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Bounding infection prevalence by bounding selectivity and accuracy of tests: with application to early COVID-19

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  • Jörg Stoye

Abstract

SummaryI propose novel partial identification bounds on infection prevalence from information on test rate and test yield. The approach utilizes user-specified bounds on (i) test accuracy and (ii) the extent to which tests are targeted, formalized as restriction on the effect of true infection status on the odds ratio of getting tested and thereby embeddable in logit specifications. The motivating application is to the COVID-19 pandemic but the strategy may also be useful elsewhere. Evaluated on data from the pandemic’s early stage, even the weakest of the novel bounds are reasonably informative. Notably, and in contrast to speculations that were widely reported at the time, they place the infection fatality rate for Italy well above the one of influenza by mid-April.

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  • Jörg Stoye, 2022. "Bounding infection prevalence by bounding selectivity and accuracy of tests: with application to early COVID-19," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 1-14.
    • Handle: RePEc:oup:emjrnl:v:25:y:2022:i:1:p:1-14.
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    File URL: http://hdl.handle.net/10.1093/ectj/utab024
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    1. Manski, Charles F. & Molinari, Francesca, 2021. "Estimating the COVID-19 infection rate: Anatomy of an inference problem," Journal of Econometrics, Elsevier, vol. 220(1), pages 181-192.
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    Cited by:

    1. Filip Obradovi'c, 2022. "Measuring Diagnostic Test Performance Using Imperfect Reference Tests: A Partial Identification Approach," Papers 2204.00180, arXiv.org, revised Aug 2024.
    2. Kitagawa, Toru & Wang, Guanyi, 2023. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," Journal of Econometrics, Elsevier, vol. 232(1), pages 109-131.
    3. Bollinger, Christopher R. & van Hasselt, Martijn, 2020. "Estimating the cumulative rate of SARS-CoV-2 infection," Economics Letters, Elsevier, vol. 197(C).

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