Cargando…
The potential impact of vaccination on tuberculosis burden in India: A modelling analysis
BACKGROUND & OBJECTIVES: Vaccination will play an important role in meeting the end tuberculosis (TB) goals. While certain vaccine candidates in advanced stages of clinical trials raise hope for the future availability of new tools, in the immediate term, there is also increasing interest in Bac...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10319376/ https://www.ncbi.nlm.nih.gov/pubmed/37202930 http://dx.doi.org/10.4103/ijmr.ijmr_328_23 |
_version_ | 1785068235398316032 |
---|---|
author | Arinaminpathy, Nimalan Rade, Kirankumar Kumar, Ravinder Joshi, Rajendra P. Rao, Raghuram |
author_facet | Arinaminpathy, Nimalan Rade, Kirankumar Kumar, Ravinder Joshi, Rajendra P. Rao, Raghuram |
author_sort | Arinaminpathy, Nimalan |
collection | PubMed |
description | BACKGROUND & OBJECTIVES: Vaccination will play an important role in meeting the end tuberculosis (TB) goals. While certain vaccine candidates in advanced stages of clinical trials raise hope for the future availability of new tools, in the immediate term, there is also increasing interest in Bacille Calmette–Guérin revaccination among adults and adolescents as a potential strategy. Here, we sought to estimate the potential epidemiological impact of TB vaccination in India. METHODS: We developed a deterministic, age-structured, compartmental model of TB in India. Data from the recent national prevalence survey was used to inform epidemiological burden while also incorporating a vulnerable population who may be prioritized for vaccination, the latter consistent with the burden of undernutrition. Using this framework, the potential impact on incidence and mortality of a vaccine with 50 per cent efficacy was estimated, if rolled out in 2023 to cover 50 per cent of the unvaccinated each year. Simulated impacts were compared for disease- vs. infection-preventing vaccines, as well as when prioritizing vulnerable groups (those with undernutrition) rather than the general population. A sensitivity analyses were also conducted with respect to the duration, and efficacy, of vaccine immunity. RESULTS: When rolled out in the general population, an infection-preventing vaccine would avert 12 per cent (95% Bayesian credible intervals (Crl): 4.3-28%) of cumulative TB incidence between 2023 and 2030, while a disease-preventing vaccine would avert 29 per cent (95% Crl: 24-34%). Although the vulnerable population accounts for only around 16 per cent of India’s population, prioritizing this group for vaccination would achieve almost half the impact of rollout in the general population, in the example of an infection-preventing vaccine. Sensitivity analysis also highlights the importance of the duration and efficacy of vaccine-induced immunity. INTERPRETATION & CONCLUSIONS: These results highlight how even a vaccine with moderate effectiveness (50%) could achieve substantial reductions in TB burden in India, especially when prioritized for the most vulnerable. |
format | Online Article Text |
id | pubmed-10319376 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Wolters Kluwer - Medknow |
record_format | MEDLINE/PubMed |
spelling | pubmed-103193762023-07-05 The potential impact of vaccination on tuberculosis burden in India: A modelling analysis Arinaminpathy, Nimalan Rade, Kirankumar Kumar, Ravinder Joshi, Rajendra P. Rao, Raghuram Indian J Med Res Policy: Original Article BACKGROUND & OBJECTIVES: Vaccination will play an important role in meeting the end tuberculosis (TB) goals. While certain vaccine candidates in advanced stages of clinical trials raise hope for the future availability of new tools, in the immediate term, there is also increasing interest in Bacille Calmette–Guérin revaccination among adults and adolescents as a potential strategy. Here, we sought to estimate the potential epidemiological impact of TB vaccination in India. METHODS: We developed a deterministic, age-structured, compartmental model of TB in India. Data from the recent national prevalence survey was used to inform epidemiological burden while also incorporating a vulnerable population who may be prioritized for vaccination, the latter consistent with the burden of undernutrition. Using this framework, the potential impact on incidence and mortality of a vaccine with 50 per cent efficacy was estimated, if rolled out in 2023 to cover 50 per cent of the unvaccinated each year. Simulated impacts were compared for disease- vs. infection-preventing vaccines, as well as when prioritizing vulnerable groups (those with undernutrition) rather than the general population. A sensitivity analyses were also conducted with respect to the duration, and efficacy, of vaccine immunity. RESULTS: When rolled out in the general population, an infection-preventing vaccine would avert 12 per cent (95% Bayesian credible intervals (Crl): 4.3-28%) of cumulative TB incidence between 2023 and 2030, while a disease-preventing vaccine would avert 29 per cent (95% Crl: 24-34%). Although the vulnerable population accounts for only around 16 per cent of India’s population, prioritizing this group for vaccination would achieve almost half the impact of rollout in the general population, in the example of an infection-preventing vaccine. Sensitivity analysis also highlights the importance of the duration and efficacy of vaccine-induced immunity. INTERPRETATION & CONCLUSIONS: These results highlight how even a vaccine with moderate effectiveness (50%) could achieve substantial reductions in TB burden in India, especially when prioritized for the most vulnerable. Wolters Kluwer - Medknow 2023 2023-05-03 /pmc/articles/PMC10319376/ /pubmed/37202930 http://dx.doi.org/10.4103/ijmr.ijmr_328_23 Text en Copyright: © 2023 Indian Journal of Medical Research https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Policy: Original Article Arinaminpathy, Nimalan Rade, Kirankumar Kumar, Ravinder Joshi, Rajendra P. Rao, Raghuram The potential impact of vaccination on tuberculosis burden in India: A modelling analysis |
title | The potential impact of vaccination on tuberculosis burden in India: A modelling analysis |
title_full | The potential impact of vaccination on tuberculosis burden in India: A modelling analysis |
title_fullStr | The potential impact of vaccination on tuberculosis burden in India: A modelling analysis |
title_full_unstemmed | The potential impact of vaccination on tuberculosis burden in India: A modelling analysis |
title_short | The potential impact of vaccination on tuberculosis burden in India: A modelling analysis |
title_sort | potential impact of vaccination on tuberculosis burden in india: a modelling analysis |
topic | Policy: Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10319376/ https://www.ncbi.nlm.nih.gov/pubmed/37202930 http://dx.doi.org/10.4103/ijmr.ijmr_328_23 |
work_keys_str_mv | AT arinaminpathynimalan thepotentialimpactofvaccinationontuberculosisburdeninindiaamodellinganalysis AT radekirankumar thepotentialimpactofvaccinationontuberculosisburdeninindiaamodellinganalysis AT kumarravinder thepotentialimpactofvaccinationontuberculosisburdeninindiaamodellinganalysis AT joshirajendrap thepotentialimpactofvaccinationontuberculosisburdeninindiaamodellinganalysis AT raoraghuram thepotentialimpactofvaccinationontuberculosisburdeninindiaamodellinganalysis AT arinaminpathynimalan potentialimpactofvaccinationontuberculosisburdeninindiaamodellinganalysis AT radekirankumar potentialimpactofvaccinationontuberculosisburdeninindiaamodellinganalysis AT kumarravinder potentialimpactofvaccinationontuberculosisburdeninindiaamodellinganalysis AT joshirajendrap potentialimpactofvaccinationontuberculosisburdeninindiaamodellinganalysis AT raoraghuram potentialimpactofvaccinationontuberculosisburdeninindiaamodellinganalysis |