Joshua Ross | ARC Centre of Excellence for Mathematical and Statistical Frontiers

Professor, Research Fellow

The University of Adelaide

I am an ARC Future Fellow and Associate Professor in Applied Mathematics within the Operations Research Group of the School of Mathematical Sciences at The University of Adelaide. I lead the "Development of innovative methods" theme in the NHMRC Centre of Research Excellence for Policy Relevant Infectious Disease Simulation and Mathematical Modelling (PRISM2), and am Director of Research for the School of Mathematical Sciences.

Research Interests:

Applied mathematics

Applied probability

Bayesian computational algorithms

Bayesian design

Bayesian inference

Markov chain

Markov chain Monte Carlo simulation algorithms

Markov decision process

Optimisation

Stochastic modelling

Qualifications:

BA, BSc (Hons), GCEd (HE), PhD

Projects

Elucidating user behaviours in a digital health surveillance system to correct prevalence estimates

ACEMS researchers at The University of Adelaide develop a statistical model to get a better estimate of the spread of influenza-like-illness, accounting for human behaviour in online health surveillance systems.

Predicting the Risk of Biological Invasions Using Environmental Similarity and Transport Network Connectedness

ACEMS researchers have developed new methods to evaluate the risk of invasion between geopolitical regions (e.g., states, or countries), by assessing climate similarity between the regions, and the volume of transport that occurs between them.

Publications

Journal Articles

2019

Cope, R. C., Ross J.V., Wittmann T. A., Watts M. J., & Cassey P. (2019). Predicting the Risk of Biological Invasions Using Environmental Similarity and Transport Network Connectedness. Risk Analysis. 39(1), 35-53. doi: 10.1111/risa.12870

2018

Rebuli, N. P., Bean N. G., & Ross J.V. (2018). Estimating the basic reproductive number during the early stages of an emerging epidemic. Theoretical Population Biology. 119, 26-36. doi: 10.1016/j.tpb.2017.10.004

Cope, R. C., Ross J.V., Chilver M., Stocks N. P., Mitchell L., & Lloyd-Smith J. (2018). Characterising seasonal influenza epidemiology using primary care surveillance data. PLOS Computational Biology. 14(8), e1006377. doi: 10.1371/journal.pcbi.1006377

Price, D. J., Bean N. G., Ross J.V., & Tuke J. (2018). An induced natural selection heuristic for finding optimal Bayesian experimental designs. Computational Statistics & Data Analysis. 126, 112–124. doi: 10.1016/j.csda.2018.04.011

Yan, A. W. C., Black A. J., McCaw J. M., Rebuli N. P., Ross J.V., Swan A. J., et al. (2018). The distribution of the time taken for an epidemic to spread between two communities. Mathematical Biosciences. 303, 139 - 147. doi: 10.1016/j.mbs.2018.07.004

2017

García-Díaz, P., Ross J.V., Woolnough A. P., & Cassey P. (2017). Managing the risk of wildlife disease introduction: Pathway-level biosecurity for preventing the introduction of alien ranaviruses. Journal of Applied Ecology. 54(1), 234-241. doi: 10.1111/1365-2664.12749

Price, D. J., Bean N. G., Ross J.V., & Tuke J. (2017). An Induced Natural Selection Heuristic for Evaluating Optimal Bayesian Experimental Designs. arXiv preprint arXiv:1703.05511.

Prowse, T. A. A., Cassey P., Ross J.V., Pfitzner C., Wittmann T. A., & Thomas P. (2017). Dodging silver bullets: good CRISPR gene-drive design is critical for eradicating exotic vertebrates. Proceedings of the Royal Society B: Biological Sciences. 284(1860), 20170799. doi: 10.1098/rspb.2017.0799

Walker, J. N., Ross J.V., & Black A. J. (2017). Inference of epidemiological parameters from household stratified data. PLOS ONE. 12(10), e0185910. doi: 10.1371/journal.pone.0185910

Brock, A. R., Ross J.V., Greenhalgh S., Durham D. P., Galvani A., Parikh S., et al. (2017). Modelling the impact of antimalarial quality on the transmission of sulfadoxine-pyrimethamine resistance in Plasmodium falciparum. Infectious Disease Modelling. 2(2), 161 - 187. doi: 10.1016/j.idm.2017.04.001

Rebuli, N. P., Bean N. G., & Ross J.V. (2017). Hybrid Markov chain models of S–I–R disease dynamics. Journal of Mathematical Biology. 75(3), 521 - 541. doi: 10.1007/s00285-016-1085-2

Brock, A., Gibbs C., Ross J.V., & Esterman A. (2017). The Impact of Antimalarial Use on the Emergence and Transmission of Plasmodium falciparum Resistance: A Scoping Review of Mathematical Models. Tropical Medicine and Infectious Disease. 2(4), 54. doi: 10.3390/tropicalmed2040054

Ballard, P. G., Bean N. G., & Ross J.V. (2017). Intervention to maximise the probability of epidemic fade-out. Mathematical Biosciences. 293, 1 - 10. doi: 10.1016/j.mbs.2017.08.003

García-Díaz, P., Ross J.V., Woolnough A. P., & Cassey P. (2017). The illegal wildlife trade is a likely source of alien species. Conservation Letters. doi: 10.1111/conl.12301

Black, A. J., Geard N., McCaw J. M., McVernon J., & Ross J.V. (2017). Characterising pandemic severity and transmissibility from data collected during first few hundred studies. Epidemics. 19, 61 - 73. doi: 10.1016/j.epidem.2017.01.004

2016

Lydeamore, M., Bean N. G., Black A. J., & Ross J.V. (2016). Choice of antiviral allocation scheme for pandemic influenza depends on strain transmissibility, delivery delay and stockpile size. Bulletin of Mathematical Biology. 78(2), 293-321. doi: 10.1007/s11538-016-0144-6

Cope, R. C., Ross J.V., Wittmann T. A., Prowse T. A. A., & Cassey P. (2016). Integrative analysis of the physical transport network into Australia. PLOS ONE. 11(2), doi: 10.1371/journal.pone.0148831

Ballard, P. G., Bean N. G., & Ross J.V. (2016). The probability of epidemic fade-out is non-monotonic in transmission rate for the Markovian SIR model with demography. Journal of Theoretical Biology. 393, 170-178. doi: 10.1016/j.jtbi.2016.01.012

Johnston, S. T., Ross J.V., Binder B. J., McElwain D.L. Sean, Haridas P., & Simpson M. J. (2016). Quantifying the effect of experimental design choices for in vitro scratch assays. Journal of Theoretical Biology. 400, 19-31. doi: 10.1016/j.jtbi.2016.04.012

Bean, N. G., Eshragh A., & Ross J.V. (2016). Fisher Information for a partially observable simple birth process. Communications in Statistics - Theory and Methods. 45(24), 7161-7183. doi: 10.1080/03610926.2014.978024

Heinrich, S., Wittmann T. A., Prowse T. A. A., Ross J.V., Delean S., Shepherd C. R., et al. (2016). Where did all the pangolins go? International CITES trade in pangolin species. Global Ecology and Conservation. 8, 241-253. doi: 10.1016/j.gecco.2016.09.007

Price, D. J., Bean N. G., Ross J.V., & Tuke J. (2016). On the efficient determination of optimal Bayesian experimental designs using ABC: A case study in optimal observation of epidemics. Journal of Statistical Planning and Inference. 172, 1-15. doi: 10.1016/j.jspi.2015.12.008

Mitchell, L., & Ross J.V. (2016). A data-driven model for influenza transmission incorporating media effects. Royal Society Open Science. 3(10), doi: 10.1098/rsos.160481

2015

Binder, B. J., Landman K. A., Newgreen D. F., & Ross J.V. (2015). Incomplete penetrance: The role of stochasticity in developmental cell colonization. Journal of Theoretical Biology. 380, 309-314. doi: 10.1016/j.jtbi.2015.05.028

Bean, N. G., Elliott R., Eshragh A., & Ross J.V. (2015). On binomial observations of continuous-time Markovian population models. Journal of Applied Probability. 52(02), 457-472. doi: 10.1017/S0021900200012572

Ross, J.V., & Black A. J. (2015). Contact tracing and antiviral prophylaxis in the early stages of a pandemic: the probability of a major outbreak. Mathematical Medicine and Biology. 32(3), 331-343. doi: 10.1093/imammb/dqu014

Robinson, S. J., Souter N. J., Bean N. G., Ross J.V., Thompson R. M., & Bjornsson K. T. (2015). Statistical description of wetland hydrological connectivity to the River Murray in South Australia under both natural and regulated conditions. Journal of Hydrology. 531, 929-939. doi: 10.1016/j.jhydrol.2015.10.006

Keeling, M. J., & Ross J.V. (2015). Optimal prophylactic vaccination in segregated populations: When can we improve on the equalising strategy?. Epidemics. 11, 7-13. doi: 10.1016/j.epidem.2015.01.002

García-Díaz, P., Ross J.V., Ayres C., & Cassey P. (2015). Understanding the biological invasion risk posed by the global wildlife trade: propagule pressure drives the introduction and establishment of Nearctic turtles. Global Change Biology. 21(3), 1078-1091. doi: 10.1111/gcb.12790

Black, A. J., & Ross J.V. (2015). Computation of epidemic final size distributions. Journal of Theoretical Biology. 367, 159-165. doi: 10.1016/j.jtbi.2014.11.029

2014

Davies, K.J., Green J.E.F., Bean N. G., Binder B.J., & Ross J.V. (2014). On the derivation of approximations to cellular automata models and the assumption of independence. Mathematical Biosciences. 253, 63-71. doi: 10.1016/j.mbs.2014.04.004

Research links

Contact

joshua.ross@adelaide.edu.au

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Professor Joshua Ross