Professor Joshua Ross
Professor, Research Fellow
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
Prizes, awards and special recognition
2020
Fulbright Future Scholarship was awarded to Joshua Ross. Awarded from the Fulbright Commission.
Joshua is a Professor of Applied Mathematics in the School of Mathematical Sciences. His research focuses on developing novel mathematical and statistical methods, and new probabilistic models, that assist in understanding the factors that are most important to complex systems in epidemiology and conservation biology. He uses these techniques to assist in determining effective public health, and conservation/biosecurity, policy.
As a Fulbright Future Scholar, Joshua will focus on the emerging area of Outbreak Analytics (i.e., Data and Decision Sciences for Outbreaks) and Gene Drive Modelling for Pest Eradication. These developments will inform how best to respond to emerging epidemiological threats, and for safe use of gene drives for pest eradication.
2016
J.H. Michell Medal was awarded to Joshua Ross. Awarded from the ANZIAM.
Moran Medal was awarded to Joshua Ross. Awarded from the Australian Academy of Science.
Publications
Journal Articles
(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). 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
(2018). Characterising seasonal influenza epidemiology using primary care surveillance data.
PLOS Computational Biology. 14(8), e1006377. doi: 10.1371/journal.pcbi.1006377
(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
(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). 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
(2017). An Induced Natural Selection Heuristic for Evaluating Optimal Bayesian Experimental Designs.
arXiv preprint arXiv:1703.05511.
(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
(2017). Inference of epidemiological parameters from household stratified data.
PLOS ONE. 12(10), e0185910. doi: 10.1371/journal.pone.0185910
(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
(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
(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
(2017). Intervention to maximise the probability of epidemic fade-out.
Mathematical Biosciences. 293, 1 - 10. doi: 10.1016/j.mbs.2017.08.003
(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
(2017). The illegal wildlife trade is a likely source of alien species.
Conservation Letters. doi: 10.1111/conl.12301
(2016). A data-driven model for influenza transmission incorporating media effects.
Royal Society Open Science. 3(10), doi: 10.1098/rsos.160481
(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
(2016). Integrative analysis of the physical transport network into Australia.
PLOS ONE. 11(2), doi: 10.1371/journal.pone.0148831
(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
(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
(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
(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
(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
(2015). Computation of epidemic final size distributions.
Journal of Theoretical Biology. 367, 159-165. doi: 10.1016/j.jtbi.2014.11.029
(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
(2015). On binomial observations of continuous-time Markovian population models.
Journal of Applied Probability. 52(02), 457-472. doi: 10.1017/S0021900200012572
(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
(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
(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
(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
(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
