Spatial information and aggregate data on the number of verified infected, either hospitalized or in compulsory quarantine, are utilized to improve a standard two-stage sampling design broadly adopted for studying human populations. The basic strategy, is based on spatially balanced sampling. The conditions for their efficiency are analytically proven. The relative advantages are shown through a simulation study.
Demetrio Falorsi, P., Nardelli, V., Arbia, G., Efficiency and feasibility of two stage sampling designs for estimating SARS-CoV-2 epidemic, Paper, in Sis 2022 - Book of Short Papers, (Caserta, 22-24 June 2022), Pearson, Roma 2022: 1096-1101 [https://hdl.handle.net/10807/325140]
Efficiency and feasibility of two stage sampling designs for estimating SARS-CoV-2 epidemic
Nardelli, Vincenzo;Arbia, Giuseppe
2022
Abstract
Spatial information and aggregate data on the number of verified infected, either hospitalized or in compulsory quarantine, are utilized to improve a standard two-stage sampling design broadly adopted for studying human populations. The basic strategy, is based on spatially balanced sampling. The conditions for their efficiency are analytically proven. The relative advantages are shown through a simulation study.
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