Research Focus

This interdisciplinary project aims to assess and improve disaster preparedness, climate, and health resilience in affordable housing communities located in coastal areas. Our approach prioritizes support for vulnerable populations disproportionately affected by climate change by integrating public health, housing infrastructure, and urban resilience strategies. We aim to develop a community-engaged, comprehensive toolkit by adapting the CDC’s Building Resilience Against Climate Effects (BRACE) framework—an evidence-based public health toolkit for climate preparedness. Our team, consisting of experts in public health, sustainable architecture, urban design, environmental health, and spatial analysis, will lead efforts to embed climate and health resilience into affordable housing programs. The long-term vision of this project is to improve and protect health outcomes for vulnerable populations in coastal affordable housing communities from climate-related health risks by addressing climate disaster preparedness and health inequities. 
In collaboration with Urban Strategies Inc., a key partner with extensive experience in community development through equitable engagement, the study will be conducted in eight coastal Choice Neighborhoods. Choice Neighborhoods is a program of the U.S. Department of Housing and Urban Development (HUD) designed to transform distressed neighborhoods with affordable housing into sustainable, mixed-income communities by leveraging public and private partnerships. The study sites are Houston, New Orleans, Ft. Myers, Miami, and Los Angeles. 
The overarching goal of this project is to create a health-equity-driven, evidence-based, and community-informed framework that integrates climate change and health resilience into affordable housing programs.  

Skills, Techniques, Methods

Due to the multidisciplinary nature of this project, RAs will be paired with sub-research groups based on research interests and needs. Learning skills will range from data and spatial analysis to visualization and data modeling. This study adopts a mixed-methods, community-engaged approach, including a rapid literature review and asset and concept mapping. 
 

Research Conditions

Students should be prepared for a combination of fieldwork and office-based research throughout the summer. This means they may need to spend time gathering data, conducting research in the field, and analyzing and processing that data in an office setting. To make the most of their summer research experience, students must be flexible and adaptable to different research conditions and environments. 

Team Structure and Opportunities

Rodrigo Siqueira Reis, PhD, MSc (Co-PI):  

  • expertise in public health, the built environment, health behaviors, and concept mapping. 

Catalina Freixas, MArch (Co-PI):  

  • expert in architecture and urban resilience 

 Ana Luiza Favarao, PhD:  

  • expert in spatial analysis and the built environment 
      

Alexandre Silva, PhD:  

  • expertise in environmental health and community-based research 
      

Milena Franco Silva, March:  

  • urban planner with mixed-methods research expertise 
     

Yi Wang, PhD:  

  • data scientist with background in housing policy 
     

Our multidisciplinary team capitalizes on each member’s expertise and aims for their contributing members to cross-pollinate the joint research agenda with their individual research interests. 

Requirements

  1. Strong work ethic: Work diligently and with dedication. 
  1. Adaptability: Demonstrate flexibility in adjusting to diverse research conditions and environments. 
  1. Research skills: Gather data, conduct research, and analyze and process data effectively. 
  1. Communication skills: Communicate findings and collaborate with team members and supervisors professionally.  
  1. Time management: Demonstrate capacity to work independently and consistently meet project deadlines.  
  1. Problem-solving skills: Approach challenges with a solution-oriented mindset.  
  1. Attention to detail: Possess a keen eye for detail  

Prior experience with GIS and spatial and data analysis will be desired but not limiting.