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MECHANISTIC AND STATISTICAL MODELS OF SKIN DISEASE TRANSMISSION

Part of: Parametric inference Applications - Dynamical systems and ergodic theory Physiological, cellular and medical topics

Published online by Cambridge University Press:  16 October 2019

MICHAEL J. LYDEAMORE Open the ORCID record for MICHAEL J. LYDEAMORE [Opens in a new window]
MICHAEL J. LYDEAMORE*
Affiliation:
Department of Infectious Diseases, Monash University, Prahran, Victoria 3181, Australia email [email protected]
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Abstract

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Keywords

epidemiologycomputational biologyBayesian inferencedynamical systems

MSC classification

Primary: 92C60: Medical epidemiology
Secondary: 37N25: Dynamical systems in biology 62F15: Bayesian inference
Type
Abstracts of Australasian PhD Theses
Information
Bulletin of the Australian Mathematical Society , Volume 101 , Issue 1 , February 2020 , pp. 174 - 176
Copyright
© 2019 Australian Mathematical Publishing Association Inc. 

Footnotes

Thesis submitted to the University of Melbourne in November 2018; degree awarded on 14 March 2019; supervisors James McCaw, Jodie McVernon and Patricia Campbell.

References

Lydeamore, M. J., Campbell, P. T., Cuningham, W., Andrews, R. M., Kearns, T., Clucas, D., Dhurrkay, R. G., Carapetis, J., Tong, S. Y. C. and McCaw, J. M. et al. , ‘Calculation of the age of the first infection for skin sores and scabies in five remote communities in northern Australia’, Epidemiol. Infect. 146 (2018), 1194–1201.Google Scholar
Lydeamore, M. J., Campbell, P. T., Price, D. J., Wu, Y., Marcato, A. J., Cuningham, W., Carapetis, J. R., Andrews, R. M., McDonald, M. I. and McVernon, J. et al. , ‘Estimation of the force of infection and infectious period of skin sores in remote Australian communities using interval-censored data’, Preprint, bioRxiv, 2019.Google Scholar
Lydeamore, M. J., Campbell, P. T., Regan, D. G., Tong, S. Y. C., Andrews, R. M., Steer, A. C., Romani, L., Kaldor, J. M., McVernon, J. and McCaw, J. M., ‘A biological model of scabies infection dynamics and treatment informs mass drug administration strategies to increase the likelihood of elimination’, Math. Biosci. 309 (2018), 163–173.Google Scholar