Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/227312
Authors: 
Wälde, Klaus
Year of Publication: 
2020
Series/Report no.: 
IZA Discussion Papers No. 13785
Abstract: 
Background: Public health measures and private behaviour are based on reported numbers of SARS-CoV-2 infections. Some argue that testing influences the confirmed number of infections. Objectives/Methods: Do time series on reported infections and the number of tests allow one to draw conclusions about actual infection numbers? A SIR model is presented where the true numbers of susceptible, infectious and removed individuals are unobserved. Testing is also modelled. Results: Official confirmed infection numbers are likely to be biased and cannot be compared over time. The bias occurs because of different reasons for testing (e.g. by symptoms, representative or testing travellers). The paper illustrates the bias and works out the effect of the number of tests on the number of reported cases. The paper also shows that the positive rate (the ratio of positive tests to the total number of tests) is uninformative in the presence of non-representative testing. Conclusions: A severity index for epidemics is proposed that is comparable over time. This index is based on Covid-19 cases and can be obtained if the reason for testing is known.
Subjects: 
SIR model
(correcting the) bias
reported number of CoV-2 infections
number of tests
COVID-19
unbiased epidemiological severity index
JEL: 
I18
C23
Document Type: 
Working Paper

Files in This Item:
File
Size
376.8 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.