Fellowship Project: A Multimethod Approach to Assess Sanitary Risks and Microbial Exposures Associated with Waterborne Illnesses and Infrastructure Management in Baltimore, Maryland
Marccus D. Hendricks is an Associate Professor of Urban Studies and Planning in the School of Architecture, Planning, and Preservation and a Faculty Affiliate with the Maryland Institute for Applied Environmental Health in the School of Public Health at the University of Maryland in College Park, Maryland. His other affiliations include the Clark School of Engineering’s Center for Disaster Resilience, the National Center for Smart Growth Research and Education, and the Environmental Finance Center.
Marccus’ primary research interests include infrastructure planning and management, social vulnerability to disaster, environmental justice, sustainable development, public health and the built environment, and citizen science. He utilizes a mixed-methods approach to his research that includes both quantitative and qualitative methods such as multiple regression, cross-sectional research, spatial mapping, in-depth interviewing, participatory action research, and different forms of spatial and analytic epidemiology. At the intersection of his work he ensures that low-income and communities of color are planned and accounted for in light of environmental hazards and investigates how the inventory, condition, and distribution of critical infrastructures and public works, such as stormwater services, energy, public transit, streets and roadways, sewer, community facilities, litter and debris removal, and green space, can modify hazard exposures, disaster impacts, public health outcomes, and community resiliency.
Marccus is a founding fellow of the William Averette Anderson Fund (the first national interdisciplinary organization working to increase the number of underrepresented persons of color in the field of disaster research, practice, and pedagogy) and currently serves as a board member for the Fund. He recently participated in a U.S. Congressional Briefing entitled “Addressing the Impact of Climate Change on Public Health and Natural Disasters” on Capitol Hill in Washington, DC, and was quoted from his participation in Scientific American. He was also awarded a Tier 1 research grant from the University of Maryland’s Division of Research to work on a project entitled, “Infrastructure, Urban Flooding and its Influence on Social Vulnerability and Mobility: A Place-based Study in Southeast Washington, D.C.” Marccus holds a Ph.D. in Urban and Regional Science and a Master of Public Health, both from Texas A&M University. He completed his undergraduate work at the University of North Texas.
A Multimethod Approach to Assess Sanitary Risks and Microbial Exposures Associated with Waterborne Illnesses and Infrastructure Management in Baltimore, Maryland
Past studies in public health have demonstrated an association between disease and poor sanitation, such as waterborne illnesses and exposure to sewage-laden waters. Modern stormwater and sanitary systems are some of history’s most lifesaving infrastructures. However, failure to maintain and rehabilitate these systems over the years, as well as changing environmental conditions, have created some pre-modern circumstances in cities across the world including Baltimore, Maryland. These risks may be particularly evident in marginalized urban neighborhoods that often have poorer stormwater and sanitation infrastructure and public works services. The Baltimore City sewer system has frequent overflows of its sanitary sewers due to an old and failing system and more frequent and intense rainfall events further overwhelming the system. Likewise, the city has a number of larger sanitation and waste management issues that can have consequences for ecological and public health. This study uses a multimethod approach to assess sanitary sewer overflow (SSO), among other sanitary risks and exposure to bacteria from contaminated surfaces within the built environment across Baltimore neighborhoods. The study will use SSO incident data, waste and trash data, land use data, and American Community Survey Data to map and statistically model incident risks, along with environmental sampling data and household surveys to understand exposure and impacts.