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BEGIN:VEVENT
DTSTAMP:20260612T113547Z
DTSTART;VALUE=DATE-TIME:20161012T120000
DTEND;VALUE=DATE-TIME:20161012T130000
SUMMARY:Complexity Forum: Mike Tildesley (ÌÇÐÄTV)
TZID:Europe/London
UID:20161012-094d434553e1cda701542ed79e5d52ad@warwick.ac.uk
CREATED:20160419T140603Z
DESCRIPTION:Models of infectious diseases in the presence of uncertainty 
 - predicting risk and informing policy Mathematical models are regularly
  used in the event of infectious disease outbreaks to predict future epi
 demic behaviour and the impact of intervention strategies. However\, suc
 h models often have to make predictions when data are not readily availa
 ble to inform model parameters. Despite this\, policy makers require rap
 id advice to ensure that any control policy that is implemented can have
  the greatest effect possible. In this presentation\, we will discuss th
 e ability of livestock infectious disease models to make "robust" predic
 tions in the absence of up to date epidemiological and demographic data.
  Our research specifically focuses upon adaptive management - a novel in
 tervention strategy that "adapts" to accrual of information to ensure th
 at the control strategy that is implemented is optimal\, given the infor
 mation that is available at that point in the outbreak. Such a strategy 
 can reduce the economic impact of future outbreaks of livestock infectio
 us disease.
LOCATION:D1.07
CATEGORIES:forum
LAST-MODIFIED:20161011T185113Z
ORGANIZER;CN=Karen McKinley:
END:VEVENT
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