CAREER: Estimating and Addressing Disaster Survivors’ Unmet Needs: A Social Vulnerability and Social Infrastructure Approach

Duration: 2020–2025

Funding Agency: National Science Foundation (#1944329)

Funding Amount: $534,985 plus $16,000 Research Experience for Undergraduate Supplement

PI: Michelle Meyer

Co PIs: n/a

Postdoc: Carlee Purdum

Graduate Research Assistants: Mason Alexander-Hawk, Joy Semien, Haley Yelle

Undergraduate Research Assistants: Jordan Vick (2021), Asad Abbas (2021), Saul Romero (2021), Adrian Rodriguez (2021), Haley Yelle (2020–2021)


This Faculty Early Career Development (CAREER) grant will further the understanding of how communities can effectively leverage philanthropic resources to meet housing-recovery needs after disasters. As disaster costs and disaster displacement increase, governmental assistance to individuals and private insurance often are inadequate to ensure full recovery for all affected people. Philanthropic resources can address unmet needs of disaster survivors if used effectively and efficiently. Locally led nonprofit “long-term recovery groups” are often charged with distributing these resources, but little is known about these organizations’ efforts or what makes their operations more or less effective in promoting community recovery and resilience. This project will assess how philanthropic housing-recovery practices affect individual unmet needs, post-disaster equity, and the overarching philanthropic ecosystem of affected communities. This project will use the research results to inform and test a training program for locally based nonprofits, government officials, and foundations that will improve their effectiveness in managing philanthropic resources for disaster recovery. Educational outcomes also include undergraduate research experiences to foster under-represented student engagement in STEM and graduate student internships coordinated with disaster recovery nonprofits to further their data management skills.

This project builds on past research into nonprofit operations and housing recovery, introducing a new approach that integrates both. Recent research indicates that governmental aid processes correlate with increased economic and racial inequality after disasters. At the same time, social “infrastructure”, like local nonprofits and especially long-term recovery groups, provide recovery support to socially vulnerable populations who often have difficulty accessing governmental disaster aid. Yet, philanthropic response to disaster is understudied. This is the first attempt to quantify long-term recovery groups’ effectiveness and to identify the factors that increase their effectiveness in supporting housing recovery across the United States. The project work will include the development and analysis of a new dataset of nonprofit disaster recovery operations using secondary and primary data from recent disasters. While focused on long-term recovery groups, the findings from this work will have implications for non-disaster situations. The project will increase understanding of how practices undertaken in disaster situations can be institutionalized into organizations, thus addressing how sudden change in mission and capacity affects organizational operations. The research findings will also point to how disaster resilience can be integrated into daily operations of all types of nonprofits and how resilience affects their overarching operation and mission. Further, this work will evaluate the effects of philanthropic response to disasters on a community’s broader philanthropic safety net.

Health Risks and Hazard Perception from Airborne Toxic Metals to Vulnerable Populations Neighboring the Houston Ship Channel

Duration: 2020–2022

Funding Agency: TiCER Pilot Project competition for 2020

Funding Amount: $68,540

PI: Shankararaman Chellam

Co PIs: Deidra Davis, Natalie Johnson, Itza Mendoza-Sanchez


Air pollution is currently the biggest environmental health risk in the world, responsible for about 11% of annual mortality. Ambient particulate matter (PM) is estimated to cause about 3 million deaths per year worldwide and 5–10% of total annual premature mortality in the United States. Paradoxically, even to date, the PM components most harmful to human health have not been conclusively identified, although current evidence points to metals as a leading contributor. For this reason, we propose to rigorously and systematically investigate outdoor PM, its metallic composition, respiratory risk, and associated toxicity mechanisms. We target the Houston Ship Channel given the Principal Investigator’s extensive prior work in this region identifying and quantitatively apportioning myriad anthropogenic PM sources therein. His previously established size segregated metals datasets will be used to estimate respiratory risk facing residents of this heavily industrialized area. An important contribution of our work is that we will “close the loop” by directly disseminating our findings to one of the impacted communities, i.e., members of Furr High School with whom we have already established strong relationships. This knowledge will equip them with the tools needed towards improving their own environment and reducing personal exposure. In addition to quantifying and communicating exposure to particulate metals, a critical facet of our research is to also pursue underlying inhalation toxicity and cellular mechanisms via in vitro testing. Toxicity screening will be performed using primary human pediatric epithelial cells. Hence, our proposed work combines an integrative approach to air pollution and health; analytical chemistry, epidemiology (including risk assessment), toxicological mechanisms, and risk communication. Our overarching goal for this pilot project is to lay the foundation for a strong NIEHS proposal for 2021 submission. Considering the established track-record of the PI in PM sampling and trace element analysis via mass spectrometry, we focus on other tasks to generate innovative preliminary data for our forthcoming proposal. Hence, research will be on quantifying impacts of inhalation exposure on Houstonians’ health, capturing the affected community’s awareness level of air quality and their perceived health risks, and developing an in vitro testing strategy to evaluate children’s unique susceptibility to respiratory effects arising from respiratory intake of particulate metals. Because of budget limitations, in lieu of collecting more PM samples during this pilot study, internet-enabled low-cost but accurate PM monitors will be installed in the high school so that students can directly assess industrial emissions in real-time. This will form the basis of their class projects, assist in their role as environmental ambassadors, and serve as a community engagement connection. To fulfill the project’s goals, a team of early-, mid-, and late-career faculty from three different schools within Texas A&M (Engineering, Public Health, and Architecture) with expertise in size-resolved aerosol sampling, metals characterization, risk assessment, inhalation and developmental toxicology, community engagement, and environmental justice has been assembled to successfully complete the proposed work.

The Effect of Federal Recovery Funds on Mitigation Behavior

Duration: 2019–2020

Funding Agency: Natural Hazards Center

Funding Amount: $2,000

PI: Maria Watson

Co PIs: Siyu Yu


Moving businesses and residents out of hazardous areas is an important mitigation priority. At the same time, disaster recovery spending is increasing as the frequency and nature of hazards intensifies. Research has suggested that disaster assistance, given its focus on infrastructure replacement, may encourage development in the same hazardous area or prevent recipients from moving through additional debt. This study examines residential and business movement in Galveston County after 2008 Hurricane Ike and 2017 Hurricane Harvey for recipients of post-disaster loans. Through a mixed-methods research design using quantitative data from local and federal agencies, surveys, as well as semi-structured interviews, this study asks whether these loans encourage or discourage residential or business movement out of hazardous areas as well as the factors influencing their location decisions. The result of this work and deeper knowledge on how recovery funding influences adaptive behavior can inform more effective approaches as practitioners reevaluate how federal assistance may conflict with local initiatives.

Center for Risk-Based Community Resilience Planning: A NIST-Funded Center of Excellence

Duration: 2015–2025

Funding Agency: National Institute of Standards and Technology (NIST)

Funding Amount: $20,000,000

PI: John van der Lindt (Colorado State University)

Co PIs: Includes 90 researchers across 12 universities. The HRRC team is Walter Gillis Peacock, Shannon Van Zandt, Nathanael Rosenheim, Maria Koliu, Maria Watson, Michelle Meyer

Graduate Students: Kijin Seong, Wayne Day, Michelle Stanley, Donghwan Gu


Working with NIST researchers and partners from 12 universities led by Colorado State University, the Community Resilience Center of Excellence, awarded in February 2015, will accelerate the development of system-level models and associated databases to support community resilience decision making. The center’s multi-disciplinary team includes experts in engineering, economics, data and computing, and social sciences. Research will support development of metrics and tools that will help local governments decide how to best invest resources intended to lessen the impact of hazards on buildings and infrastructure systems and how to recover rapidly and minimize community disruption.

The centerpiece of the center’s effort is IN-CORE — the Interdependent Networked-Community Resilience Modeling Environment. Built on an open-source platform, the computer model and associated software and databases will incorporate a risk-based approach to decision-making that will enable quantitative comparisons of alternative resilience strategies.

IN-CORE will provide the scientific basis for developing resilience metrics and decision tools to support community resilience of the built environment. The research will include evaluating cascading effects among interconnected infrastructure. In addition, models and tools will integrate social systems vital to the functioning and recovery of communities — health care delivery, education, social services, financial institutions and others.

The center’s multi-disciplinary team includes experts in engineering, economics, data and computing, and social sciences from Colorado State University, University of Illinois at Champaign Urbana, University of Oklahoma, Rice University, Oregon State University, Texas A&M University, University of South Alabama, University of Colorado Boulder, California Polytechnic at Pomona, University of Washington, University of Kansas and Iowa State University.

RAPID: Disparities in Business and Nonprofit Impact and Recovery from Hurricane Harvey, COVID-19, and Hurricane Laura

Duration: 2020–2021

Funding Agency: National Science Foundation (#2053985)

Funding Amount: $53,832

PI: Maria Watson

Co PIs: Rebekka Duddensing, Michelle Meyer

Graduate Research Assistant: Joy Semien


Reducing the effects of disasters on businesses and nonprofits is growing in importance as disasters are more frequent. However, understanding of disaster impacts and recovery across a variety of organizational types is still relatively limited. For example, while disparities in recovery for organizations owned by women, veterans, or racial minorities have been observed, the underlying mechanisms are not well established. In addition, understanding of how businesses and nonprofits recover from multiple and cascading impacts (such as hurricanes followed by a pandemic followed by another hurricane) is also only beginning to develop. This Rapid Response Research (RAPID) project extends preliminary research conducted following Hurricane Harvey to examine disaster impacts, including cumulative impacts, and disparate recovery processes associated with the current pandemic and additional coastal storms along the Gulf Coast. Findings will have implications for improved strategies for organizational survival and recovery, provide evidence that can be used for coordinated outreach and educational programs to support organizational planning and adaptation, and enable cross-case research.

This study integrates theory and findings from the disaster recovery literature with a social vulnerability perspective. The research team will geographically and conceptually expand beyond previous surveys and interviews of for-profit and nonprofit organizations after Hurricane Harvey, collecting data on organizational performance during COVID-19 and Hurricane Laura in Beaumont, TX, Port Arthur, TX, and Lake Charles, LA. The study will test how social vulnerability factors affect organizational impacts, survival, and recovery, controlling for resources, organizational characteristics, damage, and adaptive actions. It will also examine how disparities in organizational recovery propagate through multiple events, controlling for resources, organizational characteristics, damage, and adaptive actions. The team is uniquely poised to collect data quickly as it has conducted pre-disaster survey and sample verification in Beaumont and Port Arthur, tested survey methodology and best practices for this region, and has administered a previous multi-hazard survey that can be tailored for this context. This research team will work to gather data quickly in order to minimize survivor bias (i.e., before some of the vulnerable organizations fail and therefore are not represented in the study sample). Results will be relevant to the literature on cumulative disaster impacts and adaptation, social vulnerability, and organizational continuity.

Understanding Repeat Disruption to Small, Minority-Owned, and Rural Businesses with Applications to Economic Diversification and Organizational Resilience in the Gulf Coast

Duration: 2021–2022

Funding Agency: National Oceanic and Atmospheric Administration

Funding Amount: $84,967

PI: Maria Watson

Co PIs: Michelle Meyer, Rebekka Dudensing, Joy Semien


The 2020 hurricane season was the most active on record and organizations on the Gulf Coast struggled against the backdrop of the pandemic and incomplete recoveries from previous climate events. Although many communities are facing compounding, concurrent, and recurring disasters, there is limited research on how these complex events impact organizations across different ownership characteristics and geographical contexts. Previous research conducted by this team in the region uncovered disparities in recovery after Hurricane Harvey along owner/manager racial lines; the proposed study will build upon and expand this work both geographically and theoretically. It focuses on several intersectional dimensions of organizational disruption and resilience: the contextual environment of the business and nonprofit in terms of rural/small town versus urban, the socio-economic vulnerability of the organization’s market and service area, and the socio-economic characteristics of the organization’s ownership and management, itself. Using findings from this research and working with our partners at The Southern Climate Impacts Planning Program (SCIPP), Texas SeaGrant, Texas A&M University Agrilife Extension, and the Hazard Reduction & Recovery Center at Texas A&M University, we will prepare and evaluate outreach materials on best practices for small business and nonprofits at the individual business and nonprofit, regional, and programmatic level. Organizations will then apply their knowledge in workshop events where they will develop recovery and continuity plans. The hope is that this research will increase organizationally resilience locally but also provide a research framework that can be more broadly generalized.

Understanding the Response to USDA Food Aid among Minority Residents and Farmers in COVID-19

Duration: 2021

Funding Agency: PRISE: Texas A&M and Prairie View A&M

Funding Amount: $30,000

PI: Noel Estwick (Prairie View A&M)

Co PIs: Rebekka Dudensing, Michelle Meyer

Undergraduate Students: Daniela Wong, Noelia Rosas, Sarah Judkins


The COVID-19 pandemic caused a tremendous strain on America’s food supply chain. In addition to food injustices, families that struggled to put food on the table pre-pandemic continue to struggle financially and cannot afford to buy food. This research seeks to understand impacts of USDA’s Farmers to Families Food Box program in limited-resource communities in 8 Texas counties. The faculty, extension personnel, student researchers and community consultant team will work with Mayors, faith-based organizations and other stakeholders to answer the overarching research question “How are the individual

counties carrying out their Farmers to Families Food Box Programs?” The objectives are to: 1) Compare and contrast the Farmers to Families Food Box program in select counties especially variation in urban and rural contexts; 2) Assess limited-resource residents’ experience and perception of the program; and 3) Examine limited-resource producers’ perspectives of the program.

The Effect of Federal Recovery Funds on Mitigation Behavior

Duration: 2019–2020

Funding Agency: Natural Hazards Center

Funding Amount: $2,000

PI: Maria Watson

Co PIs: Siyu Yu


Moving businesses and residents out of hazardous areas is an important mitigation priority. At the same time, disaster recovery spending is increasing as the frequency and nature of hazards intensifies. Research has suggested that disaster assistance, given its focus on infrastructure replacement, may encourage development in the same hazardous area or prevent recipients from moving through additional debt. This study examines residential and business movement in Galveston County after 2008 Hurricane Ike and 2017 Hurricane Harvey for recipients of post-disaster loans. Through a mixed-methods research design using quantitative data from local and federal agencies, surveys, as well as semi-structured interviews, this study asks whether these loans encourage or discourage residential or business movement out of hazardous areas as well as the factors influencing their location decisions. The result of this work and deeper knowledge on how recovery funding influences adaptive behavior can inform more effective approaches as practitioners reevaluate how federal assistance may conflict with local initiatives.

Transference Vulnerability: Linking Social, Health and Built Environment Data with Covid-19 Exposure

Duration: 2020–2022

Funding Agency: T3: Texas A&M Triads for Transformation (Project ID: 1819)

Funding Amount: $30,000 plus $2,000 Research Experience for Undergraduate Support

PI: Siyu Yu

Co PIs: Gang Han, Andrea Roberts


With the spread of COVID-19, highly socially vulnerable communities (which typically live in denser areas and have less access to health care and open space) are facing compounded threats. To fully understand the COVID-19 impact on socially vulnerable populations, this study integrates community vulnerability assessments, public health condition evaluations, population density assessments, and land use pattern data to identify and map spatial hotspots of transference vulnerability – the probability of populations to transfer viruses/diseases during a global outbreak. Using Harris County, TX as a case site, we will assess relationships between COVID-19 morbidity and mortality rates with social, public health, and built environment factors to rank transference vulnerability by neighborhood and create an interactive visualized online platform to display the findings and related analytics.


Community Resilience to Technological Disasters: An Analysis of Risks, Preparedness, and Mitigation

Duration: 2019–2022

Funding Agency: T3: Texas A&M Triads for Transformation (Project ID: 1450)

Funding Amount: $30,000

PI: Lei Zou

Co PIs: Qingsheng Wang, Michelle Meyer


Community resilience is the community’s ability to prepare for, respond to, recover from, and more successfully adapt to catastrophic events. It is an urgent societal challenge that captures academics and decision-makers’ attention from various fields and sectors.

Technological disasters are catastrophic events caused by either human failure in controlling technology or malfunction of engineering systems, such as structural collapses (e.g., bridges and oil refinery) and industrial accidents (e.g., storage tank fires and chemical explosions). Technology-based disasters are as severe as natural disasters and sometimes could be triggered by natural disasters. However, most of the previous investigations of disaster resilience focused on natural hazards. Less than 3% of them aim to evaluate and improve community resilience to technological catastrophes.

In this research, we will develop a framework to measure and improve community resilience to technological disasters. Using the City of Houston as an example, we aim to answer three research questions:

1. What are the risks and impacts of technological disasters in the Houston area?

2. Which communities are more resilient to technological disasters in the Houston area?

3. How to improve public awareness, preparedness, and resilience of technological disasters?

The developed framework will shed light on measuring and improving community resilience to technological disasters across the nation. Results from this research will inform the Houston government and residents on preparedness and mitigation strategies for technological disasters.

Collaborative Research: Organizational development, operations, and new media among civilian flood-rescue groups

Duration: 2019–2022

Funding Agency: National Science Foundation (#1851493)

Funding Amount: $320,431 (TAMU portion $95,842 plus $19,055 Research Experience for Undergraduate Supplement)

PI: Michelle Meyer

Co PIs: Brant Mitchell (LSU), Stuart Nolan (LSU)

Postdoc: Carlee Purdum

Graduate Research Assistants: Kyle Breen (LSU), Romel Fernandez (2020–2021), Arthur Chambers (2020)

Undergraduate Research Assistants: Jackson Pierce (2019–2020), Nathan Young (2019–2021), Sofia Sierra (2020–2021), Adrian Rodriguez (2021), Tyler Eutsler (2021), Abigail Bowers (LSU, 2020–2021), Noah Balbon (LSU, 2021)


In this project, the stability or formalization and growth of volunteer groups and the use of social media in these processes will be investigated. Specifically, processes of conducting volunteer flood rescues, factors that affect immediate decision-making during rescues, decisions about volunteer group development, and use of social media for rescuing and group development will be researched through intense interviewing and participation with rescuers. Disasters are unique opportunities to study social processes, and they are also becoming more frequent social problems. Disasters of recent years have introduced volunteer organizations supported by social media and new technologies. Limited scholarly research has studied this volunteer rescue movement, these volunteers, or these rescue operations. Findings will contribute to scholarly understanding of group formation and development and how this may be affected by new technologies. They also will contribute to public welfare by being integrated in courses such as on emergency management and hazard mitigation and recovery, and by being directly shared with organizations that do rescues as well as the broader emergency management and public communities.
To address the research goal, ethnographic research will be conducted that includes participation with volunteer organizations that conduct rescues, 20–40 interviews with emergency management officials, 30–60 interviews with volunteer rescuers, and 20–30 interviews with persons rescued by civilian volunteers. Over the life of the project, this will involve training and traveling with volunteer organizations as they respond to disasters, such as the three to which these organizations responded in 2018, Hurricanes Florence and Michael and floods in Southeast Texas. Participation will be in three different roles: boat rescuer, dispatcher, and leadership coordination. In addition, available social media data and media articles will be collected and analyzed inductively. GIS technology will be used to analyze available geospatial data on rescue locations, which will be related to hazard data.

Reducing the Human Impacts of Flash Floods: Development of Microdata and Causal Model to Inform Mitigation and Preparedness

Duration: 2019–2022

Funding Agency: National Science Foundation (#1931301)

Funding Amount: $350,000

PI: Nasir Gharaibeh

Co PIs: Francisco Olivera, Lei Zou, Michelle Meyer, Garett Sansom


Flash floods hit with little lead time to warn the public and are of such velocity and force so as to make them one of the most lethal natural hazards (measured by the ratio of fatalities to people affected). The purpose of this project is to better understand why unsafe conditions exist during flash flood events, and how to reduce or eliminate these conditions. The premise is that problems are best solved by correcting their root causes, rather than reacting to their symptoms. Given the locality of flash floods, this approach to disaster research requires finer resolution data than currently exists, a gap this project fills. Such data are needed to understand the complete circumstances leading up to fatalities and injuries and to design effective structural and non-structural risk reduction measures. The new data and model principles created by this project can be used to identify effective structural and non-structural interventions for inclusion in hazard mitigation plans, emergency response plans, and capital improvement plans. This research will advance the scholarly momentum of an interdisciplinary team of investigators from civil engineering, geography, public health, and sociology to improve public safety and community resilience to flash flooding. Hence, the project supports NSF’s mission to promote the progress of science and to advance the nation’s health, prosperity, and welfare by reducing future fatalities from flash flooding.

The goal of this research is to enhance public safety by creating the data and framework for modeling the causal pathways of flash flood fatalities and injuries to inform prevention. The research questions that guide the design of this study are: (1) What are the causal pathways to flash flood fatalities and injuries? and (2) How are communities in susceptible areas preparing for and mitigating against flash floods? The project uses a mixture of data types and research methods to address these questions. Using innovative web technologies, new fine-scale data will be obtained from structured and unstructured data sources on the web on each flash flood event and victim from the past 10 years. The new data will be made available in the public domain, while protecting the anonymity of individual persons and adhering to the terms of data usage set by the original sources.

A Hybrid Decision Support System for Driving Resiliency in Texas Coastal Communities

Duration: 2019–2022

Funding Agency: Texas Sea Grant

Funding Amount: $200,000

PI: Amir Behzadan

Co PIs: Courtney Thompson, Zhe Zhang

Senior Personnel: Michelle Meyer

Graduate Students: Bahareh Alizadeh Kharazi, Diya Li, Julia Hillin

Undergraduate Students: Nathan Young (2020)


Existing flood models do not fully consider expanding development in flood-prone regions, rapid rain accumulation, construction methods and materials, climate change, or population growth. The underlying process of creating these maps is heavily centralized (i.e., authority-oriented) and disproportionately influenced to benefit wealthier, more privileged communities. A 2017 report by the Department of Homeland Security’s Office of Inspector General found that only 42% of the total flood map miles in FEMA’s inventory were updated and valid. A major limiting factor in covering neighborhoods and communities using the current flood sensing capabilities is the high cost of sensor acquisition, installation, maintenance, and a lack of skilled operators.

Our work in a Texas Sea Grant-funded project will augment flood management practices in Texas coastal communities through citizen science, artificial intelligence (AI), Spatial Decision Science, and advanced cyberinfrastructure for building resilience communities. Part of this project includes a survey component that asks respondents to 1) share their experiences with flooding and rescue operations in the past;  and 2) what types of information would have helped them while making evacuation decisions. Through integrating the findings of this survey into technology development, our long-term goal is to design a user-inspired flood risk mapping tool for coastal communities.

CRISP Type 2/Collaborative Research: Scalable Decision Model to Achieve Local and Regional Resilience of Interdependent Critical Infrastructure Systems and Communities

Duration: 2016–2022

Funding Agency: National Science Foundation (#1638273)

Funding Amount: $2,499,999 (TAMU portion $706,873)

PI: Walter Gillis Peacock

Co PIs: Nathanael Rosenheim, Daniel Goldberg, Jamie Kruse (ECU), Bruce Ellington (CSU), Edwon Chong (CSU), John van der Lindt (CSU), Paulo Gardoni (U of I), Santanu Chaudhuri (U of I), Seyedarmin Tabandeh (U of I)


The US economy and social well-being depend on interdependent critical infrastructure systems (ICISs) such as transportation, energy, water, and food systems. These ICISs shape the country’s ability to meet community needs often successful, but not for all, and are susceptible to disruptions due to extreme natural events. This interplay between normal operation, chronic issues, and disaster-induced challenges is clearly evident when considering food security issues. Food access and affordability are persistent problems for more than 14 percent of Americans in normal times and are greatly exacerbated following disasters. Frameworks for understanding ICIS interdependencies, their interface with social and economic networks in response to natural hazards, and their roles in disaster recovery for vulnerable populations and food security are nascent. The food security of a community is a function of the pre-event vulnerabilities and the resilience of its food distribution network including the vulnerabilities of its infrastructural systems in isolation and their interdependencies. Furthermore, the demands posed by different hazards, the capacity of each physical network and system to respond to these demands, and the interactions between physical and social systems are highly uncertain. Accordingly, risk-informed approaches that can guide decision methods are crucial to characterize demand and impact on a community, to predict community response, and for designing community infrastructure systems that are resilient. Well-integrated decision methods that account for and integrate the performance of different ICISs in response to disasters have broad impacts. First, such methodologies will better frame questions on disaster mitigation and recovery, and will facilitate disaster planning activities and training for various disaster scenarios. Second, they will encourage policies that address chronic and acute food-security issues, balancing the mitigation of vulnerability with the promotion of resiliency. Finally, they will foster a shared language among social, behavioral, and economic (SBE) scientists, computational scientists, and engineers on the causes and characterization of hazards and risks and mitigation solutions. This project will engage a diverse set of students, including women and minorities, and in student-centered learning. It will integrate research and education throughout the project, and effectively disseminate the results. The methodologies developed will be integrated into courses such as Engineering Risk Analysis and Structural Reliability, Disaster Mitigation and Recovery and Planning Methods, and Risk and Regulation and into two NSF Research Experience for Undergraduate (REU) summer institutes which blend geography, computer science, health, planning and social science undergraduate students in food security, disparities, and health research projects.

This research will develop a decision platform that integrates computational models of ICISs at different spatial and temporal scales. These computational models will focus on the food distribution networks and include analytics of the socioeconomic causes of vulnerability. The decision platform may be used to examine issues related to reducing the risks associated with extreme hazards while enhancing community resilience with respect to food security. The project brings together three distinct disciplines: Engineering, SBE sciences, and Computer/Computational Sciences. Achieving project goals requires a deep collaboration between these three broad disciplines. Engineering is needed to understand and model the physical components of each sector and their interdependencies. SBE sciences are essential to understand and model food distribution from wholesale to households with a focus on vulnerable populations. Computer and Computational Science are needed to develop comprehensive models representing communities and their infrastructure and are the basis for assessing policy and organizational interventions that lead to greater robustness and resilience. The interdisciplinary nature of this research will also forge new channels of communication through models that integrate social and physical aspects of risk and vulnerability.