Evidence map›Paper›PMID 30846709›Full record

ArticleScientific reports2019

Modelling the impact of effective private provider engagement on tuberculosis control in urban India.

Nimalan Arinaminpathy, Sarang Deo, Simrita Singh, Sunil Khaparde, Raghuram Rao, Bhavin Vadera, Niraj Kulshrestha, Devesh Gupta, Kiran Rade, Sreenivas Achuthan Nair and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2019. 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. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Closing gaps in the tuberculosis care cascade: an action-oriented research agenda.Journal of clinical tuberculosis and other mycobacterial diseases · 2020
    Review
  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

11 authors.

Nimalan ArinaminpathyDepartment of Infectious Disease Epidemiology, Imperial College London, London, UK. nim.pathy@imperial.ac.uk.
Sarang DeoIndian School of Business, Hyderabad, India.ORCID 0000-0002-3233-6014
Simrita SinghIndian School of Business, Hyderabad, India.
Sunil KhapardeCentral TB Division, Government of India, New Delhi, India.
Raghuram RaoCentral TB Division, Government of India, New Delhi, India.
Bhavin VaderaCentral TB Division, Government of India, New Delhi, India.
Niraj KulshresthaCentral TB Division, Government of India, New Delhi, India.
Devesh GuptaCentral TB Division, Government of India, New Delhi, India.
Kiran RadeWorld Health Organization, India Country Office, New Delhi, India.
Sreenivas Achuthan NairStop TB Partnership, Geneva, Switzerland.
Puneet DewanBill and Melinda Gates Foundation, Seattle, USA.

Funding

Medical Research Council MR/R015600/1World Health Organization 001
6 · The paper itself

Abstract

In India, the country with the world's largest burden of tuberculosis (TB), most patients first seek care in the private healthcare sector, which is fragmented and unregulated. Ongoing initiatives are demonstrating effective approaches for engaging with this sector, and form a central part of India's recent National Strategic Plan: here we aimed to address their potential impact on TB transmission in urban settings, when taken to scale. We developed a mathematical model of TB transmission dynamics, calibrated to urban populations in Mumbai and Patna, two major cities in India where pilot interventions are currently ongoing. We found that, when taken to sufficient scale to capture 75% of patient-provider interactions, the intervention could reduce incidence by upto 21.3% (95% Bayesian credible interval (CrI) 13.0-32.5%) and 15.8% (95% CrI 7.8-28.2%) in Mumbai and Patna respectively, between 2018 and 2025. There is a stronger impact on TB mortality, with a reduction of up to 38.1% (95% CrI 20.0-55.1%) in the example of Mumbai. The incidence impact of this intervention alone may be limited by the amount of transmission that has already occurred by the time a patient first presents for care: model estimates suggest an initial patient delay of 4-5 months before first seeking care, followed by a diagnostic delay of 1-2 months before ultimately initiating TB treatment. Our results suggest that the transmission impact of such interventions could be maximised by additional measures to encourage early uptake of TB services.

Indexed as

Models, TheoreticalPatient Acceptance of Health CarePrivate SectorCitiesDelayed DiagnosisHumansIndiaTuberculosisUrban Population

Identifiers

PMID30846709
PMCPMC6405912

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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.