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65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), Meeting of the Central European Network (CEN: German Region, Austro-Swiss Region and Polish Region) of the International Biometric Society (IBS)

06.09. - 09.09.2020, Berlin (online conference)

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A family of discrete frailty distributions for modelling heterogeneities in the transmission of infectious diseases

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  • Maximilian Bardo - Department of Medical Statistics, University Medical Center Goettingen, Göttingen, Germany
  • Niel Hens - I-BioStat, Data Science Institute, Hasselt University, Diepenbeek, BelgiumCentre for Health Economics Research and Modelling Infectious Diseases, Centre for the Evaluation of Vaccination, Vaccine & Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium
  • Steffen Unkel - Department of Medical Statistics, University Medical Center Goettingen, Göttingen, Germany

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), Meeting of the Central European Network (CEN: German Region, Austro-Swiss Region and Polish Region) of the International Biometric Society (IBS). Berlin, 06.-09.09.2020. Düsseldorf: German Medical Science GMS Publishing House; 2021. DocAbstr. 64

doi: 10.3205/20gmds269, urn:nbn:de:0183-20gmds2696

Published: February 26, 2021

© 2021 Bardo et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at http://creativecommons.org/licenses/by/4.0/.

Outline

Text

Frailty models provide a conceptually simple and appealing way of quantifying association between survival times and of representing heterogeneities resulting from factors which may be difficult or impossible to measure; one example are heterogeneities that are relevant for the transmission of infectious diseases. The frailty is often assumed to have a continuous distribution.

However, in some areas of application, discrete frailty distributions may be more appropriate. One such area is infectious diseases transmitted by sexual contact, in which heterogeneity could be represented by the number of sexual partners. We explore a family of discrete frailty distributions introduced by Farrington et al. [1]. This family is homogeneous in the sense that all distributions are discrete with the continuous gamma distribution as a limiting case. We propose methods of estimation for this family of densities and discuss issues of identifiability and model choice. Our methods are illustrated with applications to bivariate current status data obtained from serological surveys on human papilloma virus types [2].

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.

Outline

References

1.
Farrington CP, Unkel S, Anaya-Izquierdo K. The relative frailty variance and shared frailty models. Journal of the Royal Statistical Society Series B. 2012;74:673-696.
2.
Mollema L, de Melker HE, Hahne SJM, van Weert JWM, Berbers GAM, van der Klis FRM. PIENTER 2-project: second research project on the protection against infectious diseases offered by the national immunization programme in the Netherlands. Report 230421001. National Institute for Public Health and the Environment (RIVM); 2010.