Overview
Infectious Disease workflows link pathogen, host, exposure, and intervention evidence to clinical outcomes and person-place-time epidemiology in one episode-centered study workspace. Each use case below maps a common research question to the platform capabilities, data requirements, and suggested analysis path.
Use case index
| Use case | Research question | Key capabilities |
|---|---|---|
| Infection timeline | How do exposure, symptoms, specimens, treatment, and outcomes align for each episode? | Longitudinal episode timeline, missingness reporting, index and risk windows |
| Person-place-time epidemiology | What are the rates, epidemic curve, and stratified patterns in this cohort? | Attack rate, incidence, hospitalization, case-fatality, denominators, stratification |
| Cohort outcomes | Do outcomes differ between groups, and how does time-to-event compare? | Cohort comparison (RR/OR), chi-square/Fisher, Kaplan-Meier, log-rank |
| Outbreak investigation | Which episodes are plausibly linked, and do they form candidate clusters? | Exposure/contact network, threshold sensitivity, genomic-relatedness overlay, cluster investigation, link- and cluster-level adjudication, lineage dynamics, facility co-location |
| Intervention effectiveness | Do outcomes differ by treatment or vaccination, once time bias and confounding are addressed? | Landmark treatment outcome, treatment × resistance, observational VE, breakthrough |
| Reproduction number | Is transmission intensity rising or falling, and how fast is the epidemic growing? | Cori instantaneous Rt with credible intervals, epidemic-growth rate, doubling time |
| Epidemic surveillance and forecasting | How is a public-health signal trending across jurisdictions, what's the near-term forecast, and is a leading indicator giving early warning? | Connected surveillance sources, epidemic curve + Rt, cross-geography/signal comparison, multi-model forecast + backtest, early warning, suppressed maps |
| Host-pathogen integration | How do outcomes vary by pathogen lineage or host feature from other areas? | Cross-area linked results, feature-grouped outcomes, preserved provenance |
| Cross-area translational | How do microbial, immune, and host results connect to infection episodes and outcomes? | Shared subject/episode identity, versioned result linking, grounded interpretation |
Who these use cases serve
| Audience | Typical goals |
|---|---|
| Infectious-disease researchers | Link pathogen, host, intervention, and outcome evidence in reproducible cohorts |
| Hospital epidemiology researchers | Episode timelines, ward context, and intervention evaluation |
| Public-health research teams | Person-place-time analysis and uncertainty-aware reporting |
| Vaccine and anti-infective teams | Breakthrough and treatment-response cohorts with clinical endpoints |
Common data requirements
Most use cases start with an infectious-disease study whose central entity is the infection episode:
- Participants and episodes with index dates, case status, and risk windows
- Outcomes with severity,
event_observed, andtime_to_event_days - Denominators (population at risk, person-time) for population rates
- Linked results referencing versioned Microbiology/CompBio/Immunology artifacts by episode
Participants, episodes, exposures, interventions, outcomes, linked results, and denominators can each be bulk-loaded via CSV import, rather than entered one at a time.
Choosing a starting point
| If your primary data is… | Start with… |
|---|---|
| Episodes with dated events | Infection timeline |
| Cases plus population denominators | Person-place-time epidemiology |
| Two groups with outcomes | Cohort outcomes |
| Exposures, contacts, and isolate relatedness | Outbreak investigation |
| Treatments or vaccination status with outcomes | Intervention effectiveness |
| Dated episodes over an epidemic period | Reproduction number |
| Public surveillance feeds across jurisdictions | Epidemic surveillance and forecasting |
| Episodes plus linked pathogen/host results | Host-pathogen integration |
| Multiple areas sharing subjects | Cross-area translational |
What these use cases are not
These workflows support exploratory and translational research. They are not operational contact-tracing, mandatory-reporting, diagnostic, or prescribing systems, and they never assert transmission, causation, diagnosis, susceptibility, or outbreak status from association alone. All AI interpretation outputs include research disclaimers and cite computed metrics only.