Services
Matthews Geographics provides GIS, mapping, demographic analysis, forecasting, and place-based decision support for organizations working in public health, civic access, research, and planning. Our work turns complex data into usable evidence.
Core Areas of Practice
Spatial Analysis & Mapping
Discover geographic patterns, monitor disease burden, and measure disparities in access, risk, or demographic opportunity.
- Network travel-time impedance modeling
- 2-step and adaptive floating catchment area analysis
- Service area equity audits and site suitability
Demographic Analysis & Forecasting
Understand who lives where through small-area estimation, demographic shift analysis, and reliable local population projections.
- Population projections (5, 10, 20-year horizons)
- Small-area estimation from complex survey data
- School district enrollment forecasting
Civic & Democracy Modeling
Optimize resource allocation, analyze voter access, and apply spatial equity frameworks to infrastructure planning.
- Voter access analysis and resource allocation modeling
- Racial polarization analysis and demographic evaluation
- Precise geocoding and address-level verification
Public Health & Epidemiology
Analyzing spatial patterns in incidence and mortality using registries, electronic medical records, and Medicare claims to clearly model geographic bias and detect hot-spots.
- Mapping structural disparities in access to care
- Evaluating programmatic impact by geography
- Grant proposal methodology and manuscript development
Enabling AI
Integrating advanced generative AI frameworks into scholarly publishing and research workflows with rigorous trust-based disclosure methodologies.
- Implementation of the Human-in-the-Loop-O-Meter (HILOM) framework
- System instructions for reproducible narrative synthesis
- Verifiable disclosure statement generation for peer review
Built on the HILOM Framework for structured AI disclosure. See the AI Disclosure Policy Monitor for current institutional requirements across major publishers, funding agencies, and standards bodies.
Data Environments & Methods
Technical capabilities ensuring that the underlying analysis is robust, precise, and reproducible.
Environments
- ● Stata, R, Python
- ● ArcGIS & Network Analysis
- ● AI-Enabled Analytic Workflows
Core Datasets
- ● American Community Survey / Census
- ● Medicare Claims (FFS & MA)
- ● EMR & Cancer Registries
Technical Approaches
- ● Geocoding & Address Standardization
- ● Spatiotemporal Cluster Detection
- ● Spatial Survival Analysis (Cox Modeling)
Expertise & Methodological Foundations
What is the Matthews Geographics approach to spatial equity audits?
We combine high-precision geocoding with network impedance modeling (travel-time analysis) to identify service gaps. By overlaying demographic vulnerability indices, we quantify exactly how distance and transit barriers disproportionately affect specific populations.
How does small-area estimation differ from standard census reporting?
While the census provides static snapshots, small-area estimation (SAE) uses statistical modeling to predict demographic variables for geographies where data is sparse or suppressed. We utilize Bayesian hierarchical models to produce reliable local estimates that standard surveys cannot reach.
What is the HILOM framework for AI disclosure?
The Human-in-the-Loop-O-Meter (HILOM) is a proprietary disclosure framework that quantifies the level of AI assistance in scholarly work. It provides a standardized method for researchers to communicate the integrity and human-oversight of AI-generated components in peer-reviewed environments.
How is demographic forecasting performed for 10-20 year horizons?
We utilize a cohort-component model that accounts for local fertility, mortality, and migration rates. For long horizons, we integrate land-use constraints and regional economic drivers to ensure forecasts reflect both demographic momentum and physical capacity.