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Timo Smieszek
Selected publications
Smieszek, T., Burri, E.U., Scherzinger, R., & Scholz, R.W. (online first). Collecting close-contact social mixing data with contact diaries: reporting errors and biases. Epidemiology and Infection. doi:10.1017/S0950268811001130
Smieszek, T., Balmer, M., Hattendorf, J., Axhausen, K.W., Zinsstag, J., & Scholz, R.W. (2011). Reconstructing the 2003/2004 H3N2 influenza epidemic in Switzerland with a spatially explicit, individual-based model. BMC Infectious Diseases, 11: 115. doi:10.1186/1471-2334-11-115
Smieszek, T. (2009). A mechanistic model of infection: why duration and intensity of contacts should be included in models of disease spread. Theoretical Biology & Medical Modelling, 6: 25. doi:10.1186/1742-4682-6-25
Fiebig, L., Smieszek, T., Saurina, J., Hattendorf, J., & Zinsstag, J. (2009). Contacts between poultry farms, their spatial dimension and their relevance for avian influenza preparedness. Geospatial Health, 4: 79–95.
Smieszek, T., Fiebig, L., & Scholz, R.W. (2009). Models of epidemics: when contact repetition and clustering should be included. Theoretical Biology & Medical Modelling, 6: 11. doi:10.1186/1742-4682-6-11
Research interests
I am environmental scientist by training and I am conducting research at the interface of the social sciences and biology. I want to understand how human behavior shapes the spread of infectious diseases; particularly, how the interplay of human factors and pathogen properties results in the patterns of disease spread that we can observe.
So far, my research has built on two methodological pillars: On the one hand, I conceived computer models that helped to gain a better understanding of how the arrangement and the quality of contacts among hosts impact on disease spread. On the other hand, I worked empirically by measuring epidemiologically relevant network structures using contact diaries and questionnaires.
In the coming years I will contribute to the collection of contact data with a combination of novel survey techniques and I want to bridge infection surveillance data, empirical contact data and biological knowledge by means of modeling.
