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@ARTICLE{Fuhrmann:884065,
author = {Fuhrmann, Jan and Barbarossa, Maria Vittoria},
title = {{T}he significance of case detection ratios for predictions
on the outcome of an epidemic - a message from mathematical
modelers},
journal = {Archives of public health},
volume = {78},
number = {1},
issn = {2049-3258},
address = {Bruxelles},
publisher = {Archives},
reportid = {FZJ-2020-03074},
pages = {63},
year = {2020},
abstract = {In attempting to predict the further course of the novel
coronavirus disease (COVID-19) pandemic caused by
SARS-CoV-2, mathematical models of different types are
frequently employed and calibrated to reported case numbers.
Among the major challenges in interpreting these data is the
uncertainty about the amount of undetected infections, or
conversely: the detection ratio. As a result, some models
make assumptions about the percentage of detected cases
among total infections while others completely neglect
undetected cases. Here, we illustrate how model projections
about case and fatality numbers vary significantly under
varying assumptions on the detection ratio. Uncertainties in
model predictions can be significantly reduced by
representative testing, both for antibodies and active virus
RNA, to uncover past and current infections that have gone
undetected thus far.},
cin = {JSC},
ddc = {610},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {511 - Computational Science and Mathematical Methods
(POF3-511)},
pid = {G:(DE-HGF)POF3-511},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:32685147},
UT = {WOS:000553302200001},
doi = {10.1186/s13690-020-00445-8},
url = {https://juser.fz-juelich.de/record/884065},
}