Introducing risk inequality metrics in tuberculosis policy development

• Tipo: Artigo em Revista Científica Internacional
• Data: 2019

Autores

Gomes, MGM (Autor) Outra; Oliveira, JF (Autor) Outra; Bertolde, A (Autor) Outra; Ayabina, D (Autor) Outra; Nguyen, TA (Autor) Outra; Maciel, EL (Autor) Outra; Duarte R (Autor) Outra; Nguyen, BH (Autor) Outra; Shete, PB (Autor) Outra; Lienhardt, C (Autor) Outra

Revista

Título: Nature Communications

Vol. 10

ISSN: 2041-1723

Editora: Springer Nature

Indexação

ISI Web of Knowledge - 6 Citações

Scopus - 8 Citações

Outras Informações

ID Authenticus: P-00Q-P3Y

DOI: 10.1038/s41467-019-10447-y

Abstract (EN): 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 interpretation and policy decisions. Anticipated impediments to estimating heterogeneity for each parameter are discouraging despite considerable technical progress in recent years. Here we identify acquisition of infection as the single process where heterogeneity most fundamentally impacts model outputs, due to selection imposed by dynamic forces of infection. We 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12