An AI-assisted operational intelligence platform for epidemic response — predicting where an outbreak is moving, coordinating the field, and directing scarce resources before transmission expands. Built offline-first for low-resource, low-connectivity environments.
In low-resource settings the decisive weakness is no longer only detection — it is the days lost between a case appearing and a coordinated response reaching it. Every day the response lags, transmission compounds.
Median lag from index case to coordinated alert in low-resource settings (WHO IDSR + post-event reviews).
Detect-and-respond window needed to hold a Filovirus or Mpox outbreak below exponential growth.
Growth in zoonotic spillover events since 2000 — driven by climate, urbanisation, and migration.
It is no longer whether outbreaks continue — it is whether prediction, coordination, and resource movement can outrun transmission.
Existing systems assume connectivity the worst-affected zones don’t have, and none turn scattered field reports into a forecast of where the outbreak is heading next.
Paper forms take days to reach a database while cases double weekly. Web-only, hospital-centric tools go dark where there is no network. Coordinators drown in undifferentiated reports.
The response stays reactive — chasing cases instead of getting ahead of the corridor the outbreak is travelling.
Offline-first field intelligence, explainable AI triage, and forecasting turn every report into a live picture of where the outbreak is moving and where to act.
From reacting to cases → to positioning teams and supplies before cases arrive.
One operating loop that gets responders ahead of the spread — from a community health worker’s phone to a national command dashboard.
Forecast likely spread across villages, corridors, markets, and borders over the next days and weeks.
Cases, risks, resources, facilities, and contacts in a single real-time view shared across responders.
Direct teams, PPE, ambulances, beds, and lab capacity where they’ll matter before cases arrive.
The problem isn’t only detecting Ebola → once it’s spreading, the need is to predict where it’s going, coordinate the response faster, and move scarce resources to the right place first.
Mobile-first, AI-augmented, offline-resilient — and designed to plug into the systems responders already use, not replace them.
Android app for community health workers. Structured cases plus rumours, unexplained deaths, and funerals. Multilingual (EN/FR/SW); syncs when connectivity returns.
Risk scoring with a plain-language rationale, cluster and super-spreader detection, and a forecast of likely next hotspots.
Live geospatial view, contact-transmission graph, and resource-stress modelling for PPE, beds, and clinic capacity.
IHR (2005) notifications, WHO / Africa CDC pathways, and a full audit trail for after-action review.
The platform creates value at each stage a pathogen moves through a population.
Symptoms, exposure, and outbreak proximity scored at the point of contact — no connectivity needed.
Household, funeral, and market exposure mapped in real time; clusters flagged before hospital presentation.
Corridor crossings surfaced against the contact graph; IHR (2005) notification triggers automatically.
High-density transmission nodes identified so investigation and containment can focus fast.
PPE, isolation beds, and clinic capacity stress-modelled a week ahead, routed to the nearest capacity.
Ranked interventions proposed with rationale and a human approval gate — AI augments, never replaces.
Every field report becomes an alert, a forecast, or a resource decision on one screen — with the reasoning attached.
Every score shows its drivers — e.g. “High risk: haemorrhagic symptoms + funeral exposure + within 5km of an active cluster.” The AI flags and ranks; the human decides.
How the operating loop plays out over a fortnight of an outbreak.
A simulated scenario in the DRC–Uganda Albertine corridor — illustrative of the operating model, not field-validated results.
VitaAlert is an operational layer shared across the people who run the response — from the village to the continental command.
It is faster containment, fewer deaths, and stronger epidemic resilience — measured in outcomes, not dashboards.
Compress the gap between spread and response — the variable that most decides whether an outbreak is held at tens or escalates into thousands.
Earlier isolation, protected responders, and safer facilities as PPE and overload risks are surfaced first.
Teams, beds, and lab capacity directed to the points that matter — before cases arrive.
Less human, institutional, and economic cost per outbreak → and a field network that grows stronger between them.
Three forces converge — and the response architecture VitaAlert plugs into is live today.
We’re standing up a supervised pilot in the DRC–Uganda Albertine corridor — and inviting ministries, responders, and mission-aligned funders to shape it. VitaAlert supplies the platform, training, and field support; partners retain full ownership of their data.