COVID-19:疾病负担估算血清调查的优化设计

Sankhya. Series B (2008) Pub Date : 2022-01-01 Epub Date: 2021-10-19 DOI:10.1007/s13571-021-00267-w
Siva Athreya, Giridhara R Babu, Aniruddha Iyer, Mohammed Minhaas B S, Nihesh Rathod, Sharad Shriram, Rajesh Sundaresan, Nidhin Koshy Vaidhiyan, Sarath Yasodharan
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引用次数: 1

摘要

我们提供了一种方法,通过这种方法,流行病学家可以为一项旨在估计人群疾病负担的调查得出最佳设计。对于具有给定预算C卢比的血清调查,一组具有成本、灵敏度和特异性的特定测试,我们展示了在四种不同情况下存在最佳设计,包括众所周知的C -最优设计。通过数值算例说明了所得结果的有效性。我们的结果适用于大范围的流行病学调查,假设估计的费雪信息矩阵满足统一的正定准则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

COVID-19: Optimal Design of Serosurveys for Disease Burden Estimation.

COVID-19: Optimal Design of Serosurveys for Disease Burden Estimation.

We provide a methodology by which an epidemiologist may arrive at an optimal design for a survey whose goal is to estimate the disease burden in a population. For serosurveys with a given budget of C rupees, a specified set of tests with costs, sensitivities, and specificities, we show the existence of optimal designs in four different contexts, including the well known c-optimal design. Usefulness of the results are illustrated via numerical examples. Our results are applicable to a wide range of epidemiological surveys under the assumptions that the estimate's Fisher-information matrix satisfies a uniform positive definite criterion.

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