Stephen is broadly interested in the mathematical modeling of vector-borne and zoonotic diseases, with 10 years full-time research experience in theoretical and applied epidemiology. He has worked on the following specific disease systems: sylvatic plague (Yersinia pestis infection in wild animals) in Kazakhstan; bubonic plague (Yersinia pestis infection in humans arising from a flea bite) in Tanzania; Lyme disease in North America; African sleeping sickness in Uganda; the sylvatic cycle of Echinococcus multilocularis in Europe; and rabies in Tanzania.
His areas of expertise include the mathematical modeling of infectious disease, complex networks, theoretical population biology, and biometrics. He has a developing interest in the use of graphs and networks in pattern recognition, with applications in automatic biometric authentication and identification systems.
Stephen has co-authored a small text book, together with Dr Steven Barry, that is designed to help undergraduate students of mathematics master (and remember) skills that lecturers typically assume the students retain from either high-school or previous courses.
Barry, S. I. and Davis, S. Essential Mathematical Skills. UNSW Press, Sydney.
- AMSI AGR Honours Course – Complex Networks (2012, 2013)
- MATH2163 – Mathematics for Surveying and Geomatics A (2012, 2013)
- MATH2164 – Mathematics for Surveying and Geomatics B (2011)
- 1994 – BSc. (Hons) Mathematics, University of Melbourne.
- 1996 – Grad. Dip. Education, University of Canberra.
- 2000 – Ph. D. in Applied Mathematics, University of New South Wales.
Stephen is a Senior Lecturer in Mathematics. He began his career at CSIRO, Division of Wildlife and Ecology, and then spent 8 years in Europe and the USA as a postdoctoral scientist before returning to Australia late in 2009.
He has spent time at the Department of Biology at the University of Antwerp (Belgium), the School of Veterinary Science in Utrecht University (The Netherlands) and the School of Population Health at Yale University (USA).
He has first-author publications in Nature and Science.
- Johnstone-Robertson, S.,Diuk-Wasser, M.,Davis, S. (2020). Incorporating tick feeding behaviour into R0 for tick-borne pathogens In: Theoretical Population Biology, 131, 25 - 37
- Kotzerke, J.,Davis, S.,Hayes, R.,Horadam, K. (2019). Newborn and infant discrimination: revisiting footprints In: Australian Journal of Forensic Sciences, 51, 95 - 108
- Huang, C.,Kay, S.,Davis, S.,Tufts, D.,Gaffett, K.,Tefft, B.,Diuk-Wasser, M. (2019). High burdens of Ixodes scapularis larval ticks on white-tailed deer may limit Lyme disease risk in a low biodiversity setting In: Ticks and Tick-borne Diseases, 10, 258 - 268
- Arakala, A.,Davis, S.,Horadam, K. (2019). Vascular Biometric Graph Comparison: Theory and Performance In: Handbook of Vascular Biometrics, Springer, Switzerland
- Kotzerke, J.,Davis, S.,McVernon, J.,Horadam, K. (2018). Steps to solving the infant biometric problem with ridge-based biometrics In: IET Biometrics, 7, 567 - 572
- Johnstone-Robertson, S.,Fleming, P.,Ward, M.,Davis, S. (2017). Predicted spatial spread of canine rabies in Australia In: PLOS Neglected Tropical Diseases, 11, 1 - 21
- Arakala, A.,Davis, S.,Hao, H.,Horadam, K. (2017). Value of graph topology in vascular biometrics In: IET Biometrics, 6, 117 - 125
- States, S.,Huang, C.,Davis, S.,Tufts, D.,Diuk-Wasser, M. (2017). Co-feeding transmission facilitates strain coexistence in Borrelia burgdorferi, the Lyme disease agent In: Epidemics, 19, 33 - 42
- Leung, T.,Davis, S. (2017). Rabies vaccination targets for stray dog populations In: Frontiers in Veterinary Science, 4, 1 - 10
- Kotzerke, J.,Hao, H.,Davis, S.,Hayes, R.,Spreeuwers, L.,Veldhuis, R.,Horadam, K. (2016). Identification performance of evidential value estimation for ridge-based biometrics In: EURASIP Journal on Information Security, 2016, 1 - 10
2 PhD Current Supervisions5 PhD Completions
- Development of hydrological, ecological and epidemiological modelling to inform a CyHV3 release strategy for the biocontrol of carp in the Murray darling Basin (administered by CSIRO). Funded by: 085-Fisheries Research and Development Corporation - Industry Partnership Agreement Programme Grant from (2017 to 2020)
- Novel Dissimilarity Techniques for Characterising Noisy Spatial Networks. Funded by: ARC Discovery 2012 from (2012 to 2014)
- Babesiosis Emergence in the United States. Funded by: National Institutes of Health Research Project Grant 2015 from (2012 to 2018)
- Happy Feet: Novel footprint recognition to support childhood vaccination. Funded by: Gates Foundation Grant pre-2014 from (2011 to 2013)
- Advances in the prediction of plague outbreaks in Central Asia. Funded by: Wellcome Trust International Collaborative Research Grant pre-2014 from (2010 to 2013)