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Designing effective emergency response management (ERM) systems to respond to incidents such as road accidents is a major problem faced by communities. In addition to responding to frequent incidents each day (about 240 million emergency medical services calls and over 5 million road accidents in the US each year), these systems also support response during natural hazards. Recently, there has been a consistent interest in building decision support and optimization tools that can help emergency responders provide more efficient and effective response. This includes a number of principled subsystems that implement early incident detection, incident likelihood forecasting and strategic resource allocation and dispatch policies. In this paper, we highlight the key challenges and provide an overview of the approach developed by our team in collaboration with our community partners.
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This content will become publicly available on March 1, 2026
Is Liberalism a Defensible Framework for Pandemic Policymaking?
Liberal commitments to upholding civil liberties and relying on representative democratic procedures may seem incompatible with an effective response to an emergency like a pandemic. At the same time, the high stakes of pandemic policy-making and disagreement about the best way to respond arguably highlight the importance of other liberal commitments—for example, commitments to incorporating experts, data, and scientific knowledge, and to deliberatively engaging with divergent views about policy. Is the streamlined decision-making that enables an effective emergency response consistent with upholding these liberal commitments? An examination of that question in the context of the COVID-19 pandemic response suggests that a streamlined policymaking process in which states are given pandemic response power can be consistent with upholding these commitments.
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- Award ID(s):
- 2122574
- PAR ID:
- 10611975
- Publisher / Repository:
- Johns Hopkins University Press
- Date Published:
- Journal Name:
- Social Research: An International Quarterly
- Volume:
- 92
- Issue:
- 1
- ISSN:
- 1944-768X
- Page Range / eLocation ID:
- 9 to 34
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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