Antiretroviral therapy stockouts in Ugandan fishing communities are typically analysed as supply-chain failures, yet their downstream consequences for viral suppression depend on how exposure is defined and how treatment interruption is measured. No observational data are used or claimed. Under a declared variance structure with between-cluster standard deviation of 6.0, residual standard deviation of 4.5 and intraclass correlation of 0.64, power was estimated across 2000 replications per design cell for cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points. The design requires 54 clusters to detect a 5-percentage-point effect at 80 per cent power. The analysis clarifies why stockout exposure cannot be treated as a binary facility-level attribute, specifies the identification assumptions that a target-trial emulation must satisfy, and shows how design operating characteristics constrain the sociological questions that can be answered with cluster-level data. The contribution is a methodological framework that aligns the measurement of stockout exposure with the causal question that medical sociology claims to ask.
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Lakot et al. (2026) studied this question.
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