The “Data in Crises” paper calls for re-thinking how data are leveraged in planning for and responding to disasters in the United States, by calling for preempting the needs of medically vulnerable populations, and provisioning for disruptions in major utilities during natural disasters.

Pointing to recent disasters in the United States — including Hurricane Maria, Winter storms in Texas, and wildfires across California — the authors of the paper argue that novel data streams could help mitigate both the short and longterm impacts of emergency events in the country. They state that data on medical needs, population vulnerabilities, physical and medical infrastructure, human mobility, and environmental conditions have become available in near-real time, and that sophisticated analytic methods for combining them meaningfully are being developed and are rapidly evolving. Despite this, the translation of these data and methods into improved disaster response faces substantial challenges, namely in regards to accessibility, the implementation of policies based on the data, and the integration of them into regular disaster response operations.

The authors of the paper outline solutions to these problems, and propose a mandate to ensure these data pipelines are to be sustained and integrated into routine disaster response.


  • Caroline Buckee, Harvard T.H. Chan School of Public Health
  • Satchit Balsari, Harvard T.H. Chan School of Public Health; Harvard Medical School
  • Mathew Kiang, Stanford University School of Medicine

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