Workshop on Data-driven Computational
Epidemic Forecasting for West African Countries

Invited by the Forecasting for Social Good (F4SG) Research Network, we delivered an online workshop on epidemic forecasting. The registration was open to the public and the target audiences were researchers and practitioners from West African Countries.

Our vulnerability to emerging infectious diseases has been illustrated with the devastating impact of the COVID-19 pandemic. Forecasting epidemic trajectories (such as future incidence over the next four weeks) gives policymakers a valuable input for designing effective healthcare policies and optimizing supply chain decisions; however, this is a non-trivial task with multiple open questions. In this workshop, we will go through current research and practice in epidemic forecasting, from recent machine learning innovations to real-time forecasting challenges, with an emphasis in data-driven computational methods. Research topics include (but not limited to) leveraging heterogenous and multimodal data, handling data quality issues, spatio-temporal modeling, auto-regressive time-series models, topic models, uncertainty quantification, mechanistic models, and neural epidemic models. We will also share practical insights from our applied research experience in real-time forecasting for the US Centers of Disease Control and Prevention in influenza and COVID-19, and how forecasts may be used to inform decision-making.

  • Date: Wednesday 01 December 2021
  • Time: 09.00-13.00 Eastern Time, 14.00-18.00 (London)
  • Location: Virtual/Zoom
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Slides: [PDF].