Estimation of hidden carriers of infectious diseases
Hoff, Vincent
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https://hdl.handle.net/2142/115181
Description
Title
Estimation of hidden carriers of infectious diseases
Author(s)
Hoff, Vincent
Issue Date
2022-04-27
Director of Research (if dissertation) or Advisor (if thesis)
Beck, Carolyn L.
Discipline
Industrial Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2022-10-31T12:51:17-05:00
Keyword(s)
COVID-19
pandemic
infectious diseases
chao estimator
bootstrap
jackknife
SAIRS
Language
eng
Abstract
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.
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