Disease surveillance, real-time outbreak detection, automated CDC reporting, and population health analytics — all on a governed AI data foundation.
xAQUA augments epidemiologists, surveillance teams, and outbreak responders — it does not replace NEDSS, your IIS, or your lab reporting infrastructure. It sits above them, correlates signals across surveillance streams, and turns plain-English questions into reportable, lineage-traceable answers. Built for hard CDC and state reporting cadence.
Public health data is the most fragmented in government — across labs, providers, registries, environmental sources, and wastewater. The systems work. The integration is what slows everything down. xAQUA fixes the integration without replacing the systems.
NEDSS, immunization registries, vital records, ELR, wastewater (NWSS), and environmental data each on their own platform with their own format. Cross-stream questions take days.
Days behind disease velocityEpis spend nearly half their time on data entry, case investigations, and report compilation. CDC and state reporting requires manual extraction from multiple systems every cycle.
Reporting eats analytical capacityDays or weeks pass before patterns surface from fragmented data. By the time clusters are identified, an outbreak may already be spreading. The cost of slow correlation is measured in cases.
Time-to-detect measured in daysxAQUA does not replace your systems of record. It does not bulk-copy your data. It federates queries with full authority enforcement — and every request is logged, scoped, and replayable.
From front-line operations to federal reporting. xAQUA covers the operational, analytical, and oversight workload across the agency.
Each agent is a specialist. Together they augment your front-line staff, analysts, and oversight team — without replacing the systems they already use.
A unified, governed view across surveillance streams — cases, specimens, immunizations, wastewater signals, vital records — with sub-county geographic resolution and cohort linkage.
PHI handling, 42 CFR Part 2 enforcement, de-identification thresholds, and small-cell suppression. The compliance posture CDC, IRBs, and state oversight already require.
Anomaly detection across syndromic, lab, and wastewater signals identifies clusters before they spread. Predictive models with explainable feature attribution.
HL7/FHIR-aware connectors. Automated NNDSS submissions. Schema-aware ingestion for new conditions, new lab partners, and new federal data calls.
Identify undervaccinated populations by geography, age, and demographic. Target outreach campaigns. Track health equity metrics with bias monitoring.
Real-time dashboards for health department leadership. Disease trends, immunization coverage, equity outcomes — with auto-narrated commentary and full lineage.
A typical surge analyst flow. Same shape holds for outbreak investigation, immunization gap analysis, and federal reporting.
Concrete workflows scoped at peer agencies. Each one is a single use case the platform unlocks — and the platform unlocks dozens more after the first.
Accelerate investigations with AI-powered case linkage, cluster analysis, and source identification across fragmented surveillance, lab, and wastewater data.
Identify undervaccinated populations by geography, age, and demographic with sub-county precision. Target outreach without violating privacy thresholds.
Correlate NWSS signals with clinical surveillance. Early warning for respiratory viruses, enteric diseases, and emerging threats — days ahead of clinical signal.
Analyze birth and death data for population health trends. Track maternal mortality, infant outcomes, and cause-of-death patterns with cohort analytics.
Link environmental exposures to health outcomes. Track lead poisoning, air quality impacts, and water contamination incidents across geography and time.
Coordinate emergency public health response with real-time situational awareness. Mass-casualty tracking, resource allocation, communications, and federal reporting.
Automate notifiable disease submissions. Generate HL7/FHIR messages, NETSS, and state-specific reportable formats with full data lineage.
Cohort outcomes by demographic, geography, and program participation. Bias-aware models with cohort-level explainability for community health planning.
Manage cancer, diabetes, hypertension, and asthma registries. Cross-link with social determinants for prevention program design and outcome tracking.
Government data carries statutory privacy, federal reporting, and oversight obligations from day one. xAQUA is built for that posture, not against it.
Reference outcomes from peer-department design conversations and adjacent production deployments on the same platform.
A scoped 30–60 day pilot against your specific use cases. Live in your environment. No PHI egress. We work with state and local health departments on outbreak detection, NNDSS automation, immunization equity, and wastewater integration.