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Estimating the health and macroeconomic burdens of tuberculosis in India, 2021-2040: A fully integrated modelling
Marcus R Keogh-Brown1, Tom Sumner2, Sedona Sweeney1
1Department of Global Health and Development, Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Background:
Tuberculosis (TB) imposes a substantial health and economic burden on many populations and countries, but lack of funding has significantly contributed to several countries falling short of global TB reduction targets. Furthermore, existing assessments of the economic impact of TB do not capture the impacts on productivity and economic growth or the pathways by which epidemiology, demography, and the economy interact. Evidence is needed to answer how investment in treatment and control measures may help to mitigate the twin Indian health and macroeconomic burdens of TB over the coming decades.
Methods And Findings:
We develop a fully integrated dynamic macroeconomic-health-demographic simulation model for India, the country with the largest national TB burden, and use it to estimate the macroeconomic return to investment in TB treatment. Our estimated results indicate that, over 2021 to 2040, the health and macroeconomic burdens of TB in India will include over 62.4m incident cases, 8.1m TB-related deaths and a cumulative gross domestic product (GDP) loss of US$146.4bn. Low-income households will bear larger health and relative economic burdens while larger absolute economic burdens will fall on high-income households. Achieving the World Health Organisation's End TB target of 90% case detection could reduce clinical and demographic disease burdens by 75% to 89% and reduce the macroeconomic burden by US$120.2bn. Developing a 95% effective pan-TB treatment regimen would reduce the same burdens by 25% to 31% and US$35.3bn, respectively, while less effective but immediately achievable scaling-up of existing treatment regimens would reduce burdens by 20% to 25% and US$28.4bn, respectively. If an increase in case detection to 90% could be combined with 95% effective pan-TB treatment, it could reduce clinical and demographic disease burdens by 78% to 91% and reduce the macroeconomic burden by US$124.2bn. In order to develop this complex integrated model framework, some aspects of the epidemiological model were simplified such that the model does not capture, for example, separate modelling of drug susceptible and multidrug-resistant (MDR) cases or separate public/private healthcare provision. However, future iterations of the model could address these limitations.
Conclusions:
In this study, we find that even our least effective, but most accessible, revised TB treatment regimen has the potential to generate US$28bn in GDP gains. Clearly, the economic gains of increasing case detection rates and implementing improved TB treatment regimens hinges on both the feasibility and timeframe over which they can be achieved in practice. Nevertheless, the revised TB treatment regimen is readily accessible, and our results therefore demonstrate that there is room for undertaking substantial additional investment in control and treatment of TB in India, in order to reduce the suffering of TB patients while maintaining acceptable provision of resourcing elsewhere in the Indian economy.
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