Timo Smieszek "Network Epidemiology: Unravelling Infectious Disease Dynamics using Contact Network Data."
A large number of different pathogens require (social) interaction in order to be transmitted from an infected to a susceptible host. The dynamics of many sexually transmitted diseases and droplet transmitted diseases in humans, as well as various infectious diseases of livestock and wild animals, are all better understood because of monitoring and modelling the interaction between the respective hosts. Here, I will concentrate on pathogens that are transmitted via droplets.
In my seminar, I will touch the question how ‘potentially contagious contact’ has been defined for various diseases and how such contacts can be measured. I will contrast different data collection methods and elucidate their strengths and weaknesses, particularly measurement errors that are specific to these methods. Further, I will discuss briefly whether the existing contact definitions make sense and what the research needs in this area are.
Since measuring contacts among hosts (be it humans or animals) is very costly and requires early preparation and planning, I will show that readily available dataset – like class schedules at schools, organisational charts of companies, or floor plans – can serve as proxies for detailed network data and may allow to answer some questions of public health relevance.
As a final element of this tour d’horizon of network epidemiological concepts, I intend to show that not only the configuration of contacts, but also the configuration of host characteristics within such a network can affect disease spread. My former colleagues at the Pennsylvania State University and I were able to show that vaccination can be assortative: We found at a US high school that individuals who were not vaccinated against seasonal influenza were clustered in the school’s contact network. Such a clustering of non-vaccinated individuals diminishes the effects of herd immunity.
Date: 26.02.2014, 17:15
Helmholtz-Centre for Infection Research
Building and room
Senior Mathematical Modeller
Modelling and Economics Unit, Public Health England, London, UK
Department of Infectious Disease Epidemiology, Imperial College, London, UK