Information Collection/Data Governance

How do we develop policies and practices for better epidemiological data collection and for sharing data with the appropriate authorities?

Conference Participate

Slow and inaccurate collection and dissemination of epidemiological data reduces efficiency in the prevention and control of outbreaks. The goal of this session is to identify innovative and effective methods to collect reliable epidemiological data from institutions and individuals and make it available. We are looking for concrete and specific examples of responsible and effective public health data sharing practices.


The problems have been fleshed out into a briefing designed to describe the root causes of the problem, current approaches in different countries, and lessons learned from other domains.

Read the Problem Description


Mobile tech–assisted surveillance

Improve the speed and reliability of surveillance data by integrating flexible mobile technologies like SMS and smartphone app reporting into surveillance activities

Resources: Moderate Investment ($100k-$500k)
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Resource Offset: mHealth technologies, including participatory digital surveillance and mobile-assisted case reporting, have the potential to expand surveillance at low cost compared to traditional methods. Investments in mobile devices and human resources can be offset by broad integration with other government activities like disaster response


Gordon Cressman, RTI International, John Brownstein, Healthmap, Harvard Medical School, Brian Lee, U.S. Centers for Disease Control Health Information Innovation Consortium

Form disease surveillance data collaborative

Collaborate with companies and universities to identify new sources of disease surveillance data

Resources: Some Investment ($10k-$100k)
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Resource Offset: Data collaboratives are, by definition, corporate data philanthropy


Richard Benjamins, Director of External Positioning & Big Data for Social Good, LUCA: Data-Driven Decisions (Telefonica), Stefaan Verhulst, GovLab

Develop data-sharing playbook

Promote openness and participation in surveillance data collection, storage, sharing, and use by developing a data governance playbook for epidemic response and building broad commitment to use it

Resources: Moderate Investment ($100k-$500k)
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Resource Offset: More open and participatory surveillance data can generate cost savings through faster and more accurate epidemic detection and modeling. In addition, insights generated from data sharing can lead to more efficient use of public health resources


Michael Johansson, U.S Centers for Disease Control