About the Uncertainty of Forecasting Fatalities in Armed Conflict (UFFAC) project

Taking uncertainty into account when forecasting future conflict is of paramount importance to facilitate use of data-driven predictions for anticipatory action and crisis response. Uncertainty of Forecasting Fatalities in Armed Conflict (UFFAC) is the first comprehensive research project of its kind that addresses this need.  
Building onto and expanding the Violence & Impacts Early Warning System (VIEWS), the UFFAC project sets out to develop prediction models that forecast the number of fatalities in armed conflict while carefully exploring and assessing the multiple sources of uncertainty thereof with each monthly release of new VIEWS data. In addition to a thorough review of the extent to which prediction uncertainty can be fully assessed, the project will also explore how best to evaluate the quality of the forecasting models, taking both forecasts and their associated uncertainty into account.
Over the course of the UFFAC project, we will expand the VIEWS model from predicting only state-based conflict to also predicting direct deaths from one-sided violence and non-state conflict, per the UCDP definitions thereof. 
  • Host institution: PRIO
  • Funder: The Norwegian Research Council (NFR)
  • Project duration: September 2023 – September 2025
  • Project members: Håvard Hegre, Jonas Vestby, Paola Vesco, Céline Cunen, Halvard Buhaug, Jonathan Williams
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Work Packages

The project covers four interlinked Work Packages (WPs):
  • WP1: Uncertainty
    To address statistical uncertainty, UFFAC will made systematic use of bootstrapping approaches, explore missing data and measurement uncertainty issues, and also explore whether uncertainty itself is a useful early warning signal.
  • WP2: Constituent models
    UFFAC will review and specify a number of algorithms and combination of predictors that together form a specific forecasting model.
  • WP3: Ensembling and calibration
    UFFAC will explore techniques to combine the insights from individual constituent models into an aggregated ‘model ensemble’ (a set of models), while processing their forecasts so that the end result comes as close to the distribution of the outcome variable as possible.
  • WP4: Evaluation
    UFFAC will develop a protocol for evaluating whether the forecasting models are optimal, discussing the criteria for specifying what is optimal as well as the technical solutions. The entire model system will be validated by a gradual integration with the VIEWS early-warning system.