Addressing the problem of lack of representativeness on syndromic surveillance schemes

Isabel Natário; M. Lucília Carvalho

Discussiones Mathematicae Probability and Statistics (2009)

  • Volume: 29, Issue: 2, page 169-183
  • ISSN: 1509-9423

Abstract

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A major concern with some contagious diseases has recently led to an enormous effort to monitor population health status by several different means. This work presents a modeling approach to overcome this poor data characteristic, allowing its use for the estimation of the true population disease picture. We use a state space model, where we run two processes in parallel - a process describing the non observable states of the population concerning the presence/absence of disease, and an observational process resulting from the monitoring. We then use resampling importance sampling estimation techniques, in a Bayesian framework, which enables us to estimate the population states and, thus, the corresponding disease incidence curves.

How to cite

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Isabel Natário, and M. Lucília Carvalho. "Addressing the problem of lack of representativeness on syndromic surveillance schemes." Discussiones Mathematicae Probability and Statistics 29.2 (2009): 169-183. <http://eudml.org/doc/277025>.

@article{IsabelNatário2009,
abstract = { A major concern with some contagious diseases has recently led to an enormous effort to monitor population health status by several different means. This work presents a modeling approach to overcome this poor data characteristic, allowing its use for the estimation of the true population disease picture. We use a state space model, where we run two processes in parallel - a process describing the non observable states of the population concerning the presence/absence of disease, and an observational process resulting from the monitoring. We then use resampling importance sampling estimation techniques, in a Bayesian framework, which enables us to estimate the population states and, thus, the corresponding disease incidence curves. },
author = {Isabel Natário, M. Lucília Carvalho},
journal = {Discussiones Mathematicae Probability and Statistics},
keywords = {syndromic surveillance; state space models; importance sampling},
language = {eng},
number = {2},
pages = {169-183},
title = {Addressing the problem of lack of representativeness on syndromic surveillance schemes},
url = {http://eudml.org/doc/277025},
volume = {29},
year = {2009},
}

TY - JOUR
AU - Isabel Natário
AU - M. Lucília Carvalho
TI - Addressing the problem of lack of representativeness on syndromic surveillance schemes
JO - Discussiones Mathematicae Probability and Statistics
PY - 2009
VL - 29
IS - 2
SP - 169
EP - 183
AB - A major concern with some contagious diseases has recently led to an enormous effort to monitor population health status by several different means. This work presents a modeling approach to overcome this poor data characteristic, allowing its use for the estimation of the true population disease picture. We use a state space model, where we run two processes in parallel - a process describing the non observable states of the population concerning the presence/absence of disease, and an observational process resulting from the monitoring. We then use resampling importance sampling estimation techniques, in a Bayesian framework, which enables us to estimate the population states and, thus, the corresponding disease incidence curves.
LA - eng
KW - syndromic surveillance; state space models; importance sampling
UR - http://eudml.org/doc/277025
ER -

References

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