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...

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Detalles Bibliográficos
Autores principales: Athreya, Siva, Babu, Giridhara R., Iyer, Aniruddha, S., Mohammed Minhaas B., Rathod, Nihesh, Shriram, Sharad, Sundaresan, Rajesh, Vaidhiyan, Nidhin Koshy, Yasodharan, Sarath
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer India 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524406/
https://www.ncbi.nlm.nih.gov/pubmed/34690461
http://dx.doi.org/10.1007/s13571-021-00267-w
Descripción
Sumario: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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