Picture of fish in sea

Open Access research that uses mathematical models to solve ecological problems...

Solving a variety of ecological and biological problems is the focus of marine population modelling research conducted within the Department of Mathematics & Statistics. Here research deploys mathematical models to better understanding issues relating to fish stock management, ecosystem dynamics, ocean currents, and the effects of multispecies interactions within diverse marine ecosystems.

Research work in marine population modelling interfaces with a number of other key research specialisms, including mathematical biology, epidemiology and statistical informatics, where investigations are improving human understanding of the behaviour of infectious diseases, particularly in relation to animal infections; but also the modelling of complex biological processes such as antibiotic prodcution in actinobacteria.

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Group by: Publication Date | Item type | No Grouping
Jump to: 2019 | 2018 | 2017 | 2016 | 2015
Number of items: 8.

2019

Liang, Yanfeng and Greenhalgh, David (2019) Estimation of the expected number of cases of microcephaly in Brazil as a result of Zika. Mathematical Biosciences and Engineering, 16 (6). 8217–8242. ISSN 1547-1063

Liang, Y. and Ahmad Mohiddin, M. N. and Bahauddin, R. and Hidayatul, F. O. and Nazni, W. A. and Lee, H. L. and Greenhalgh, D. (2019) Modelling the effect of a novel autodissemination trap on the spread of dengue in Shah Alam and Malaysia. Computational and Mathematical Methods in Medicine, 2019. 1923479. ISSN 1748-6718

2018

Greenhalgh, David and Liang, Yanfeng and Nazni, Wasi Ahmad and Teoh, Guat-ney and Lee, Han Lim and Massad, Eduardo (2018) Modelling the effect of a novel auto-dissemination trap on the spread of dengue in high-rise condominia, Malaysia. Journal of Biological Systems, 26 (4). pp. 553-578. ISSN 0218-3390

2017

Liang, Yanfeng and Greenhalgh, David; (2017) Mathematical modelling the spread of Zika and Microcephaly in Brazil. In: Proceedings of the 17th International Conference on Computational and Mathematical Methods in Science and Engineering. CMMSE, [S.I.], pp. 1264-1268. ISBN 978-84-617-8694-7

2016

Greenhalgh, D. and Liang, Y. and Mao, X. (2016) Modelling the effect of telegraph noise in the SIRS epidemic model using Markovian switching. Physica A: Statistical Mechanics and its Applications, 462. pp. 684-704. ISSN 0378-4371

Liang, Yanfeng and Greenhalgh, David and Mao, Xuerong (2016) A stochastic differential equation model for the spread of HIV amongst people who inject drugs. Computational and Mathematical Methods in Medicine, 2016. 6757928. ISSN 1748-6718

Greenhalgh, D. and Liang, Y. and Mao, X. (2016) SDE SIS epidemic model with demographic stochasticity and varying population size. Applied Mathematics and Computation, 276. pp. 218-238. ISSN 0096-3003

2015

Greenhalgh, David and Liang, Yanfeng and Mao, Xuerong (2015) Demographic stochasticity in the SDE SIS epidemic model. Discrete and Continuous Dynamical Systems - Series B, 20 (9). pp. 2859-2884. ISSN 1531-3492

This list was generated on Mon Jul 6 04:41:47 2020 BST.