high-risk individuals were screened by the program utilizing existing workforce and resources. The two scale indicators (target, observed) were: percentage of i) population mapped as high-risk (≥11%, 18.3%) and ii) mapped population screened (≥90%, 7.4%). The four quality indicators (target, observed) were: percentage of i) screened identified as presumptive TB (≥5%, 2%) ii) presumptive TB tested (≥95%, 66.3%) iii) tested diagnosed as TB (≥5%, 1.6%) and iv) diagnosed put on treatment (≥95%, 100%). The number needed to screen (target ≤1538 considering the algorithm) to detect one person with TB was 4971. The same was observed across most of the high-risk groups, with few exceptions. The extent of using rapid molecular diagnostic tests was 26.4% and the median time taken from screening to sputum collection and testing was one day. To conclude, ACF scale and quality in 2023, assessed using prospectively collected individual level data, were grossly below the benchmark and lower than previously reported (2021) based on retrospective aggregate program data. Effective planning, resource allocation including use of rapid molecular diagnostic tests and individual data recording among those screened to facilitate implementation monitoring are recommended.

Identifiers

PMID41166290
PMCPMC12574901

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.