Decision pathway
1
Environment
Is this a higher-risk place and time for infected ticks?
2
Exposure
Does your planned activity make contact more likely?
3
Bayesian red flags
After exposure, selected findings update concern from prior to posterior probability.
4
Action
Use precautions now and seek care when red flags warrant it.
41%
infected-tick exposure
next 48 hours
next 48 hours
Elevated exposure risk
Risk is elevated because regional baseline, humidity, seasonal pattern, and outing context all matter.
Regional baseline
Elevated
Lunenburg County is modelled as a higher-risk Nova Scotia setting.
Weather signal
Favourable
Warm, humid, low-wind conditions support questing activity.
Expected tick activity
High
Conditions suggest ticks may be active on vegetation edges and trails.
Infection pressure
Moderate
Estimated using simulated regional prevalence and placeholder surveillance inputs.
Your exposure
Moderate
Route, time outdoors, vegetation contact, and protection shape risk.
Clinical red-flag status
None selected
Optional symptom inputs update the Bayesian panel.
72-hour exposure outlook
Bayesian clinical red-flag update
This panel demonstrates the intended Bayesian functionality using placeholder priors and likelihood ratios.
Reference class
Plausible exposure
Prior probability
3%
Posterior probability
3%
| Evidence selected | Placeholder LR | Interpretation |
|---|---|---|
| No red flags selected | 1.0 | No clinical probability update applied. |
Current status: Bayesian engine demonstrated with simulated priors and placeholder likelihood ratios.
Why the app thinks risk is elevated
What to do now
Implementation status
Implemented in this demo
User workflow, regional selector, outing adjustment, risk explanation, 72-hour display, red-flag check, and Bayesian prior-to-posterior update.
Simulated
Nova Scotia regional baseline values, tick infection pressure, weather suitability, short-term forecast movement, and clinical priors.
Placeholder
Likelihood ratios, calibrated regional prevalence, veterinary sentinel coefficients, and data source confidence scoring.
Future live version
Provincial surveillance integration, weather API, parameter register, provenance display, and validation against observed tick and exposure data.
Data layers behind the forecast
Weather and microclimate
Short-range forecasts, humidity, temperature, wind, rainfall, and ground-level conditions from providers such as meteoblue.
Historical phenology and prevalence
Regional patterns showing when ticks are typically active and where infected tick prevalence has historically been higher.
Public and animal surveillance
Human case baselines, infected tick submissions, provincial surveillance, animal sentinel signals, and citizen science reports used to estimate infection pressure.
This simulation is a public information and design demonstration. It is not a medical device, diagnostic tool, or substitute for clinical advice.
Clinical concept, model and design: Michael Tremblay.
Intellectual property owner: Cassis Ltd. Copyright © 2026 Cassis Ltd. All rights reserved.
Publication of this demonstrator grants no licence for reproduction, adaptation, redistribution or commercial use without prior written permission, except as permitted by applicable law.
Intellectual property owner: Cassis Ltd. Copyright © 2026 Cassis Ltd. All rights reserved.
Publication of this demonstrator grants no licence for reproduction, adaptation, redistribution or commercial use without prior written permission, except as permitted by applicable law.