Author: Daniel B Larremore; Bailey K Fosdick; Kate M Bubar; Sam Zhang; Stephen M Kissler; C. Jessica E. Metcalf; Caroline Buckee; Yonatan Grad
Title: Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys Document date: 2020_4_20
ID: c4cs14ja_17
Snippet: Strategic sample allocation improves estimates. The flexible framework described in Fig. 1 enables the calculation of sample sizes for different serological survey designs. To calculate the number of tests required to achieve a seroprevalence estimate with a specified tolerance for uncertainty, and to allocate tests according to a specific subpopulation or in the context of a particular intervention, we treated the eventual estimate uncertainty a.....
Document: Strategic sample allocation improves estimates. The flexible framework described in Fig. 1 enables the calculation of sample sizes for different serological survey designs. To calculate the number of tests required to achieve a seroprevalence estimate with a specified tolerance for uncertainty, and to allocate tests according to a specific subpopulation or in the context of a particular intervention, we treated the eventual estimate uncertainty as a framework output and then sought to minimize it by improving the allocation of samples (Fig. 1, dashed arrow) .
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