Identification and Estimation of Undetected COVID-19 Cases Using Testing Data from Iceland   [open pdf - 396KB]

From the Abstract: "In the early stages of the COVID-19 [coronavirus disease 2019] pandemic, international testing efforts tended to target individuals whose symptoms and/or jobs placed them at a high presumed risk of infection. Testing regimes of this sort potentially result in a high proportion of cases going undetected. Quantifying this parameter, which we refer to as the undetected rate, is an important contribution to the analysis of the early spread of the SARS-CoV-2 [severe acute respiratory syndrome coronavirus 2] virus. We show that partial identification techniques can credibly deal with the data problems that common COVID-19 testing programs induce (i.e. excluding quarantined individuals from testing and low participation in random screening programs). We use public data from two Icelandic testing regimes during the first month of the outbreak and estimate an identified interval for the undetected rate. Our main approach estimates that the undetected rate was between 89% and 93% before the medical system broadened its eligibility criteria and between 80% and 90% after."

Report Number:
NBER Working Paper No. 27528; National Bureau of Economic Research Working Paper No. 27528
2020 Karl M. Aspelund, Michael C. Droste, James H. Stock, and Christopher D. Walker. Posted here with permission. Documents are for personal use only and not for commercial profit.
Retrieved From:
National Bureau of Economic Research: https://www.nber.org/
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