How do CBP encounter counts translate into estimates of unique unauthorized entrants?

1. What “encounters” actually count and why they overstate unique arrivals

CBP defines encounters to include USBP Title 8 apprehensions, OFO Title 8 inadmissibles at ports of entry, and Title 42 expulsions, so the published totals mix different processing outcomes and modes of arrival rather than exclusively tallying successful unauthorized entries ^{[1] [3] [6]}. CBP and DHS explicitly note their encounter unit counts people encountered more than once during a reporting period multiple times, meaning repeat attempts by the same person inflate the headline figure ^[2]. CBP has acknowledged pandemic-era expulsions and repeat attempts increased repeat encounters, so “total encounters somewhat overstate the number of unique individuals arriving at the border” ^[7].

2. CBP’s “unique encounters” — the most direct internal correction

CBP sometimes publishes a separate “unique encounters” figure that it defines as persons not previously encountered in the prior 12 months; that metric is the agency’s closest internal attempt to count distinct individuals rather than contact events ^[4]. Monthly and regional updates have used that measure — for example CBP reported the number of unique individuals encountered along the Southwest border in specific months — and noted repeat encounters accounted for a measurable share of overall encounters ^[8]. Relying on CBP’s unique-encounter series is the most straightforward way to translate encounters into a lower-bound estimate of distinct persons when CBP provides it ^{[4] [8]}.

3. The DHS statistical approach: encounter totals + apprehension rate = estimated successful entries

When CBP does not publish unique-person counts, DHS and independent groups have used a statistical approach that combines reported encounters with an estimated apprehension (or detection) rate to infer how many crossings evaded capture; USAFacts explicitly replicated DHS’s methodology for national estimates using encounters and an apprehension-rate adjustment ^[5]. Conceptually, if the apprehension rate is A (the share of attempted crossings that result in apprehension/detection), then observed apprehensions ≈ A × total attempts, so estimated successful undetected entries ≈ total attempts × (1 − A). Using encounters and an independently estimated A lets analysts back out likely unique successful entries, but the result depends critically on the chosen A and whether encounters include expulsions or inadmissibles ^[5].

4. Key uncertainties, alternative viewpoints and institutional incentives

The approach hinges on two contested inputs: how CBP counts categories within “encounters” (ports versus between-ports, Title 42 expulsions, etc.) and what true apprehension/detection rate to apply; CBP’s encounters mix administrative and enforcement events which complicates any single formula ^{[1] [2]}. CBP has an institutional incentive to present both raw-encounter and unique-encounter figures to show operational workload and to highlight repeat attempts, while outside analysts may prefer statistical estimates of “successful entries” to judge border control effectiveness — each framing supports different policy narratives ^{[7] [5]}. Independent replications such as USAFacts follow DHS’s documented methodology but must make assumptions about apprehension rates that materially change outcomes ^[5].

5. Practical prescription for reliable estimates

The most defensible route is to use CBP’s published unique-encounter counts when available as the direct lower-bound on distinct people ^{[4] [8]}, and where those are missing apply a DHS/USAFacts-style correction: combine encounter totals with a transparently stated apprehension/detection rate to estimate undetected successful entries while clearly reporting the sensitivity of results to alternative A values ^[5]. Sources here do not provide a single universal A or a fully detailed DHS formula, so any numeric estimate must disclose those methodological assumptions ^{[5] [2]}.