Projects
Acropolis Analytics Research Institute uses computation and modeling to carry evidence from population-scale data into clinical practice, public policy, and the everyday lives of patients, families, and communities.
Population-Adjusted Epidemiology Outcomes Network (PAEON)
The Population-Adjusted Epidemiology Outcomes Network (PAEON) is the core data backbone for Acropolis Analytics Research Institute—a unified, county-level outcomes engine that stitches together population denominators, behavioral risk surveys, infectious-disease reports, chronic-disease surveillance, structural context, and mortality into one reusable framework.
PAEON aligns diverse datasets to a common geography and definition set so that trends in risk, burden, health-care use, and mortality can be compared fairly across counties, states, and years. Its tiered architecture includes population “Atlas” layers, behavioral risk, infectious and chronic morbidity, hospital utilization, mortality, environment, mobility, crime, and access to care—providing an annual, population-adjusted view of health and context for every U.S. county.
The goal is straightforward: build a reproducible data engine that public-health agencies, clinicians, and policymakers can use to answer hard questions about who is at risk, where systems are failing or improving, and which interventions are most likely to move the needle.
PAEON I — PAX: Border Demographics, Disease & Crime
PAX is the first large-scale demonstration of the PAEON backbone, focused on the U.S.–Mexico border corridor defined by the La Paz Agreement (roughly 100 km on either side of the border). PAX produces a baseline atlas of how the region has changed since 1990: who lives there, and how burdens of chronic disease, infectious disease, and crime have moved over time.
Using harmonized U.S. and Mexican data, PAX generates population-adjusted, county- and state-level estimates for four domains: demographics, chronic disease, infectious disease, and crime & violence. Outputs include standardized maps, tables, and time-series panels that allow side-by-side comparison of border vs. non-border areas in both countries, with careful documentation of uncertainty and data gaps.
PAEON II — AORTA: National Cardiovascular Disease Burden
AORTA extends PAEON to cardiovascular disease (CVD), describing how CVD risk and burden are distributed and changing across all U.S. counties. It integrates demographic denominators, surveillance data, and state-level composition to create reconciled, population-adjusted county-year estimates of CVD prevalence and mortality that are comparable across states, rural vs. urban areas, and levels of social vulnerability.
AORTA then builds multivariable models that relate demographic, behavioral, metabolic, and structural factors—such as smoking, obesity, diabetes, insurance coverage, and poverty—to CVD morbidity and mortality. The result is a national CVD risk atlas that highlights where burden is rising or falling, quantifies geographic inequalities, and supports scenario-based planning for prevention and treatment resources.
PAEON III — PANCREA: Diabetes & Metabolic Risk
PANCREA focuses on diabetes and related metabolic risk. Built on the same PAEON backbone, it generates county-level estimates of diabetes prevalence, obesity, physical inactivity, and related indicators over time, enabling fair comparisons within and across states, between rural and urban communities, and across levels of social vulnerability.
PANCREA links these indicators to mortality and access-to-care measures, then models how demographic, behavioral, metabolic, and structural factors shape diabetes morbidity and mortality. It also connects directly to AORTA, producing joint cardiovascular–diabetes risk structures and scenario forecasts that help planners see how changes in obesity, activity, or preventive care could shift future burden.
PAEON IV — PNEUMA: Chronic Respiratory Disease Burden
PNEUMA tracks chronic respiratory diseases—especially COPD and asthma—across U.S. counties. It produces harmonized, population-adjusted county-year estimates of respiratory morbidity and mortality, with consistent age adjustment and uncertainty reporting, so that patterns can be compared across rural and urban counties and across different vulnerability levels.
Beyond burden mapping, PNEUMA models how tobacco exposure, occupational hazards, and environmental conditions contribute to geographic inequalities in respiratory health. It also builds a baseline vulnerability surface that can later be overlaid with air-quality and wildfire-smoke data, supporting environmental-health preparedness.
ADRD Caregiver Experience & Burden Survey
Many Alzheimer’s and dementia programs only see formal caregiver data every few years, even though caregivers’ lives can change dramatically in a matter of months. Acropolis Analytics Research Institute is developing a facility-level Alzheimer’s Disease and Related Dementias (ADRD) Caregiver Experience & Burden Survey that organizations can run on a recurring basis.
The project adapts state-level caregiver survey work into a format that individual ADRD and memory facilities and programs can deploy with their own patients’ and residents’ families. The instrument focuses on who caregivers are, how caregiving affects their work and finances, the time and tasks they take on, how it impacts their physical and mental health, and which supports they still cannot access.
Acropolis Analytics Research Institute provides participating facilities with de-identified datasets and clear, visual reports that track caregiver burden over time and highlight unmet needs. As capacity allows, recurring analyses (often annually) will be produced for partners, and aggregated, de-identified summaries and graphics will be made available through the Data & Graphics section of this site. Over the long term, this project is designed to connect with the broader PAEON / MNEME framework, linking facility-level caregiver experience to county-level patterns in cognitive decline and caregiver strain.
Collaborations
Acropolis Analytics Research Institute is built to work alongside other people’s strengths. We collaborate with universities, state and local health departments, clinical and long-term care facilities, laboratory groups, and non-profit organizations that want to turn their data and questions into usable evidence.
On the quantitative side, we bring expertise in large-scale data integration, epidemiologic and statistical modeling, survey design and analysis, and reproducible reporting. On the translational side, we focus on connecting what happens in clinics, facilities, and programs to population-level questions and policy-relevant outcomes.
Collaborations can range from one-off analytic support and technical consultation to co-developed grant applications, shared datasets, and long-term joint projects. The common thread is simple: we look for partners who care about moving high-quality science toward better medicine, better policy, and better outcomes for the people they serve.