@article{fdi:010076067,
  title = {{I}ntroducing risk inequality metrics in tuberculosis policy development},
  author = {{G}omes, {M}. {G}. {M}. and {O}liveira, {J}. {F}. and {B}ertolde, {A}. and {A}yabina, {D}. and {N}guyen, {T}. {A}. and {M}aciel, {E}. {L}. and {D}uarte, {R}. and {N}guyen, {B}. {H}. and {S}hete, {P}. {B}. and {L}ienhardt, {C}hristian},
  editor = {},
  language = {{ENG}},
  abstract = {{G}lobal stakeholders including the {W}orld {H}ealth {O}rganization rely on predictive models for developing strategies and setting targets for tuberculosis care and control programs. {F}ailure to account for variation in individual risk leads to substantial biases that impair data interpretation and policy decisions. {A}nticipated impediments to estimating heterogeneity for each parameter are discouraging despite considerable technical progress in recent years. {H}ere 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. {W}e 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.},
  keywords = {},
  booktitle = {},
  journal = {{N}ature {C}ommunications},
  volume = {10},
  numero = {},
  pages = {art. 2480 [12 p.]},
  ISSN = {2041-1723},
  year = {2019},
  DOI = {10.1038/s41467-019-10447-y},
  URL = {https://www.documentation.ird.fr/hor/fdi:010076067},
}