Who
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Population: Infants, children, and young adolescents aged 0–14 years living in 130 low-income and middle-income countries (LMICs).
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This group represents 99.5% of global paediatric TB incidence.
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Subgroups in 63 countries were further stratified by HIV status (no HIV, on ART, or not on ART).
What
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Focus of the Study: Estimate how cuts to US bilateral health aid and Global Fund contributions could affect paediatric tuberculosis (TB) incidence and mortality between 2025 and 2034.
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Key Findings:
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If US bilateral funding stops (Scenario 2):
+2.5 million paediatric TB cases and +340,000 TB deaths. -
If the US also withdraws from the Global Fund (Scenario 3):
+5.9 million cases and +0.9 million deaths. -
If non-US donors also reduce contributions by 50% (Scenario 4):
+8.9 million cases and +1.5 million deaths—134% increase in deaths vs continued funding.
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Interpretation: Cuts could reverse decades of gains, especially in Africa and South-East Asia.
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Implication: Rapid restoration of funding (even within one year) could reduce excess deaths by ≥90%.
When
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Study projection period: 2025–2034.
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Historical model base: Paediatric cohorts simulated from 2010 to allow full 0–14-year population by 2025.
Where
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Geographic scope:
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130 LMICs across all WHO regions (largest impacts in African Region and South-East Asia Region).
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Minimal projected impact in Europe and the Americas.
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Why
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Rationale:
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Children have higher susceptibility to TB infection and mortality than adults.
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US government cuts in early 2025 affected USAID, PEPFAR, and potentially The Global Fund.
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Many high-burden countries rely heavily on external TB/HIV funding; disruptions risk surging transmission, reduced treatment access, and increased deaths.
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How
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Study Design: Mathematical modelling study.
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Methods:
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Transmission-dynamic TB and HIV models calibrated for 130 countries.
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Used country-specific data on funding shares, TB/HIV epidemiology, malnutrition, and BCG vaccination.
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Created four funding scenarios, from no cuts to severe cuts involving both US and non-US donors.
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Modelled:
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Changes in force of infection (TB transmission risk),
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Declines in treatment coverage (TB treatment & ART),
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Resulting TB incidence and mortality among children.
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Incorporated parameter uncertainty using 1000 Monte Carlo simulations.
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Validation: Compared model outputs to WHO and Global Burden of Disease estimates for recent years.
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