About this trial
The Human Observatory Study is a prospective observational and ecological surveillance study building a continuously-updating world model for human health, disease, and death at the individual and population level. Individual multi-system clinical data from enrolled participants are linked to a continuously-ingested ecological data infrastructure spanning environmental exposures, social determinants, genealogical and family history records, mortality data, and population health databases at geographic resolutions from home address to global scale and beyond. The resulting model generates individual screening recommendations informed by population-level causal estimates, and population-level causal forecasts anchored by present-timepoint individual clinical biology. This linkage creates a feedback architecture designed to improve both simultaneously.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Enrolled in the 100-Year Human Aging Study at any fixed or mobile clinical site; OR completion of online health screener with provision of geographic anchor data and consent.
Disqualifiers
Age under 18 years (current protocol; pediatric amendment planned).
Trial population
Participants of all ages, health statuses, and demographic backgrounds enrolled in the 100-Year Human Aging Study at any fixed or mobile clinical site, plus participants completing the online health screener. No exclusions based on health status, geographic location, language, or population group. The ecological surveillance layer requires no individual enrollment.
Trial design
Cohort
Prospective
Treatments tested in this trial
Multi-Domain Ecological and Clinical Data Linkage
Other interventionLinkage of individual multi-system clinical health measurements to continuously-ingested ecological data from public and private registries spanning environmental, social, genealogical, and population health domains at geographic resolutions from home address to global scale and beyond. The linked dataset feeds a continuously-updating causal inference engine generating life expectancy estimates, disease cluster detection, individual screening recommendations, and population health intelligence.
Treatment groups
Trial outcomes
Primary outcomes
Life Expectancy Estimates by Geography
Continuously-updated life expectancy point estimates with credible intervals generated at individual, neighborhood, ZIP code, county, state, national, global, and beyond-earth scales using individual clinical data linked to population mortality records, environmental context, and ecological data.
Geographic Disease Cluster and Outbreak Detection
Statistically anomalous concentrations of incident disease, mortality spikes, or shared symptom patterns at neighborhood and community resolution.
Secondary outcomes
Individual Screening Recommendation Accuracy
Concordance between population-level causal estimates used to generate individualized screening recommendations and actual individual health outcomes at longitudinal follow-up, assessed periodically as outcomes accrue.
Causal Effect Estimates for Modifiable Exposures
Estimated attributable life-years gained or lost per unit change in modifiable environmental, occupational, and social exposures.
Geographic Variation in Disability-Free Life Expectancy
Disability-free life expectancy stratified by geography, ascertained via the functional independence and disability survey instrument used across all three associated protocols.
Health Equity Characterization
Life expectancy gaps and chronic disease disparities stratified by geography, income, race and ethnicity, educational attainment, and rural-urban classification.
Sponsors and contacts
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