title: Beyond crystal balls: crosscutting solutions in global health to prepare for an unpredictable future.
abstract: BACKGROUND
  Efforts in global heath need to deal not only with current challenges, but also to anticipate new scenarios, which sometimes unfold at lightning speed. Predictive modeling is frequently used to assist planning, but outcomes depend heavily on a subset of critical assumptions, which are mostly hampered by our limited knowledge about the many factors, mechanisms and relationships that determine the dynamics of disease systems, by a lack of data to parameterize and validate models, and by uncertainties about future scenarios.
  
  
  CONCLUSIONS
  We propose a shift from a focus on the prediction of individual disease patterns to the identification and mitigation of broader fragilities in public health systems. Modeling capabilities should be used to perform "stress tests" on how interrelated fragilities respond when faced with a range of possible or plausible threats of different nature and intensity. This system should be able to reveal crosscutting solutions with the potential to address not only one threat, but multiple areas of vulnerability to future health risks. Actionable knowledge not based on a narrow subset of threats and conditions can better guide policy, build societal resilience and ensure effective prevention in an uncertain world.
authors.affiliation: Fogarty International Center, National Institutes of Health, Bethesda, Maryland, 20892, USA. alonsow@mail.nih.gov.|Origem Scientifica, São Paulo, São Paulo, Brazil. alonsow@mail.nih.gov.
authors.forename: Wladimir Jimenez
authors.initials: WJ
authors.lastname: Alonso
authors.affiliation: Fogarty International Center, National Institutes of Health, Bethesda, Maryland, 20892, USA. ben.mccormick@nih.gov.
authors.forename: Benjamin Joseph James
authors.initials: BJ
authors.lastname: McCormick
authors.affiliation: Fogarty International Center, National Institutes of Health, Bethesda, Maryland, 20892, USA. millemar@mail.nih.gov.
authors.forename: Mark A
authors.initials: MA
authors.lastname: Miller
authors.affiliation: Origem Scientifica, São Paulo, São Paulo, Brazil. cynthia.paim@wolfson.oxon.org.
authors.forename: Cynthia
authors.initials: C
authors.lastname: Schuck-Paim
authors.affiliation: Joint Global Change Research Institute, University of Maryland, College Park, MD, 20740, USA. ghassem.asrar@pnnl.gov.
authors.forename: Ghassem R
authors.initials: GR
authors.lastname: Asrar
mesh_terms: D005544:Forecasting; D014943:Global Health / Q000639:trends*; D006801:Humans; D008962:Models, Theoretical; D011634:Public Health / Q000639:trends*