The Mango Model: Best Practices in the Creation of a COVID-19 Open Data Project Through a Partnership with Google Health and the Non-Profit FinMango

ABSTRACT

This article addresses the issue of accessibility related to collecting and publishing Open Data for COVID-19, and suggestions for using the finalized project data in addressing lifestyle behaviors that will inform Health Educators in differing agencies when developing programs for prevention and management of COVID-19. The Mango Model, based on evidence from a COVID-19 Open Data Project was funded by Google Health in partnership with the nonprofit FinMango. First, the purpose and background for the creation of the Open Data Project are provided. Second, outreach to various agencies is addressed. Third, differing methodologies used by agencies for collecting, organizing, automating, and publishing subnational were observed. Fourth, implications for organizations regarding practice, policy and research are discussed. The Google Health and FinMango COVID-19 Open Data Project reinforces the need for a universal standard for publishing open data with consistent reporting. Through the creation of the project, the Mango-Model offers best practices and solutions for universally releasing types of data to assist public health professionals, researchers, policymakers, and others in health-related fields in understanding and managing the virus, and in the mobilization of resources in future responses to local and global need.

Acknowledgments

The authors wish to thank the FinMango volunteers, “Mangoes,” for their effort, and tireless commitment in collecting data. Additionally, the authors thank Google Health for the donation to the non-profit FinMango to assist with the development and creation of this collaborative project.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Google Health [Donation - No Award Number].