New tuberculosis vaccines in India: Modelling the potential health and economic impacts of adolescent/adult vaccination with M72/AS01


Journal

medRxiv : the preprint server for health sciences
Titre abrégé: medRxiv
Pays: United States
ID NLM: 101767986

Informations de publication

Date de publication:
10 Jul 2023
Historique:
pubmed: 4 3 2023
medline: 4 3 2023
entrez: 3 3 2023
Statut: epublish

Résumé

Background India had an estimated 2.9 million tuberculosis cases and 506 thousand deaths in 2021. Novel vaccines effective in adolescents and adults could reduce this burden. M72/AS01E and BCG-revaccination have recently completed Phase IIb trials and estimates of their population-level impact are needed. We estimated the potential health and economic impact of M72/AS01E and BCG-revaccination in India and investigated the impact of variation in vaccine characteristics and delivery strategies. Methods We developed an age-stratified compartmental tuberculosis transmission model for India calibrated to country-specific epidemiology. We projected baseline epidemiology to 2050 assuming no-new-vaccine introduction, and M72/AS01E and BCG-revaccination scenarios over 2025-2050 exploring uncertainty in product characteristics (vaccine efficacy, mechanism of effect, infection status required for vaccine efficacy, duration of protection) and implementation (achieved vaccine coverage and ages targeted). We estimated reductions in tuberculosis cases and deaths by each scenario compared to no-new-vaccine introduction, as well as costs and cost-effectiveness from health-system and societal perspectives. Results M72/AS01E scenarios were predicted to avert 40% more tuberculosis cases and deaths by 2050 compared to BCG-revaccination scenarios. Cost-effectiveness ratios for M72/AS01E vaccines were around seven times higher than BCG-revaccination, but nearly all scenarios were cost-effective. The estimated average incremental cost was US$190 million for M72/AS01E and US$23 million for BCG-revaccination per year. Sources of uncertainty included whether M72/AS01E was efficacious in uninfected individuals at vaccination, and if BCG-revaccination could prevent disease. Conclusions M72/AS01E and BCG-revaccination could be impactful and cost-effective in India. However, there is great uncertainty in impact, especially given unknowns surrounding mechanism of effect and infection status required for vaccine efficacy. Greater investment in vaccine development and delivery is needed to resolve these unknowns in vaccine product characteristics.

Identifiants

pubmed: 36865172
doi: 10.1101/2023.02.24.23286406
pmc: PMC9980245
pii:
doi:

Types de publication

Preprint

Langues

eng

Subventions

Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Bill & Melinda Gates Foundation
ID : INV-001754
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI147321
Pays : United States

Commentaires et corrections

Type : UpdateIn

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Auteurs

Rebecca A Clark (RA)

TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine.
Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine.
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine.
Vaccine Centre, London School of Hygiene and Tropical Medicine.

Chathika K Weerasuriya (CK)

TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine.
Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine.
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine.

Allison Portnoy (A)

Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, USA.

Christinah Mukandavire (C)

TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine.
Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine.
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine.

Matthew Quaife (M)

TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine.
Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine.
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine.

Roel Bakker (R)

TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine.
Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine.
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine.
KNCV Tuberculosis Foundation.

Danny Scarponi (D)

TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine.
Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine.
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine.

Rebecca C Harris (RC)

TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine.
Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine.
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine.
Sanofi Pasteur, Singapore.

Kirankumar Rade (K)

World Health Organization, India.

Sanjay Kumar Mattoo (SK)

Central TB Division, NTEP, MoHFW Govt of India. New Delhi, India.

Dheeraj Tumu (D)

World Health Organization, India.
Central TB Division, NTEP, MoHFW Govt of India. New Delhi, India.

Nicolas A Menzies (NA)

Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, USA.
Department of Global Health and Population, Harvard T.H. Chan School of Public Health.

Richard G White (RG)

TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine.
Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine.
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine.

Classifications MeSH