Infectious Disease
The Infectious Disease area is a web workspace for episode-centered infectious-disease cohort research and population-level spread intelligence. Model participants, infection episodes, specimens, exposures, interventions, and outcomes; link versioned Microbiology, Computational Biology, and Immunology results by subject and episode; run person-place-time epidemiology, cohort comparison, time-to-event, genomic cluster and transmission-network investigation, and host-pathogen-outcome integration; and use the shared Spread workspace for immutable connector snapshots, national and HHS-region surveillance curves, choropleths, Rt estimation, probabilistic forecasting, wastewater early warning, and WHO Global Health Observatory country indicators — with AI-assisted interpretation grounded in computed metrics and association-only guardrails throughout.
Start from a research scenario
Guided workflows map common questions to data requirements, analysis steps, and documentation — pick the scenario closest to your study.
Infection timeline
Research question: For each infection episode, how do events line up over time, and where are index dates, symptom onset, or follow-up missing?
Assemble a per-episode, aligned sequence of exposure, symptom, specimen, treatment, and outcome events, with missingness shown rather than invented.
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Person-place-time epidemiology
Research question: What are the attack rate, incidence, hospitalization, and case-fatality in this cohort, how does the epidemic curve look, and how do patterns differ across strata?
Compute descriptive rates, an epidemic curve, and stratified patterns over an episode cohort, with denominators and ascertainment attached to every rate.
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Cohort outcomes
Research question: Do outcomes differ between two cohorts, and how do survival or time-to-clearance curves compare — as associations, not causal effects?
Compare a binary outcome between groups and analyze time-to-event, with effect sizes and explicit censoring reported alongside significance.
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Outbreak investigation
Research question: Which episodes are plausibly linked by shared exposure and pathogen relatedness, do they form candidate clusters, and which clusters warrant investigation?
Turn an episode cohort into candidate exposure links and candidate outbreak clusters from case timing, location and contact evidence, and pathogen genomic relatedness — then adjudicate them. Every result is a hypothesis for investigator review, never proof of transmission or a confirmed outbreak.
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Intervention effectiveness
Research question: Do outcomes differ by treatment or by vaccination status, once immortal-time bias is addressed and confounding is made visible?
Compare clinical outcomes across treatment and vaccination groups with bias-aware, descriptive methods — a landmark design for treatment and observational VE for vaccination. These are association-only research estimates, never treatment effectiveness for prescribing or vaccine efficacy for policy.
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Reproduction number
Research question: Is transmission intensity rising or falling over this cohort's timeline, and how fast is the epidemic growing?
Estimate how fast an epidemic is changing from the episode incidence curve — the instantaneous reproduction number (Rt) with the Cori renewal method and a log-linear epidemic-growth rate. These are retrospective research estimates with assumptions surfaced, never real-time surveillance or nowcasting.
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Epidemic surveillance and forecasting
Research question: Is a monitored public-health signal rising or falling across geographies, what does a near-term forecast look like, and does a candidate leading indicator (such as wastewater) provide useful early warning relative to a clinical reference signal?
Pull versioned public-health surveillance signals, track epidemic curves and reproduction number across jurisdictions, forecast near-term trajectory, and screen for early-warning signals — through the area-level **Epidemic Dynamics** dashboard (`/areas/infectious-disease/spread`). This is distinct from a single study's [Reproduction number](/documentation/infectious-disease/use-cases/epidemic-dynamics) analysis, which runs on one study's episode data rather than external surveillance feeds.
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Host-pathogen integration
Research question: Do outcomes differ by pathogen lineage, resistance, or a host feature produced in another area — without recomputing that area's science here?
Group episode outcomes by a pathogen or host feature carried in versioned cross-area results, preserving the originating area, run, and version.
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Cross-area translational
Research question: How do versioned results from Microbiology, Computational Biology, and Immunology connect to infection timing, interventions, and clinical outcomes in one cohort?
Connect microbial, immune, and host-response results to infection episodes and outcomes through shared subject and episode identity, without duplicating another area's pipeline.
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Platform features
Everything available in the Infectious Disease workspace today — pipelines, explorers, exports, and provenance.
- Episode-centered data model: participants, encounters, infection episodes, specimens, exposures, interventions, and outcomes
- Versioned research case definitions with adjudication and revision history
- Longitudinal infection timelines with explicit missingness and uncertain intervals
- Person-place-time epidemiology: attack rate, incidence, hospitalization, and case-fatality with denominators and ascertainment
- Epidemic curves and stratification by time, place, demographics, and setting
- Cohort comparison with risk ratio, odds ratio, and chi-square/Fisher testing
- Kaplan-Meier time-to-event analysis with log-rank testing and explicit censoring
- Host-pathogen-outcome integration linking versioned cross-area results by episode, with provenance preserved
- Exposure and contact network analysis surfacing candidate transmission-hypothesis links from contacts, shared locations with overlapping windows, and shared events — with a pathogen genomic-relatedness overlay, never proof of transmission
- Outbreak cluster investigation combining case timing, location and contact evidence, and pathogen genomic relatedness into candidate clusters, with an interactive network view
- Investigator adjudication that promotes, rejects, or resets candidate clusters with a recorded rationale and preserves those decisions across re-runs
- Directional transmission-hypothesis links with serial-interval and genomic-distance likelihood, link-level accept/reject/uncertain adjudication, and threshold sensitivity sweeps
- Hospital movement and facility investigation views for within-facility spread hypotheses
- Pathogen lineage dynamics over time from linked Microbiology genomic results (frequency, replacement, growth-advantage summaries)
- Landmark treatment/resistance-outcome comparison that defuses immortal-time bias, stratifies by antimicrobial-resistance evidence linked from Microbiology, and flags confounding by indication — descriptive and non-prescriptive, never treatment effectiveness
- Observational vaccine effectiveness (VE = 1 − risk/odds ratio) with confidence intervals, breakthrough-infection summaries, an optional test-negative design, and subgroup views — association only, never causal efficacy or a policy claim
- Instantaneous reproduction number (Cori renewal method) with a caller-supplied serial interval and credible intervals, plus epidemic-growth rate and doubling time — a retrospective research estimate, never real-time surveillance
- Spread intelligence workspace: shared connector registry, immutable content-hashed raw snapshots (GCS archival), evidence records with license/attribution, and Cloud Tasks connector refresh
- Machine-enforced redistribution gate blocking raw export and bundling for restricted or unknown-license sources
- CDC Open Data connectors: national NREVSS respiratory positivity and lab test/detection volumes; HHS Region 1–10 positivity trends; state RSV and SARS-CoV-2 centered 3-week positivity/tests and trailing 5-week detections with explicit eligibility/suppression gaps; NSSP state emergency-department visit percentages for RSV, SARS-CoV-2, influenza, and combined respiratory illness; NNDSS weekly state reports for measles, pertussis, hepatitis A, Lyme disease, West Nile virus, and salmonellosis with distinct no-cases, unavailable, and not-reportable states; state COVID/influenza hospital admissions and hospitalized census; U.S. Census population denominators
- HHS-region Epidemic Dynamics analysis with stable regional geography, region-specific curves, Rt estimation, probabilistic forecasts, rolling evaluation, and per-region data-quality review
- Surveillance data-quality panel: source freshness, geographic coverage, missingness, gap detection, and revision deltas between snapshot vintages
- Comparison workspace for up to six regions, states, or countries on a shared measure scale, plus unit-safe multi-signal trajectory comparison using independently indexed laboratory, ED, hospitalization, and wastewater series with per-series missingness and snapshot provenance
- Population-normalized epidemic curves with explicit date basis; series preflight guard refusing mixed date bases, structural breaks, or too-few-points before Rt/forecast runs
- U.S. state choropleth map (deck.gl) with Census per-capita normalization and small-count suppression
- Spread Rt estimation: raw vs delay-adjusted stable Rt with provisional tail flagging, Rt=1 change-point crossings, serial-interval × window sensitivity grid, and archived estimates diffable by data cutoff
- Probabilistic surveillance forecasting: no-change/seasonal/trend baselines, renewal/GLM/state-space models, ensemble comparison, rolling-origin backtest (WIS/MAE, coverage, calibration), and promotion gate refusing models that fail to beat baselines or are miscalibrated; append-only forecast archive
- Wastewater early warning: CDC NWSS national viral-activity signals (SARS-CoV-2, influenza A, RSV), revision-window snapshot retention, dual-source lag sweep vs clinical/lab reference, and rolling leading-indicator evaluation
- WHO Global Health Observatory (first slice): OData connector transport, ISO 3166 alpha-3 country crosswalk, country indicators (DTP3, measles MCV1, polio, HepB3, TB incidence, malaria deaths, HIV new infections), global world-map choropleth (percent, per 100k, per 1k), country epidemic curves with full-history default, and annual forecast/evaluation horizons
- Observed / estimated / projected outputs kept visibly distinct in Spread UI, exports, and interpretation (retrospective, non-operational surveillance — not a command-and-control system)
- Grounded AI interpretation with associational guardrails against transmission, causation, diagnosis, and outbreak claims
- Async job polling with downloadable artifacts and reproducible provenance