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Estimating the undetected infections in the Covid-19 outbreak by harnessing capture-recapture methods (preprint)
medrxiv; 2020.
Preprint
in English
| medRxiv | ID: ppzbmed-10.1101.2020.04.20.20072629
ABSTRACT
A major open question, affecting the policy makers decisions, is the estimation of the true size of COVID-19 infections. Most of them are undetected, because of a large number of asymptomatic cases. We provide an efficient, easy to compute and robust lower bound estimator for the number of undetected cases. A "modified" version of the Chao estimator is proposed, based on the cumulative time-series distribution of cases and deaths. Heterogeneity has been accounted for by assuming a geometrical distribution underlying the data generation process. An (approximated) analytical variance formula has been properly derived to compute reliable confidence intervals at 95%. An application to Austrian situation is provided and results from other European Countries are mentioned in the discussion.
Full text:
Available
Collection:
Preprints
Database:
medRxiv
Main subject:
Death
/
COVID-19
Language:
English
Year:
2020
Document Type:
Preprint
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