Respiratory Infections · Workflow Optimization · Lab Operations · Application Insights

Respiratory season surge: sizing assay inventory and staffing before the first wave

Published 10/06/2026

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Key takeaways

Respiratory surge planning is a pre-season exercise: a demand baseline from your own historical peaks, a deliberately tiered assay menu, two inventory buffers, staffing sized from hands-on bench time, and turnaround targets that are measured, not assumed.

Build the demand baseline from your own weekly volumes, not national averages.
Tier the menu: rapid triage, batched panels, and reserved broad syndromic testing.
Carry two inventory buffers — supply allocation and cold-chain discipline.
Size staffing from hands-on bench minutes against the peak-day model.

Target audienceLab Director, Operations, Procurement

Review and references

Source

Compiled from public manufacturer materials and regulatory sources. Not independently verified and not reviewed by a named clinician.

Published

2026-10-06

Updated

2026-10-06

Disclaimer

professional use

References

FAQ

Common questions

When should respiratory season planning start?

Six to eight weeks before typical local activity rises — most temperate-region laboratories start in late summer. Procurement lead times, not bench readiness, are usually the binding constraint.

Should we default to syndromic respiratory panels?

Rarely as a default. Syndromic panels earn their cost on complicated, immunocompromised, or epidemiologically unusual cases; high-volume triage is usually better served by rapid single-plex assays with a clear escalation path.

How much inventory is enough for peak week?

Enough to cover the modelled peak week plus a supply buffer for allocation constraints and a cold-chain buffer for excursions. Track days of cover, not box counts, and set a reorder trigger the bench can act on.

What is the most common planning mistake?

Sizing against average demand. Averages hide the peak week that consumes inventory and staffing simultaneously — plan against a percentile-day model with an explicit STAT and add-on allowance.