Epidemiological versus meteorological forecasts: Best practice for linking models to policymaking

Erin Coughlan de Perez*, Elisabeth Stephens, M. van Aalst, Juan Bazo, Eleonore Fournier-Tombs, Sebastian Funk, Jeremy J. Hess, Nicola Ranger, Rachel Lowe

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
24 Downloads (Pure)


Weather forecasts, climate change projections, and epidemiological predictions all represent domains that are using forecast data to take early action for risk management. However, the methods and applications of the modeling efforts in each of these three fields have been developed and applied with little cross-fertilization. This perspective identifies best practices in each domain that can be adopted by the others, which can be used to inform each field separately as well as to facilitate a more effective combined use for the management of compound and evolving risks. In light of increased attention to predictive modeling during the COVID-19 pandemic, we identify three major areas that all three of these modeling fields should prioritize for future investment and improvement: (1) decision support, (2) conveying uncertainty, and (3) capturing vulnerability.

Original languageEnglish
Pages (from-to)521-526
Number of pages6
JournalInternational Journal of Forecasting
Issue number2
Early online date21 Sept 2021
Publication statusPublished - 1 Apr 2022


  • Climate
  • Communication
  • COVID-19
  • Disasters
  • Forecasting
  • Risk
  • Uncertainty
  • Vulnerability
  • Weather


Dive into the research topics of 'Epidemiological versus meteorological forecasts: Best practice for linking models to policymaking'. Together they form a unique fingerprint.

Cite this