Cargando…
Modelling the impact of effective private provider engagement on tuberculosis control in urban India
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’...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6405912/ https://www.ncbi.nlm.nih.gov/pubmed/30846709 http://dx.doi.org/10.1038/s41598-019-39799-7 |
_version_ | 1783401185342914560 |
---|---|
author | Arinaminpathy, Nimalan Deo, Sarang Singh, Simrita Khaparde, Sunil Rao, Raghuram Vadera, Bhavin Kulshrestha, Niraj Gupta, Devesh Rade, Kiran Nair, Sreenivas Achuthan Dewan, Puneet |
author_facet | Arinaminpathy, Nimalan Deo, Sarang Singh, Simrita Khaparde, Sunil Rao, Raghuram Vadera, Bhavin Kulshrestha, Niraj Gupta, Devesh Rade, Kiran Nair, Sreenivas Achuthan Dewan, Puneet |
author_sort | Arinaminpathy, Nimalan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6405912 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-64059122019-03-12 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 Sci Rep Article 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. Nature Publishing Group UK 2019-03-07 /pmc/articles/PMC6405912/ /pubmed/30846709 http://dx.doi.org/10.1038/s41598-019-39799-7 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Arinaminpathy, Nimalan Deo, Sarang Singh, Simrita Khaparde, Sunil Rao, Raghuram Vadera, Bhavin Kulshrestha, Niraj Gupta, Devesh Rade, Kiran Nair, Sreenivas Achuthan Dewan, Puneet Modelling the impact of effective private provider engagement on tuberculosis control in urban India |
title | Modelling the impact of effective private provider engagement on tuberculosis control in urban India |
title_full | Modelling the impact of effective private provider engagement on tuberculosis control in urban India |
title_fullStr | Modelling the impact of effective private provider engagement on tuberculosis control in urban India |
title_full_unstemmed | Modelling the impact of effective private provider engagement on tuberculosis control in urban India |
title_short | Modelling the impact of effective private provider engagement on tuberculosis control in urban India |
title_sort | modelling the impact of effective private provider engagement on tuberculosis control in urban india |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6405912/ https://www.ncbi.nlm.nih.gov/pubmed/30846709 http://dx.doi.org/10.1038/s41598-019-39799-7 |
work_keys_str_mv | AT arinaminpathynimalan modellingtheimpactofeffectiveprivateproviderengagementontuberculosiscontrolinurbanindia AT deosarang modellingtheimpactofeffectiveprivateproviderengagementontuberculosiscontrolinurbanindia AT singhsimrita modellingtheimpactofeffectiveprivateproviderengagementontuberculosiscontrolinurbanindia AT khapardesunil modellingtheimpactofeffectiveprivateproviderengagementontuberculosiscontrolinurbanindia AT raoraghuram modellingtheimpactofeffectiveprivateproviderengagementontuberculosiscontrolinurbanindia AT vaderabhavin modellingtheimpactofeffectiveprivateproviderengagementontuberculosiscontrolinurbanindia AT kulshresthaniraj modellingtheimpactofeffectiveprivateproviderengagementontuberculosiscontrolinurbanindia AT guptadevesh modellingtheimpactofeffectiveprivateproviderengagementontuberculosiscontrolinurbanindia AT radekiran modellingtheimpactofeffectiveprivateproviderengagementontuberculosiscontrolinurbanindia AT nairsreenivasachuthan modellingtheimpactofeffectiveprivateproviderengagementontuberculosiscontrolinurbanindia AT dewanpuneet modellingtheimpactofeffectiveprivateproviderengagementontuberculosiscontrolinurbanindia |