ArticleTechnological forecasting and social change2021
Managing the COVID-19 emergency: A coordination framework to enhance response practices and actions.
Article in Technological forecasting and social change, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Understanding the layout of emergency scientific research during COVID-19 prevention and control: a comparative analysis of project solicitation and project approval.BMC public health · 2025Article
- The COVID-19 Vaccination Rollout in Tanzania: The Role of Coordination in Its Success.Vaccines · 2025Article
- Developing an index for measuring gender lens investing in organizations: the GLIMETRICS framework.Frontiers in psychology · 2025Article
- Measuring and optimizing the urban community resilience against public health emergencies: a case study in Nanjing, China.Frontiers in public health · 2025Article
- Stakeholders' perspectives on barriers to and facilitators of school-based HPV vaccination in the context of COVID-19 pandemic-related disruption: a qualitative mixed methods study.International journal of qualitative studies on health and well-being · 2024Article
- How Much Dialogic Coordination Practices Matter to Healthcare Professionals-A Delphi Approach towards a Tool for Identification and Measurement.Healthcare (Basel, Switzerland) · 2023Article
- Research Progress and Improvement Ideas of Anti-Epidemic Resilience in China's Urban Communities.International journal of environmental research and public health · 2022Review
- Coordination and Management of COVID-19 in Africa through Health Operations and Technical Expertise Pillar: A Case Study from WHO AFRO One Year into Response.Tropical medicine and infectious disease · 2022Article
- Resilience in emergency management: Learning from COVID-19 in oil and gas platforms.International journal of disaster risk reduction : IJDRR · 2022Article
- Coordination mechanisms for COVID-19 in the WHO Regional office for Africa.BMC health services research · 2022Review
- How policymakers and other leaders can build a more sustainable post-COVID-19 'normal'.Discover sustainability · 2022Article
- Digital knowledge sharing and creative performance: Work from home during the COVID-19 pandemic.Technological forecasting and social change · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The global outbreak of the coronavirus pneumonia (COVID-19) showed how epidemics today can spread very rapidly, with potentially ruinous impact on economies and societies. Whereas medical research is crucial to define effective treatment protocols, technology innovation and social research can contribute by defining effective approaches to emergency management, especially to optimize the complex dynamics arising within actors and systems during the outbreak. The purpose of this article is to define a framework for modeling activities, actors and resources coordination in the epidemic management scenario, and to reflect on its use to enhance response practices and actions. We identify 25 types of resources and 8 activities involved in the management of epidemic, and study 29 "flow", "fit", and "share" dependencies among those resources and activities, along with purposeful management criteria. Next, we use a coordination framework to conceptualize an emergency management system encompassing practices and response actions. This study has the potential to impact a broad audience, and can opens avenues for follow up works at the intersection between technology and innovation management and societal challenges. The outcomes can have immediate applicability to an ongoing societal problem, as well as be generalized for application in future (possible although undesired) events.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.