Dynamic Modelling of Critical Infrastructures for Improved Disaster Habitation Recovery

ABSTRACT Natural disasters damage infrastructure systems that support housing habitability, leading to population displacement. Recovery efforts speed up infrastructure capacity restoration and, thereby, rehabitation by displaced residents. Current recovery policy analysis methods focus on individual infrastructure systems or overall community recovery and are not focused on the impacts of built infrastructures on habitation. Many modelling methodologies are qualitative, do not capture the dynamic nature of infrastructure restoration or use single recovery metrics, thereby limiting their effectiveness for recovery planning. Rigorous modelling and quantification methods are needed to improve policy analysis and design. Using the system dynamics modelling methodology, the current work models and quantifies the impacts of realistic disaster recovery policies on habitation. The model is used to quantify and evaluate the policy effectiveness of selected disaster recovery initiatives derived from the literature in three performance dimensions. Specifically, it quantifies the habitation allowed by multiple community critical infrastructure systems, the scale of habitation loss and recovery duration. Modelled policies include increased resources, ease of access to public funding and accelerated administrative response to reduce process constraints in starting infrastructure repair. Results indicate that improving administrative response decreases habitation loss scale but does not significantly affect recovery duration. However, increasing accessibility to and amounts of public funding reduces the habitation loss scale and shortens recovery duration. The model structure is used to explain these results, which can facilitate improved analysis, identification of high‐leverage points and development of effective and efficient natural disaster recovery strategies.

Authors

Institutions

Publication Details

Journal
Systems Research and Behavioral Science
Published
2025-11-25
DOI
https://doi.org/10.1002/sres.3221
Citations
1
Primary Topic
Disaster Management and Resilience
Type
article
Field-Weighted Citation Impact
4.20

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dynamic Modelling of Critical Infrastructures for Improved Disaster Habitation Recovery

Benjamin C. Ozumba, David N. Ford
1 citations
Systems Research and Behavioral Science
Disaster Management and Resilience
4.20
article

Dynamic Modelling of Critical Infrastructures for Improved Disaster Habitation Recovery

Benjamin C. Ozumba, David N. Ford
article en
1 citations

Abstract

ABSTRACT Natural disasters damage infrastructure systems that support housing habitability, leading to population displacement. Recovery efforts speed up infrastructure capacity restoration and, thereby, rehabitation by displaced residents. Current recovery policy analysis methods focus on individual infrastructure systems or overall community recovery and are not focused on the impacts of built infrastructures on habitation. Many modelling methodologies are qualitative, do not capture the dynamic nature of infrastructure restoration or use single recovery metrics, thereby limiting their effectiveness for recovery planning. Rigorous modelling and quantification methods are needed to improve policy analysis and design. Using the system dynamics modelling methodology, the current work models and quantifies the impacts of realistic disaster recovery policies on habitation. The model is used to quantify and evaluate the policy effectiveness of selected disaster recovery initiatives derived from the literature in three performance dimensions. Specifically, it quantifies the habitation allowed by multiple community critical infrastructure systems, the scale of habitation loss and recovery duration. Modelled policies include increased resources, ease of access to public funding and accelerated administrative response to reduce process constraints in starting infrastructure repair. Results indicate that improving administrative response decreases habitation loss scale but does not significantly affect recovery duration. However, increasing accessibility to and amounts of public funding reduces the habitation loss scale and shortens recovery duration. The model structure is used to explain these results, which can facilitate improved analysis, identification of high‐leverage points and development of effective and efficient natural disaster recovery strategies.

Systems Research and Behavioral Science
Exponent (United States) (US), Virginia Tech (US)
Texas Department of Transportation, U.S. Army, U.S. Army Corps of Engineers
Openalex Percentile: Top 5%
Disaster Management and Resilience
4.20
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.