Model shedding probability across biological conditions and assay assumptions. Compare uncertainty, thresholds, and outcome ranges. Turn inputs into interpretable risk estimates, charts, and reports.
1) Effective load decay
Leff = max(0, L0 - d × t)
2) Load normalization
Ln = min(1.5, Leff / Lref)
3) Latent shedding score
z = log(P0 / (1 - P0))
+ 3.4(Ln - 0.5)
+ 0.7 ln(H)
+ 0.5 ln(T)
+ 0.4 ln(E)
+ 0.4 ln(A)
4) Shedding probability
Pshed = 1 / (1 + e-z)
5) Assay-positive probability
Ptest+ = Pshed × Se + (1 - Pshed) × (1 - Sp)
6) Predictive values
PPV = (Se × Pshed) / [(Se × Pshed) + (1 - Sp)(1 - Pshed)]
NPV = [Sp(1 - Pshed)] / [Sp(1 - Pshed) + (1 - Se)Pshed]
This model is an educational probability framework. It combines prior prevalence, adjusted biological load, host effects, tissue context, environment, activity, and assay performance into one interpretable estimate.
| Scenario | Initial Load | Days Since Peak | Host Factor | Tissue Factor | Assay Sensitivity | Assay Specificity | Estimated Shedding % |
|---|---|---|---|---|---|---|---|
| A | 7.8 | 3 | 1.20 | 1.30 | 92 | 96 | 44.70 |
| B | 9.0 | 1 | 1.40 | 1.60 | 95 | 97 | 77.90 |
| C | 5.5 | 6 | 1.00 | 1.10 | 88 | 92 | 6.30 |
| D | 6.8 | 4 | 1.10 | 1.20 | 90 | 95 | 26.80 |
It estimates the chance that a biological source is actively shedding under the entered assumptions. The model combines prior prevalence, adjusted load, contextual multipliers, and assay performance into one probability.
Multipliers let you scale the model around a neutral value of 1.00. Values above 1 increase modeled shedding tendency, while values below 1 reduce it.
Effective load is the remaining log10 load after time decay is applied. It provides a simple way to reflect declining biological concentration after the peak phase.
Shedding probability represents the latent biological state. Assay-positive probability also includes test sensitivity and specificity, so it reflects what a laboratory result may show.
The interval shows uncertainty around the estimated shedding probability, based on the sample size you enter. Larger samples usually produce a narrower interval.
Use a defensible prior from surveillance data, published prevalence estimates, or internal study baselines. The calculator treats this input as the starting probability before modifiers are applied.
It can be adapted for many biological contexts, but the parameters are generic. You should calibrate factors and decay assumptions to the organism, matrix, and sampling route you study.
The graph plots estimated shedding probability and expected assay-positive probability over time, using your current settings. It helps you visualize how decay changes both biological and test-level outcomes.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.