Regional policy coordination of pandemic responses using an iterative mobility-driven algorithm

ABSTRACT

The COVID-19 experience has shown that horizontal cooperation of non-pharmaceutical interventions across jurisdictions is crucial to combat pandemics. However, the question of how to construct policy coordination regions has not yet received enough attention. In this study, we develop an iterative mobility-driven community detection algorithm based on the modularity function to identify multilevel public policy coordination regions. As a case study, we use movement of people in the United States to identify regions of interconnected locations at different levels. We argue that pre-emptively designed community structures based on mobility can be more appropriate to meet critical preparedness goals than existing jurisdictions.

KEYWORDS:

• pandemics
• regional policy coordination
• community detection
• mobility
• COVID-19
• spatial dependence

JEL:

• H12
• H75
• I18
• R1

ACKNOWLEDGEMENTS

The authors gratefully acknowledge Camber Systems for making the mobility data available for this study. They also thank three anonymous referees for their constructive feedback and Alka Sapat for her insightful comments on earlier versions of the manuscript.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1. See https://www.covid19mobility.org

2. See https://cambersystems.com

3. See https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data

4. See https://www.floridahealth.gov/provider-and-partner-resources/health-councils/index.html