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

Author

Listed:
  • Siva Athreya

    (Indian Statistical Institute)

  • Giridhara R. Babu

    (Indian Institute of Public Health)

  • Aniruddha Iyer

    (Indian Institute of Science)

  • Mohammed Minhaas B. S.

    (Indian Institute of Science)

  • Nihesh Rathod

    (Indian Institute of Science)

  • Sharad Shriram

    (Indian Institute of Science)

  • Rajesh Sundaresan

    (Indian Institute of Science)

  • Nidhin Koshy Vaidhiyan

    (Indian Institute of Science)

  • Sarath Yasodharan

    (Indian Institute of Science)

Abstract

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.

Suggested Citation

  • Siva Athreya & Giridhara R. Babu & Aniruddha Iyer & Mohammed Minhaas B. S. & Nihesh Rathod & Sharad Shriram & Rajesh Sundaresan & Nidhin Koshy Vaidhiyan & Sarath Yasodharan, 2022. "COVID-19: Optimal Design of Serosurveys for Disease Burden Estimation," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 472-494, November.
    • Handle: RePEc:spr:sankhb:v:84:y:2022:i:2:d:10.1007_s13571-021-00267-w
    DOI: 10.1007/s13571-021-00267-w
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