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Reviews on Environmental Health

Editor-in-Chief: Carpenter, David O. / Sly, Peter

Editorial Board: Brugge, Doug / Edwards, John W. / Field, R.William / Garbisu, Carlos / Hales, Simon / Horowitz, Michal / Lawrence, Roderick / Maibach, H.I. / Shaw, Susan / Tao, Shu / Tchounwou, Paul B.


IMPACT FACTOR 2018: 1.616

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Source Normalized Impact per Paper (SNIP) 2018: 0.664

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2191-0308
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Volume 31, Issue 1

Issues

Bayesian networks in infectious disease eco-epidemiology

Colleen L. Lau
  • Corresponding author
  • Children’s Health and Environment Program, L7 Child Health Research Centre, The University of Queensland, 62 Graham St, South Brisbane, Queensland 4101, Australia
  • Queensland Children’s Medical Research Institute, Centre for Children’s Health Research, Brisbane, Australia
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Carl S. Smith
Published Online: 2016-01-20 | DOI: https://doi.org/10.1515/reveh-2015-0052

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.

Keywords: Bayesian networks; eco-epidemiology; infectious disease epidemiology; leptospirosis; zoonoses

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About the article

Corresponding author: Colleen L. Lau, Children’s Health and Environment Program, L7 Child Health Research Centre, The University of Queensland, 62 Graham St, South Brisbane, Queensland 4101, Australia; and Queensland Children’s Medical Research Institute, Centre for Children’s Health Research, Brisbane, Australia, E-mail:


Received: 2015-10-15

Accepted: 2015-10-16

Published Online: 2016-01-20

Published in Print: 2016-03-01


Citation Information: Reviews on Environmental Health, Volume 31, Issue 1, Pages 173–177, ISSN (Online) 2191-0308, ISSN (Print) 0048-7554, DOI: https://doi.org/10.1515/reveh-2015-0052.

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