Estimation of hidden carriers of infectious diseases

Hoff, Vincent

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https://hdl.handle.net/2142/115181 Copy

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

Keyword(s)

• COVID-19, pandemic
• infectious diseases
• chao estimator
• bootstrap
• jackknife
• SAIRS

Language

en

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.

Graduation Semester

2022-05

Type of Resource

text

Copyright and License Information

Copyright 2022 Vincent Hoff

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