Seedlabs

SeasonWatch: One-Map Respiratory Co-Circulation Explorer for Health Departments

A map for health departments that shows flu, RSV, and COVID spreading in one view instead of separate screens.

A browser-based situational-awareness tool for epidemiology teams that shows flu, RSV, and COVID spreading at once — one animated map where each concentric ring is a pathogen — replacing the current juggling of separate per-pathogen dashboards.

Computer ScienceData Visualization and Analytics
Cognitive-Adaptive Visual AnalyticsPublic health surveillance / epidemiology

Concept

During respiratory season, epidemiologists monitor several pathogens simultaneously, but today's dashboards (one per pathogen, or small multiples) make it hard to see where flu surges while RSV declines and COVID climbs. SeasonWatch applies the validated geocircle encoding across pathogens: at each region, each concentric hollow ring is a color-coded pathogen, animated week by week through the season, with optional overlay rings for hospital capacity or vaccination uptake. Epi teams get a single view for questions like 'which regions have multiple pathogens peaking together?' — the multivariate, spatiotemporal queries the method was built for — plus one-click snapshot exports for briefings.

Why now

The new paper reports that interview and observational sessions with epidemiologists confirmed the importance of multivariate, spatiotemporal queries and the utility of the concentric-circle animated tool for answering them; the encoding explicitly handles multiple, potentially interacting variables (cases, deaths, vaccinations) without occlusion, and the implementation is open-source and browser-based. The recurring winter flu/RSV/COVID wave in the US and Europe gives a concrete, repeating buyer need that the COVID-focused research tool did not package.

Written by GLM · 11 Oct 2026

AI assessment

Backed by 1 paper81

A highly focused application of a validated visualization method for a clear professional pain point, though it suffers from low novelty due to a nearly identical existing idea in the catalog.

Evidence strength
5/5
The idea directly implements the specific concentric-circle encoding and browser-based delivery validated by the research paper's interviews with epidemiologists.
Market pull
4/5
Public health agencies have a recurring, urgent need to manage 'tripledemic' surges, and the target beneficiaries are well-defined.
Novelty & moat
1/5
The idea is essentially a variant of 'OutbreakPulse', using the same mechanism (concentric circles) and same value proposition (multivariate outbreak mapping).
Feasibility
5/5
The research already provides an open-source, browser-based implementation (CoronaViz), making the MVP a matter of data integration rather than R&D.
Wedge clarity
5/5
The focus on 'respiratory co-circulation' is a sharp, specific entry point that solves a concrete problem for a specific user group.
Simplicity / focus
5/5
The product is a single, focused visualization tool without unnecessary feature bloat or platform ambitions.

Scored by Gemma 4 · 11 Oct 2026. Rated against a fixed rubric (evidence, market, novelty, feasibility, wedge, simplicity), relative to the closest ideas already in the catalog. A prior estimate to compare ideas before real-world signal arrives.

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Who benefits

  • European Centre for Disease Prevention and Control (ECDC)organization

    Publishes weekly respiratory-virus surveillance across EU countries; a single animated co-circulation map would directly support its seasonal situational assessments and public weekly reports.

  • UK Health Security Agency (UKHSA)organization

    Runs national flu, RSV, and COVID surveillance each winter; one multivariate animated view would speed regional co-circulation queries versus toggling separate pathogen dashboards.

  • Massachusetts Department of Public Healthorganization

    Its state epi team tracks multiple respiratory pathogens by county during season; county-level animated rings match its weekly situational review workflow.

Research it builds on

  1. Visualizing multilayer spatiotemporal epidemiological data with animated geocircles
    Brian Ondov, Harsh B Patel, Ai-Te Kuo et al. · 2024 · 1 citations
    All ideas from this paper →
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feasibility