Rate My Professor Nic Geard

Geard's research specializes in agent-based modelling and computational simulations to investigate infectious disease dynamics and control, including influenza, group A Streptococcus, and COVID-19, accounting for demographic, behavioral, and pathogen heterogeneity. His broader interests encompass simulation models of complex biological, social, and artificial systems, with prior work on gene regulatory networks, developmental and evolutionary processes, and co-evolution in dynamic networks. Notable publications include "Implications of asymptomatic carriers for infectious disease transmission and control" (Chisholm et al., 2018, Royal Society Open Science), "Synthetic population dynamics: a model of household demography" (Geard et al., 2013, Journal of Artificial Societies and Social Simulation), "Optimal timing of influenza vaccine during pregnancy: A systematic review and meta-analysis" (Cuningham et al., 2019, Influenza and Other Respiratory Viruses), "The effects of demographic change on disease transmission and vaccine impact in a household structured population" (Geard et al., 2015, Epidemics), and "Risk mapping for COVID-19 outbreaks in Australia using mobility data" (Zachreson et al., 2021, Journal of The Royal Society Interface). He received the ARC DECRA Fellowship and FEIT Excellence Awards in Interdisciplinary Research.