Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/215669
Authors: 
Boysen-Hogrefe, Jens
Stamer, Vincent
Year of Publication: 
2020
Series/Report no.: 
Kiel Working Paper No. 2152
Abstract: 
We provide a calculation tool to assess the properties of a maximumlikelihood (ML) estimator that extrapolates the true prevalence of an infectious disease from a random sample. The tools allow the researcher to correct for the specificity and sensitivity of the underlying medical test, calculate the standard deviation of the estimator and to plan the needed sample size. This document explains the underlying methods of the calculation tools and provides instructions for their proper use. We apply an adaption of the epidemiological SEIR-model to show that ML-estimators from random sampling tests provide a more realistic rate of infection than common approaches.
Subjects: 
Infectious diseases
random sampling
maximum-likelihood
SEIR-model
Document Type: 
Working Paper

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