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SUMMARY:Detecting superspreaders in wildlife reservoirs of disease - Evand
 ro Konzen (University of Warwick)
DTSTART:20240228T140000Z
DTEND:20240228T150000Z
UID:TALK212773@talks.cam.ac.uk
CONTACT:Dr Ciara Dangerfield
DESCRIPTION:To better understand the dynamics of infectious diseases of wi
 ldlife\, it is crucial to be able to fit dynamic transmission models to ob
 served data in a robust and efficient way\, in order to estimate key epide
 miological parameters and generate well calibrated predictive information.
  In practice\, epidemiological events are at best only partially observed\
 , and as such it is necessary to infer missing information alongside the m
 odel parameters as part of the inference routine\, requiring computational
 ly intensive inference algorithms where computational load increases non-l
 inearly with population size and with increased dimensionality of the hidd
 en states.\nWith this in mind\, we implement a recently proposed individua
 l forward filtering backward sampling algorithm to fit a complex individua
 l-based epidemic model to data from a large-scale longitudinal study of bo
 vine tuberculosis in badgers. This data set\, from Woodchester Park in sou
 th-west England\, comprises >2\,000 badgers across 34 social groups over a
  40-year period. We deal with many complexities typical to endemic wildlif
 e disease systems: incomplete sampling of individuals over time (through c
 apture-mark-recapture events)\, the use of multiple diagnostic tests\, spa
 tial meta-population structures\, and non-Markovian demographic aspects su
 ch as age-dependent mortality rates (with censoring)\, all alongside a hid
 den stochastic compartmental model of disease spread. The method produces 
 full posterior distributions for the parameters\, and predictive distribut
 ions for the hidden states over time for each individual\, and fits in jus
 t a few hours on a desktop machine.\nWe also propose a novel individual-le
 vel reproduction number which accounts for major sources of uncertainty of
  the disease system\, and from it provide quantitative evidence for the pr
 esence of superspreader badgers in Woodchester Park. The inference framewo
 rk is very flexible\, and could be applied to other individual-level disea
 se systems\, and we will discuss future extensions to explore further impo
 rtant epidemiological questions.
LOCATION:Zoom
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