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Modelling the impact of effective private provider engagement on tuberculosis control in urban India.
Arinaminpathy, Nimalan; Deo, Sarang; Singh, Simrita; Khaparde, Sunil; Rao, Raghuram; Vadera, Bhavin; Kulshrestha, Niraj; Gupta, Devesh; Rade, Kiran; Nair, Sreenivas Achuthan; Dewan, Puneet.
Affiliation
  • Arinaminpathy N; Department of Infectious Disease Epidemiology, Imperial College London, London, UK. nim.pathy@imperial.ac.uk.
  • Deo S; Indian School of Business, Hyderabad, India.
  • Singh S; Indian School of Business, Hyderabad, India.
  • Khaparde S; Central TB Division, Government of India, New Delhi, India.
  • Rao R; Central TB Division, Government of India, New Delhi, India.
  • Vadera B; Central TB Division, Government of India, New Delhi, India.
  • Kulshrestha N; Central TB Division, Government of India, New Delhi, India.
  • Gupta D; Central TB Division, Government of India, New Delhi, India.
  • Rade K; World Health Organization, India Country Office, New Delhi, India.
  • Nair SA; Stop TB Partnership, Geneva, Switzerland.
  • Dewan P; Bill and Melinda Gates Foundation, Seattle, USA.
Sci Rep ; 9(1): 3810, 2019 03 07.
Article in En | MEDLINE | ID: mdl-30846709
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Tuberculosis / Patient Acceptance of Health Care / Private Sector / Models, Theoretical Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Country/Region as subject: Asia Language: En Journal: Sci Rep Year: 2019 Document type: Article Affiliation country: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Tuberculosis / Patient Acceptance of Health Care / Private Sector / Models, Theoretical Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Country/Region as subject: Asia Language: En Journal: Sci Rep Year: 2019 Document type: Article Affiliation country: United kingdom