Investigating the Dark Figure of COVID-19 Cases in Austria: Borrowing From the Decode Genetics Study in Iceland

Austrian Journal of Statistics

article

Rainer Hirk¹  Gregor Kastner¹  Laura Vana¹ 

[1] Vienna University of Economics and Business

关键词: Comparative Study;    SARS-CoV-2;    Uncertainty Quantification;    Unreported Infections.;   

DOI  :  10.17713/ajs.v49i4.1142

学科分类：医学（综合）

来源: Austrian Statistical Society

【 摘 要 】

The number of undetected cases of SARS-CoV-2 infections is expected to be a multiple of the reported figures mainly due to the high ratio of asymptomatic infections and to limited availability of trustworthy testing resources. Relying on the deCODE study in Iceland, which offers large scale testing among the general population, we investigate the magnitude and uncertainty of the number of undetected cases COVID-19 cases in Austria. We formulate several scenarios relying on data on the number of COVID-19 cases which have been hospitalized, in intensive care, as well as on the number of deaths and positive tests in Iceland and Austria. We employ frequentist and Bayesian methods for estimating the dark figure in Austria based on the hypothesized scenarios and for accounting for the uncertainty surrounding this figure. Using data available on April 1, 2020, our study contains two main findings: First, we find the estimated number of infections to be on average around 8.35 times higher than the recorded number of infections. Second, the width of the uncertainty bounds associated with this figure depends highly on the statistical method employed. At a 95% level, lower bounds range from 3.96 to 6.83 and upper bounds range from 9.82 to 12.61. Overall, our findings confirm the need for systematic tests in the general population of Austria.

【 授权许可】

CC BY