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SUMMARY:Theory and practice of infectious disease surveillance - Woolhouse
 \, M (University of Edinburgh)
DTSTART:20130821T090000Z
DTEND:20130821T093000Z
UID:TALK46751@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Surveillance is the first line of defence against infectious d
 isease outbreaks\, making the design of effective and efficient surveillan
 ce systems an important public health challenge. Both statistical and proc
 ess models of outbreak dynamics are potentially useful in this context\, b
 ut there have been relatively few applications of these tools to designing
  surveillance systems\, in marked contrast to the many and influential app
 lications to prevention and control programmes. Here\, I review efforts to
  fill this gap\, focussing on the design of so-called smart surveillance s
 ystems that incorporate knowledge of patterns of risk to target surveillan
 ce effort more efficiently. There are several examples where smart surveil
 lance systems have been shown to be considerably more efficient: post-epid
 emic surveillance for freedom from foot-and-mouth disease (5x more efficie
 nt)\; detection of new infections spreading through a network of hospitals
  (up to 8x). Designing surveillance systems is more challenging when signa
 l has to be separated from noise. This is important for understanding the 
 impact of vaccination on the detection of H5N1 influenza in poultry or the
  detection of pandemic influenza in the presence of seasonal influenza. Th
 ere is an even more difficult problem of identifying novel events\, e.g. u
 nusual clinical cases or outbreaks due to unrecognised\, unexpected or eve
 n completely new infectious diseases. This is being addressed by using dat
 a reduction methods to provide a benchmark for expected patterns of variat
 ion in clinical presentation or outbreak characteristics. Designing smart 
 surveillance systems presents a number of interesting challenges\, both in
  theory and in practice. The take home message from the various studies de
 scribed here is that model-based approaches have considerable potential to
  contribute to improving the effectiveness and efficiency of surveillance 
 systems\, to the benefit of both human and animal health.\n
LOCATION:Seminar Room 1\, Newton Institute
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