ORCID as entered in ROS

Select Publications
2022, Monoclonal antibody levels and protection from COVID-19, http://dx.doi.org/10.1101/2022.11.22.22282199
,2022, Neutralising antibodies predict protection from severe COVID-19, http://dx.doi.org/10.1101/2022.06.09.22275942
,2022, Predicting the efficacy of variant-modified COVID-19 vaccine boosters, http://dx.doi.org/10.1101/2022.08.25.22279237
,2022, Risk of Plasmodium vivax recurrences follows a 30-70 rule and indicates relapse heterogeneity in the population, http://dx.doi.org/10.1101/2022.05.18.22275180
,2022, SARS-CoV-2 Omicron: evasion of potent humoral responses and resistance to clinical immunotherapeutics relative to viral variants of concern, http://dx.doi.org/10.21203/rs.3.rs-1207364/v1
,2021, A meta-analysis of Early Results to predict Vaccine efficacy against Omicron, http://dx.doi.org/10.1101/2021.12.13.21267748
,2021, Dynamics of immune recall following SARS-CoV-2 vaccination or breakthrough infection, http://dx.doi.org/10.1101/2021.12.23.21268285
,2021, Relating in vitro neutralisation level and protection in the CVnCoV (CUREVAC) trial, http://dx.doi.org/10.1101/2021.06.29.21259504
,2021, SARS-CoV-2 variants: levels of neutralisation required for protective immunity, http://dx.doi.org/10.1101/2021.08.11.21261876
,2021, What level of neutralising antibody protects from COVID-19?, http://dx.doi.org/10.1101/2021.03.09.21252641
,2020, Decay of Fc-dependent antibody functions after mild to moderate COVID-19, http://dx.doi.org/10.1101/2020.12.13.20248143
,2020, Early analysis of the Australian COVID-19 epidemic, http://dx.doi.org/10.1101/2020.04.25.20080127
,2020, Evolution of immunity to SARS-CoV-2, http://dx.doi.org/10.1101/2020.09.09.20191205
,2017, A mechanistic model quantifies artemisinin-induced parasite growth retardation in blood-stage Plasmodium falciparum infection, http://dx.doi.org/10.48550/arxiv.1701.05302
,