Data-Driven Solutions for Sustainable Emergency Preparedness and Response

Dear Colleagues,

This Special Issue addresses the essential role played by data-driven approaches in strengthening resilience and sustainability within communities and nations. In an era where both natural and human-made crises are increasingly complex, sustainable emergency preparedness is critical for immediate response and supporting long-term social stability and resilience. This Special Issue studies using data science, artificial intelligence, predictive modelling, and advanced computing to enhance emergency planning, response, and recovery. It emphasizes integrating project management, computer science, and logistics to create robust systems capable of adapting to diverse emergency scenarios, thereby supporting sustainability at multiple levels: governmental, organizational, and community.

This Special Issue’s scope covers diverse data analytics applications, ranging from early risk assessment and real-time resource allocation to optimizing emergency logistics. By examining the roles played by these computational tools in fostering sustainable responses, this Special Issue encourages contributions from multiple disciplines. Researchers from project management, computer science, and logistics are invited to explore how their fields contribute to resilient emergency management systems. Our primary aim is to compile practical, adaptable, and scalable data-driven methods that support emergency preparedness and responses in ways that reduce long-term societal disruption.

This Special Issue advances existing research in emergency management by highlighting sustainability as a primary outcome of data-driven approaches. Current studies often examine the technical applications of data science in emergencies or address sustainable development independently. However, fewer studies consider how computational tools can simultaneously support immediate response needs and long-term resilience objectives. By merging insights from data science, project management, and logistics, this Special Issue addresses a significant research gap: the need for integrated, sustainable, and adaptive approaches to enhance community resilience and emergency preparedness. The Special Issue will advance the field through this interdisciplinary focus by encouraging the creation of new models, frameworks, and policies that connect sustainable development goals with effective emergency response strategies. It will also inspire further research and practice, fostering a more resilient global society equipped to face emerging challenges.

Suggest themes:

• Machine Learning for Predictive Emergency and Humanitarian Logistics;
• AI, LaaS and Physical Internet Integration for Resilient Supply Chains;
• Data Science for Predictive Analysis and Early Warning Systems in Crisis Management;
• Machine Learning Models for Anticipating Supply Chain and Transport Disruptions;
• Accessibility of Emergency Infrastructure for Disaster and Human-made Crisis Preparedness;
• Artificial Intelligence in Emergency Preparedness;
• Predictive Analytics for Resource Allocation;
• Digital Twins for Emergencies;
• IoT for Emergency Response;
• Data-Driven Post-Disaster Recovery;
• Blockchain in Resource Management;
• Multi-Criteria Decision Analysis for Resilience;
• AI-Based Decision Support;
• Sustainable Emergency Supply Chains;
• Geospatial Data for Disaster Preparedness;
• Project Management in Emergency Response;
• Data-Driven Public Health Emergency Preparedness;
• Epidemiological Modelling for Crisis Response;
• Health Systems Resilience in Emergencies;
• Public Health Data for Predicting Disease Outbreaks;
• Resource Reallocation for Optimized Crisis Response;
• Human Resource Management in Emergency Situations;
• Agile Human Resource Strategies in Crises.

We look forward to receiving your contributions.

Dr. Andrii Galkin
Prof. Dr. Igor Chumachenko
Prof. Dr. Sergiy Bushuyev
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• sustainable emergency preparedness
• resilience
• emergency management
• logistics
• project management
• logistics
• risk assessment
• response planning
• resource reallocation
• artificial intelligence