Associated organisationsIndian Institute of Technology Bombay · London School of Hygiene & Tropical Medicine · Fundação Oswaldo Cruz · Universidade Federal Da Bahia · Universitas Indonesia · Universitas Padjadjaran · University of Indonesia · Witshealth Consortium (Pty) LTD. (South Africa)Europe PMC affiliations are not treated as award recipients or mapped locations.
Funding£3.5M
PeriodAug 2024 — Jul 2028
In plain English
AI plain-English summary
Tuberculosis kills more people globally than any other infectious disease, and drug-resistant strains are driving up both death rates and economic costs. Researchers in India, South Africa, Brazil, Indonesia, and the UK are building a computer model to help governments and global health agencies decide which combination of treatments, vaccines, and other interventions will save the most lives for the money available. New TB vaccines for adolescents and adults are now in late-stage trials, but no one knows how best to roll them out alongside existing drugs and diagnostics. The model will estimate the health impact, cost-effectiveness, and budget consequences of different options, then feed that evidence directly to decision-makers in countries that together account for 40 percent of global TB cases, as well as to the WHO, GAVI, and the Global Fund. If the model works, it could help these organisations shift from guesswork to data-driven planning, accelerating the decline of a disease that still kills over a million people each year.
View original technical description
TB is a leading global cause of death. Drug-resistant (DR)-TB causes a disproportionately large health and economic burden. New adolescent/adult TB vaccines are in phase 2b/3 trials, but implementation will be challenging, as is identifying the optimal choice of anti-TB interventions to make the best use of limited resources. In strong collaboration, we (India, South Africa, Brazil, Indonesia, UK) will create evidence to strengthen capacity and sustainably support high tuberculosis (TB) burden countries (HBC) and global decision-makers in reducing the global burden of TB, by using modelling tools to address key questions on drug-resistant (DR-)TB, new TB vaccines and other interventions, and extend and apply a state-of-the-art TB model, to estimate the relative health, cost-effectiveness, and budget impact, of new and existing interventions, as well as their optimal combination. The evidence created in the project will strengthen capacity and sustainably inform national and global decision-makers, including the governments of India, South Africa, Brazil and Indonesia (representing 40% of global TB), WHO, GAVI, and GFATM, to more rapidly reduce the global burden of TB.
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