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Adaptive cluster sampling-based design for estimating COVID-19 cases with random samples
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Adaptive cluster sampling-based design for estimating COVID-19 cases with random samples
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Journal Article
Adaptive cluster sampling-based design for estimating COVID-19 cases with random samples
2021
Overview
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.
Publisher
Current Science Association
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