Introducing risk inequality metrics in tuberculosis policy development.
Concrete metrics of risk inequality, their utility in mathematical models, and information for a risk inequality coefficient
Abstract
Global stakeholders including the World Health Organization rely on predictive models for developing strategies and setting targets for tuberculosis care and control programs. Failure to account for variation in individual risk leads to substantial biases that impair data inter- pretation and policy decisions. Anticipated impediments to estimating heterogeneity for each parameter are discouraging despite considerable technical progress in recent years.
The authors identify acquisition of infection as the single process where heterogeneity most fundamentally impacts model outputs, due to selection imposed by dynamic forces of infection. They introduce concrete metrics of risk inequality, demonstrate their utility in mathematical models, and pack the information into a risk inequality coefficient (RIC) which can be calculated and reported by national tuberculosis programs for use in policy development and modeling.
This research was supported by the UK Department for International Development’s Operational Research Capacity Building Programme led by the International Union Against TB and Lung Disease (The Union)
Citation
Gomes MGM, Oliveira JF, Bertolde A, Ayabina D, Nguyen TA, Maciel EL, Duarte R, Nguyen BH, Shete PB, Lienhardt C. Introducing risk inequality metrics in tuberculosis policy development. Nature Communications. 2019;10(1):2480.
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Introducing risk inequality metrics in tuberculosis policy development