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of 54
pro vyhledávání: '"Hoehle, Michael"'
The real-time analysis of infectious disease surveillance data, e.g., in the form of a time-series of reported cases or fatalities, is essential in obtaining situational awareness about the current dynamics of an adverse health event such as the COVI
Externí odkaz:
http://arxiv.org/abs/2202.04569
Publikováno v:
In Zeitschrift fuer Evidenz, Fortbildung und Qualitaet im Gesundheitswesen May 2024 186:18-26
Coronavirus disease 2019 (COVID-19) is associated with a very high number of casualties in the general population. Assessing the exact magnitude of this number is a non-trivial problem, as relying only on officially reported COVID-19 associated fatal
Externí odkaz:
http://arxiv.org/abs/2106.13827
Autor:
Allévius, Benjamin, Höhle, Michael
An expectation-based scan statistic is proposed for the prospective monitoring of spatio-temporal count data with an excess of zeros. The method, which is based on an outbreak model for the zero-inflated Poisson distribution, is shown to be superior
Externí odkaz:
http://arxiv.org/abs/1712.09188
Autor:
Allévius, Benjamin, Höhle, Michael
This chapter surveys univariate and multivariate methods for infectious disease outbreak detection. The setting considered is a prospective one: data arrives sequentially as part of the surveillance systems maintained by public health authorities, an
Externí odkaz:
http://arxiv.org/abs/1711.08960
Publikováno v:
Biometrics 68, 607--616
A novel point process model continuous in space-time is proposed for quantifying the transmission dynamics of the two most common meningococcal antigenic sequence types observed in Germany 2002-2008. Modelling is based on the conditional intensity fu
Externí odkaz:
http://arxiv.org/abs/1508.05740
Publikováno v:
Journal of Statistical Software (2017); 77 (11): 1-55
The availability of geocoded health data and the inherent temporal structure of communicable diseases have led to an increased interest in statistical models and software for spatio-temporal data with epidemic features. The open source R package surv
Externí odkaz:
http://arxiv.org/abs/1411.0416
Publikováno v:
Journal of the Royal Statistical Society. Series C (Applied Statistics), 2005 Jan 01. 54(2), 349-366.
Externí odkaz:
https://www.jstor.org/stable/3592643
Akademický článek
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Publikováno v:
Clinical Infectious Diseases, 2016 Dec . 63(12), 1558-1563.
Externí odkaz:
https://www.jstor.org/stable/26373578