2026-09-21T10:48:16Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/115181 2023-07-11 col_2142_5131 col_2142_16359 com_2142_5130 com_2142_16358 com_2142_234

Beck, Carolyn L. 2022-05 application/pdf Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-10-31 without embargo terms This Thesis was approved for publication on 2022-04-27 at 16:16. The student, Vincent Hoff, accepted the attached license on 2022-04-22 at 08:59. DSpace SAF Submission Ingestion Package generated from Vireo submission #17914 on 2022-10-31 at 12:20:51 The student, Vincent Hoff, submitted this Thesis for approval on 2022-04-22 at 09:10. dissertation/thesis Estimation of hidden carriers of infectious diseases Hoff, Vincent 2022-04-27 2022-10-31T12:51:17-05:00 COVID-19 pandemic infectious diseases chao estimator bootstrap jackknife SAIRS We consider the general problem of estimating missing information in a given dataset. We focus specifically on the problem of estimating the asymptomatic segment of the population that is COVID-19 infected, given datasets for which subjects have self-selected to be tested, that is, the data do not comprise a random sample. We present several methods to estimate the number of persons infected with COVID-19 that are not captured by traditional methods. We first present a simple comparison of incidence numbers between datasets with varying levels of completion, approximating different degrees of random sampling. We then use the Chao estimator to obtain a ratio of total cases to observed cases. Finally, we employ several other methods to compare against those results, such as a second order jackknife, a SAIRS epidemic model, and an incidence rate. text eng https://hdl.handle.net/2142/115181 Copyright 2022 Vincent Hoff Industrial Engineering University of Illinois at Urbana-Champaign Thesis M.S. Industrial & Enterprise Sys Eng