Bounding Infection Prevalence by Bounding Selectivity and Accuracy of Tests: With Application to Early COVID-19
نویسندگان
چکیده
Abstract I propose novel partial identification bounds on infection prevalence from information test rate and yield. The approach utilizes user-specified (i) accuracy (ii) the extent to which tests are targeted, formalized as restriction effect of true status odds ratio getting tested thereby embeddable in logit specifications. motivating application is COVID-19 pandemic but strategy may also be useful elsewhere. Evaluated data pandemic’s early stage, even weakest reasonably informative. Notably, contrast speculations that were widely reported at time, they place fatality for Italy well above one influenza by mid-April.
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ژورنال
عنوان ژورنال: Econometrics Journal
سال: 2021
ISSN: ['1368-423X', '1367-423X', '1368-4221']
DOI: https://doi.org/10.1093/ectj/utab024