Supporting Post-disaster Recovery with Agent-based Modeling in Multilayer Socio-physical Networks

The examination of post-disaster recovery (PDR) in a socio-physical system enables us to elucidate the complex relationships between humans and infrastructures. Although existing studies have identified many patterns in the PDR process, they fall short of describing how individual recoveries contribute to the overall recovery of the system. To enhance the understanding of individual return behavior and the recovery of point-of-interests (POIs), we propose an agent-based model (ABM), called PostDisasterSim. We apply the model to analyze the recovery of five counties in Texas following Hurricane Harvey in 2017. Specifically, we construct a three-layer network comprising the human layer, the social infrastructure layer, and the physical infrastructure layer, using mobile phone location data and POI data. Based on prior studies and a household survey, we develop the ABM to simulate how evacuated individuals return to their homes, and social and physical infrastructures recover. By implementing the ABM, we unveil the heterogeneity in recovery dynamics in terms of agent types, housing types, household income levels, and geographical locations. Moreover, simulation results across nine scenarios quantitatively demonstrate the positive effects of social and physical infrastructure improvement plans. This study can assist disaster scientists in uncovering nuanced recovery patterns and policymakers in translating policies like resource allocation into practice.Comment: 28 pages, 10 figure

An interdisciplinary system dynamics model for post-disaster housing recovery

Many previous disasters have demonstrated the need for extensive personal, public, and governmental expenditures for housing recovery highlighting the importance of studying housing recovery. Yet, much research is still needed to fully understand the multi-faceted and complex nature of housing recovery. The goal of this paper is to present a holistic model to further the understanding of the dynamic processes and interdependencies of housing recovery. The impetus for this work is that inequalities in housing recovery could be addressed more effectively if we better understood interconnected factors and dynamic processes that slow down recovery for some. Currently, there is a lack of understanding about such factors and processes. Literature from engineering and social sciences was reviewed to develop an integrated system dynamics model for post-disaster housing recovery. While it is beyond current capabilities to quantify such complexities, the presented model takes a major stride toward articulating the complex phenomenon that is housing recovery

Holistic Resilience Quantification Framework of Rural Communities

Communities need to prepare for anticipated hazards, adapt to varying conditions, and resist and recover rapidly from disturbances. Protecting the built environment from natural and man-made hazards and understanding the impact of these hazards helps allocate resources efficiently. Recently, an indicator-based and time-dependent approach was developed for defining and measuring the functionality and disaster resilience continuously at the community level. This computational method uses seven dimensions that find qualitative characteristics and transforms them into quantitative measures. The proposed framework is used to study the resilience of rural communities’ subject to severe flooding events. Harlan County in the Appalachian region is chosen as a case study to evaluate the proposed resilience quantification framework subject to severe flooding. The results show the validity of the proposed approach as a decision-support mechanism to assess and enhance the resilience of rural communities

Density and disasters: economics of urban hazard risk

Today, 370 million people live in cities in earthquake prone areas and 310 million in cities with high probability of tropical cyclones. By 2050, these numbers are likely to more than double. Mortality risk therefore is highly concentrated in many of the world’s cities and economic risk even more so. This paper discusses what sets hazard risk in urban areas apart, provides estimates of valuation of hazard risk, and discusses implications for individual mitigation and public policy. The main conclusions are that urban agglomeration economies change the cost-benefit calculation of hazard mitigation, that good hazard management is first and foremost good general urban management, and that the public sector must perform better in generating and disseminating credible information on hazard risk in cities.Banks&Banking Reform,Environmental Economics&Policies,Hazard Risk Management,Urban Housing,Labor Policies

Resilience of healthcare and education networks and their interactions following major earthquakes

2021 Spring.Includes bibliographical references.Healthcare and education systems have been identified by various national and international organizations as the main pillars of communities' stability. Ensuring the continuation of vital community services such as healthcare and education is critical for minimizing social losses after extreme events. A shortage of healthcare services could have catastrophic short-term and long-term effects on a community including an increase in morbidity and mortality, as well as population outmigration. Moreover, a shortage or lack of facilities for K-12 education, including elementary, middle, and high schools could impact a wide range of the community's population and could lead to impact population outmigration. Despite their importance to communities, there are a lack of comprehensive models that can be used to quantify recovery of functionalities of healthcare systems and schools following natural disasters. In addition to capturing the recovery of functionality, understanding the correlation between these main social services institutions is critical to determining the welfare of communities following natural disasters. Although hospitals and schools are key indicators of the stability of community social services, no studies to date have been conducted to determine the level of interdependence between hospitals and schools and their collective influence on their recoveries following extreme events. In this study, comprehensive frameworks are devised for estimating the losses, functionality, and recovery of healthcare and educational services following earthquakes. Success trees and semi-Markov stochastic models coupled with dynamic optimization are used to develop socio-technical models that describe functionalities and restorations of the facilities providing these services, by integrating the physical infrastructure, the supplies, and the people who operate and use these facilities. New frameworks are proposed to simulate processes such as patient demand on hospitals, hospitals' interaction, student enrollment, and school administration as well as different decisions and mitigation strategies applied by hospitals and schools while considering the disturbance imposed by earthquake events on these processes. The complex interaction between healthcare and education networks is captured using a new agent-based model which has been developed in the context of the communities' physical, social, and economic sectors that affect overall recovery. This model is employed to simulate the functional processes within each facility while optimizing their recovery trajectories after earthquake occurrence. The results highlight significant interdependencies between hospitals and schools, including direct and indirect relationships, suggesting the need for collective coupling of their recovery to achieve full functionality of either of the two systems following natural disasters. Recognizing this high level of interdependence, a social services stability index is then established which can be used by policymakers and community leaders to quantify the impact of healthcare and educational services on community resilience and social services stability

Comparative analysis of spring flood risk reduction measures in Alaska, United States and the Sakha Republic, Russia

Thesis (Ph.D.) University of Alaska Fairbanks, 2017River ice thaw and breakup are an annual springtime phenomena in the North. Depending on regional weather patterns and river morphology, breakups can result in catastrophic floods in exposed and vulnerable communities. Breakup flood risk is especially high in rural and remote northern communities, where flood relief and recovery are complicated by unique geographical and climatological features, and limited physical and communication infrastructure. Proactive spring flood management would significantly minimize the adverse impacts of spring floods. Proactive flood management entails flood risk reduction through advances in ice jam and flood prevention, forecasting and mitigation, and community preparedness. With the goal to identify best practices in spring flood risk reduction, I conducted a comparative case study between two flood-prone communities, Galena in Alaska, United States and Edeytsy in the Sakha Republic, Russia. Within a week from each other, Galena and Edeytsy sustained major floods in May 2013. Methods included focus groups with the representatives from flood managing agencies, surveys of families impacted by the 2013 floods, observations on site, and archival review. Comparative parameters of the study included natural and human causes of spring floods, effectiveness of spring flood mitigation and preparedness strategies, and the role of interagency communication and cooperation in flood risk reduction. The analysis revealed that spring flood risk in Galena and Edeytsy results from complex interactions among a series of natural processes and human actions that generate conditions of hazard, exposure, and vulnerability. Therefore, flood risk in Galena and Edeytsy can be reduced by managing conditions of ice-jam floods, and decreasing exposure and vulnerability of the at-risk populations. Implementing the Pressure and Release model to analyze the vulnerability progression of Edeytsy and Galena points to common root causes at the two research sites, including colonial heritage, unequal distribution of resources and power, top-down governance, and limited inclusion of local communities in the decision-making process. To construct an appropriate flood risk reduction framework it is important to establish a dialogue among the diverse stakeholders on potential solutions, arriving at a range of top-down and bottom-up initiatives and in conjunction selecting the appropriate strategies. Both communities have progressed in terms of greater awareness of the hazard, reduction in vulnerabilities, and a shift to more reliance on shelter-in-place. However, in neither community have needed improvements in levee protection been completed. Dialogue between outside authorities and the community begins earlier and is more intensive for Edeytsy, perhaps accounting for Edeytsy's more favorable rating of risk management and response than Galena's