Current Science

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During the COVID-19 pandemic, testing of all persons except those who are symptomatic, is not feasible due to shortage of facilities and staff. This article focuses on estimating the number of COVID-19-positive persons over a geographical domain. The Horvitz–Thompson and Hansen–Hurwitz type estimators under adaptive cluster sampling-based design have been suggested. Two case studies are discussed to demonstrate the performance of the estimators under certain assumptions. Advantages and limitations are also mentioned.

Keywords

Adaptive Cluster Sampling, COVID-19, Pandemic, Precise Estimation, Random Samples.
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