Dear all,
1. On Wednesday 22nd February 2012, the RSS Leeds/Bradford local group will be hosting two talks on "The statistics of epidemics". The meeting will be held at room LT01, Roger Stevens Building, University of Leeds starting at 3:00pm, with refreshments from 2:30pm in the level 9 foyer of the School of Mathematics (see http://www.leeds.ac.uk/campusmap for directions).
No registration required for this event.
Further details can be found on our webpage:
http://tinyurl.com/rss-lba
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Dr. Sarah Fleming
Secretary/Treasurer, RSS Leeds/Bradford Local Group, Division of Biostatistics, LIGHT, School of Medicine, University of Leeds, Leeds, LS2 9JT, UK.
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1. Wednesday 22nd February, 3.00pm, University of Leeds.
The statistics of epidemics
Thomas House (University of Warwick)
What households tell us about the diseases that pass through them
Households are a natural unit for epidemiological data collection - after all, if you've knocked a door, you might as well try to recruit all the residents to your study. Mathematically, if you plot a graph with the number of cases of an infection in a household on the x-axis, and the probability of that number on the y-axis, then the probability distribution displayed often looks more like a 'u' than an 'n'. This fact, coupled with modern computationally intensive statistical methods, can be used to extract much more information from household-stratified datasets than can be obtained from aggregate data. Work applying this observation to the early transmission of influenza A H1N1pdm09 in Birmingham will be presented.
Valerie Isham (RSS President, University College London)
Epidemics and rumours: the effect of network structure on transmission dynamics
The basic (SIR) epidemic model for the spread of infection in a homogeneously-mixing population is a special case of a more general stochastic model used for the spread of information (a `rumour`). In both cases it is well known that there is a threshold for widespread transmission.
More generally, for both epidemics and rumours, there is particular interest in using a network to represent population structure. This ensures that some pairs of individuals are never in contact, and direct spread between them cannot occur. Natural applications are to the spread of infection or information on social networks.
In this talk, I will review simple epidemic and rumour models, and describe networks generated by a range of random mechanisms. I will then discuss the effect of different network structures on the transmission dynamics of epidemics or rumours on networks and, in particular, the effect of different network properties on thresholds for widespread transmission.
The meeting will be held Leeds University Roger Stevens Building in room LT01 at 3pm with refreshments from 2:30 in the level 9 foyer of the School of Mathematics.
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