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We present a new analysis of relationships between disease incidence and theprevalence of an experimentally defined state of `recent infection'. This leadsto a clean separation between biological parameters (properties of diseaseprogression as reflected in a test for recent infection), which need to becalibrated, and epidemiological state variables, which are estimated in across-sectional survey. The framework takes into account the possibility thatdetails of the assay and host/pathogen chemistry leave a (knowable) fraction ofthe population in the recent category for all times. This systematicallyaddresses an issue which is the source of some controversy about theappropriate use of the BED assay for defining recent HIV infection. Analysis ofrelative contributions of error arising variously from statisticalconsiderations and simplifications of general expressions indicate thatstatistical error dominates heavily over all sources of bias for realisticepidemiological and biological scenarios. Numerical calculations validate theapproximations made in analytical relations.

Relating Recent Infection Prevalence to Incidence with a Sub-population of Non-progressors