Viral Shedding Duration Calculator

Formula used

The calculator estimates shedding duration as a baseline time multiplied by adjustment factors:

• Profile method: Baseline Days come from the selected shedding profile.
• Ct method: Baseline Days = (Threshold Ct − Initial Ct) ÷ (Ct increase per day).
• Log10 method: Baseline Days = (Initial log10 − Threshold log10) ÷ (Log10 decay per day).

A planning range is also shown by scaling the estimate to reflect typical variability.

How to use this calculator

1. Select a calculation method based on your available information.
2. Choose how you want to interpret positivity with the assay interpretation setting.
3. Set specimen, immune status, and other context fields.
4. If using Ct or log10 methods, enter the required numeric values carefully.
5. Optionally add a reference date to estimate an end date.
6. Press Submit to see results above the form, then export if needed.

Baseline selection for realistic planning

The calculator starts with a baseline duration that represents the core clearance timeline before adjustments. Choose Profile when you only know a typical course: Short 4 days, Typical 7 days, Extended 14 days, or Chronic 30 days. These baselines act as anchors for scenario planning, staffing, and follow‑up sampling cadence.

Ct decay method for threshold timing

If you track Ct values, baseline days are computed as (Threshold Ct − Initial Ct) ÷ (Ct increase per day). For example, an Initial Ct of 20, a Threshold Ct of 35, and a Ct rise of 1.5/day gives (35−20)/1.5 = 10.0 days. This yields an estimate. A faster Ct rise, such as 2.0/day, shortens the same scenario to 7.5 days.

Log10 copies decay for quantitative assays

For quantitative reporting, baseline days are (Initial log10 − Threshold log10) ÷ (log10 decay/day). Example: 7.2 log10 down to 3.0 log10 with a 0.45/day decline yields (7.2−3.0)/0.45 = 9.33 days. Use this method when labs provide calibrated concentrations rather than Ct. If decay improves to 0.60/day under therapy, the example becomes 7.0 days.

Adjustment factors that capture context

The baseline is multiplied by factors for assay interpretation, specimen type, immune status, age, symptom severity, therapy timing, and vaccination. Molecular detection uses 1.00, while culture proxy uses 0.65 to represent a shorter infectious window. Specimen multipliers range from 0.95 (saliva) to 1.40 (blood/serum). Immunocompetent is 1.00, mildly compromised 1.25, and severely compromised 1.80.

Therapy timing applies 0.75 (early), 0.88 (mid), or 0.95 (late), and vaccination applies 0.90 when up to date. Multiplying factors produces a combined coefficient displayed in the breakdown. For instance, 7 baseline days × 1.25 immune × 1.10 lower respiratory × 0.75 early therapy ≈ 7.2 days, before adding other adjustments.

Ranges, documentation, and exports

Because real trajectories vary, the tool reports a planning range at 0.75× to 1.35× the point estimate. Add a reference date to translate days into an approximate end date using a ceiling day count. Exports create a CSV for analysis pipelines and a PDF summary for clinical, lab, or program documentation. Keep exported files with assay cutoffs, sampling frequency, and any protocol notes for auditability.

FAQs

What does the assay interpretation setting change?

It switches between a detectable window (molecular testing) and a shorter infectious-window proxy (culture). The model applies multipliers of 1.00 and 0.65 respectively to the baseline before other factors.

Which calculation method should I use?

Use Profile when you lack lab trends, Ct decay when you have serial Ct values and a cutoff, and Log10 decay when you have calibrated concentrations. The best method is the one supported by your available data.

How do I choose Ct threshold and Ct change per day?

Use the lab’s reported cutoff when possible. Ct change per day is the average rise between tests; compute it from two results and divide by days between them, then refine as more points arrive.

Why do immune status and severity affect estimates?

Reduced immune function or higher clinical severity can slow viral clearance. The calculator reflects this by scaling the baseline duration with multipliers, allowing quick sensitivity checks across patient or cohort profiles.

How is the end date computed from the reference date?

If you enter a reference date, the tool adds the ceiling of the estimated days to that date. This provides a practical “around this day” marker rather than a fractional-day timestamp.

Can I treat this output as a clinical decision rule?

No. It is an educational planning model, not medical advice. Different pathogens, assays, sampling sites, and protocols can change timelines substantially. Use it for comparisons, and validate assumptions with local guidance.

Example data table

Fictional examples to demonstrate inputs and outputs.