Estimating the size of undetected cases of the COVID-19 outbreak in Europe: an upper bound estimator

DOI10.1515/EM-2020-0024zbMath1466.92203OpenAlexW3118914877MaRDI QIDQ829925

Heinz Holling, Antonello Maruotti, Irene Rocchetti, Dankmar Boehning

Publication date: 6 May 2021

Published in: Epidemiologic Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/em-2020-0024

zbMATH Keywords

geometric distributioncapture-recapture methodsCOVID-19Chao's lower bound

Mathematics Subject Classification ID

Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (3)

Mortality containment vs. economics opening: optimal policies in a SEIARD model ⋮ A statistical model for the dynamics of COVID‐19 infections and their case detection ratio in 2020 ⋮ The Role of Asymptomatic Infections in the COVID-19 Epidemic via Complex Networks and Stability Analysis

Uses Software

• EstimateS
• asymptor

Cites Work

• Unnamed Item
• Capture-recapture estimation based upon the geometric distribution allowing for heterogeneity
• Implementing the parametric bootstrap in capture--recapture models with continuous co\-vari\-ates.
• Estimating Population Size for Sparse Data in Capture-Recapture Experiments
• Estimating the Population Size for Capture-Recapture Data with Unequal Catchability
• Thirty years of progeny from Chao’s inequality: Estimating and comparing richness with incidence data and incomplete sampling
• Uncertainty estimation in heterogeneous capture–recapture count data
• Upper bound estimators of the population size based on ordinal models for capture‐recapture experiments

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