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Chris Glenn Lea-Ann Peter Ruth Brennan-Jones Pearson Kirkham Richmond Thornton PhD BA (Education) PhD Candidate PhD MBBS MRCP(UK) FRACP PhD Head, Ear
Deborah Lea-Ann Peter Ruth Strickland Kirkham Richmond Thornton PhD PhD MBBS MRCP(UK) FRACP PhD Head, Pregnancy and Early Life Immunology Co-Head,
Lea-Ann Peter Ruth Kirkham Richmond Thornton PhD MBBS MRCP(UK) FRACP PhD Co-Head, Bacterial Respiratory Infectious Disease Group; Microbiology Lead,
Peter Ruth Elke Richmond Thornton Seppanen MBBS MRCP(UK) FRACP PhD BSc PhD Head, Vaccine Trials Group Co-head, Bacterial Respiratory Infectious
Ruth Elke Peter Thornton Seppanen Richmond PhD BSc PhD MBBS MRCP(UK) FRACP Co-head, Bacterial Respiratory Infectious Disease Group (BRIDG) Program
IgE-mediated sensitisation to egg is common in infants. In some cases, the processes leading to egg sensitisation are established in early life, even before introduction to solid foods. The underlying mechanisms remain poorly understood.
Children in Papua New Guinea (PNG) are at high risk of pneumococcal infections. We investigated pneumococcal carriage rates, serotype distribution, and antimicrobial susceptibility in PNG children after vaccination with 10-valent or 13-valent pneumococcal conjugate vaccines (PCV10; PCV13).
To identify and review key research advances from the literature published between 2019 and 2023 on the diagnosis and microbiology of otitis media (OM) including acute otitis media (AOM), recurrent AOM (rAOM), otitis media with effusion (OME), chronic suppurative otitis media (CSOM) and AOM complications (mastoiditis).
To identify the barriers and facilitators for timely detection and optimal management of otitis media in Aboriginal children in a primary care setting from the perspective of carers of Aboriginal children.
Pneumonia remains a leading cause of hospitalization and death among young children worldwide, and the diagnostic challenge of differentiating bacterial from non-bacterial pneumonia is the main driver of antibiotic use for treating pneumonia in children. Causal Bayesian networks (BNs) serve as powerful tools for this problem as they provide clear maps of probabilistic relationships between variables and produce results in an explainable way by incorporating both domain expert knowledge and numerical data.