Test sensitivity is secondary to frequency and turnaround time for COVID-19 surveillance

TLDR

The COVID‑19 pandemic has created a public health crisis, and because SARS‑CoV‑2 can spread from pre‑symptomatic, symptomatic, and asymptomatic individuals, robust surveillance—often centered on virus testing—is essential for reopening societies and controlling spread, with viral load kinetics influencing detection timing. We model surveillance effectiveness considering test sensitivities, frequency, and sample‑to‑answer reporting time. The model is based on viral load kinetics. Effective surveillance depends largely on testing frequency and reporting speed, and is only marginally improved by high test sensitivity; thus surveillance should prioritize accessibility, frequency, and sample‑to‑answer time, with analytical limits of detection being secondary.

Abstract

The COVID-19 pandemic has created a public health crisis. Because SARS-CoV-2 can spread from individuals with pre-symptomatic, symptomatic, and asymptomatic infections, the re-opening of societies and the control of virus spread will be facilitated by robust surveillance, for which virus testing will often be central. After infection, individuals undergo a period of incubation during which viral titers are usually too low to detect, followed by an exponential viral growth, leading to a peak viral load and infectiousness, and ending with declining viral levels and clearance. Given the pattern of viral load kinetics, we model surveillance effectiveness considering test sensitivities, frequency, and sample-to-answer reporting time. These results demonstrate that effective surveillance depends largely on frequency of testing and the speed of reporting, and is only marginally improved by high test sensitivity. We therefore conclude that surveillance should prioritize accessibility, frequency, and sample-to-answer time; analytical limits of detection should be secondary.