Texas Spatial-Temporal Data Science, Informatics and Modeling Core (TEX-SIM)

CANCER POPULATION HEALTH

Cancer population health focuses on understanding and improving health outcomes – including prevention, control, equitable access to treatment, and reducing disparities – at the community and group levels. Cancer affects everyone, but some communities face a heavier burden due to socioeconomic challenges, environmental risks, limited healthcare access, and geographic barriers.  

THE CORE FACILITY

The Texas Spatial-Temporal Data Science, Informatics, and Modeling Core Facility (TEX-SIM) works to address these challenges by providing advanced data analytical tools and informatics tailored to the diverse needs of communities across Texas. TEX-SIM integrates data on environmental exposures, georeferenced health information, and healthcare access metrics to uncover how these factors influence cancer risk, treatment, and outcomes for all types of cancer. TEX-SIM focuses on cancers that disproportionately affect disadvantaged communities, identifying their unique characteristics and needs. Unlike traditional approaches centered on individual patients, TEX-SIM emphasizes community-level health trends by developing customized community profiles that offer actionable insights to reduce disparities, promote equity, and encourage pride in our Texas communities. TEX-SIM supports evidence-based decision-making by providing the data infrastructure, analytics, and visualization tools needed to enable researchers to identify high-risk populations, design targeted interventions, expand data availability, and effectively reduce cancer disparities (Fig. 1).  

Figure 1. TEX-SIM workflow to advance population-focused cancer research.

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OVERALL GOALS OF THE CORE FACILITY

TEX-SIM is an innovative initiative to transform cancer population health research, promote health equity, and support CPRIT’s mission to reduce the cancer burden in Texas. By leveraging cutting-edge spatial-temporal data science and informatics, TEX-SIM addresses the complex interplay of social determinants of health (SDoH), environmental, and geographic factors that contribute to cancer disparities. TEX-SIM provides essential and tailored tools, resources, and support to researchers, institutions, and communities statewide, supporting data-driven strategies to reduce disparities and improve cancer outcomes across Texas communities. By leveraging UTHealth Houston’s institutional infrastructure and community engagement, TEX-SIM will effectively disseminate resources and contribute to actionable interventions.

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SPECIFIC AIMS

Aim 1: Develop the TEX-SIM infrastructure – a state-of-the-art data and computing platform – for spatial-temporal data science and geospatially linked informatics to support cancer population health research and implementation. TEX-SIM will provide a robust, scalable platform that integrates diverse, spatial-temporal datasets with geospatial informatics and advanced analytical tools for sophisticated analytical and predictive modeling. 

Aim 2: Deliver comprehensive spatial-temporal data, advanced analytics, and visualization services leveraging the novel infrastructure and methodology expertise to support cancer research initiatives across Texas. TEX-SIM will deliver harmonized datasets, interactive dashboards, and cutting-edge modeling tools to identify high-risk populations, understand cancer disparities, and design targeted prevention and treatment strategies.

Aim 3: Establish TEX-SIM as the central hub for spatial-temporal data science and informatics locally, state-wide, and nationally in cancer population health. TEX-SIM aims to foster collaboration, offer training, and host workshops to advance research, promote precision prevention, and to improve health outcomes across diverse populations.

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EXPERTISE

TEX-SIM will offer specialized services to the cancer research community, focusing on spatial-temporal data, advanced analytics, visualizations (including interactive dashboards), and tailored applications. TEX-SIM is directed and managed by Dr. Cici Bauer, Associate Professor at the School of Public Health and the Director (and founder) of the Center for Spatial-Temporal Modeling for Applications in Population Sciences (CSMAPS) at UTHealth. TEX-SIM further leverages the expertise of a wide diversity of experienced faculty housed within one of TEX-SIM’s three major cores:

1. Spatial-Temporal Data Science Core led by Dr. Cici Bauer – expertise in spatial-temporal modeling, small area estimation, multi-level modeling, simulation studies, and large-data analyses
2. Clinical Informatics Core led by Dr. Hongfang Liu – expertise in data security and integrity, comprehensive geocoding, and data linkage.
3. Cancer Population Epidemiology Core led by Dr. Qian Xiao – expertise in epidemiological study design and methods, sensitivity analysis, environmental health, and health disparities.

 

For more details on our faculty members’ specific expertise, please see the TEAM tab.