Bayesian networks in infectious disease eco-epidemiology.

Abstract:

:Globally, infectious diseases are responsible for a significant burden on human health. Drivers of disease transmission depend on interactions between humans, the environment, vectors, carriers, and pathogens; transmission dynamics are therefore potentially highly complex. Research in infectious disease eco-epidemiology has been rapidly gaining momentum because of the rising global importance of disease emergence and outbreaks, and growing understanding of the intimate links between human health and the environment. The scientific community is increasingly recognising the need for multidisciplinary translational research, integrated approaches, and innovative methods and tools to optimise risk prediction and control measures. Environmental health experts have also identified the need for more advanced analytical and biostatistical approaches to better determine causality, and deal with unknowns and uncertainties inherent in complex systems. In this paper, we discuss the use of Bayesian networks in infectious disease eco-epidemiology, and the potential for developing dynamic tools for public health decision-making and improving intervention strategies.

journal_name

Rev Environ Health

authors

Lau CL,Smith CS

doi

10.1515/reveh-2015-0052

subject

Has Abstract

pub_date

2016-03-01 00:00:00

pages

173-7

issue

1

eissn

0048-7554

issn

2191-0308

pii

/j/reveh.ahead-of-print/reveh-2015-0052/reveh-2015

journal_volume

31

pub_type

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