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The Western Australia (WA) Respiratory Infections Linked Data Platform is a population-based cohort established to investigate the epidemiology of RSV and other respiratory infections in children aged 0-10 years, incorporating microbiological testing patterns, hospital admissions, emergency department presentations, and socio-demographic data.
Invasive fungal disease (IFD) occurs less frequently during treatment for solid compared to hematological malignancies in children, and risk groups are poorly defined. Retrospective national multicenter cohort data (2004-2013) were analyzed to document prevalence, clinical characteristics, and microbiology of IFD.
To describe the characteristics of patients with chronic hepatitis B (CHB) presenting to a tertiary paediatric hospital in Perth, Western Australia. Review of implementation of previous follow-up recommendations for the cohort was also undertaken.
Respiratory syncytial virus contributes to significant global infant morbidity and mortality. We applied a previously developed statistical prediction model incorporating pre-pandemic RSV testing data and hospital admission data to estimate infant RSV-hospitalizations by birth month and prematurity, focused on infants aged <1 year.
The global population has been severely affected by the coronavirus disease 2019 (COVID-19) pandemic, however, with older age identified as a risk factor, children have been underprioritized. This article discusses the factors contributing to the less severe response observed in children following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), including, differing viral entry receptor expression and immune responses.
Western Australian laboratory data demonstrated a decrease in human metapneumovirus detections through 2020 associated with SARS-CoV-2-related non-pharmaceutical interventions, followed by a subsequent surge in metropolitan region in mid-2021. We aimed to assess the impact of the surge in hMPV on paediatric hospital admissions and the contribution of changes in testing.
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.
COVID-19 is a new multi-organ disease causing considerable worldwide morbidity and mortality. While many recognized pathophysiological mechanisms are involved, their exact causal relationships remain opaque. Better understanding is needed for predicting their progression, targeting therapeutic approaches, and improving patient outcomes. While many mathematical causal models describe COVID-19 epidemiology, none have described its pathophysiology.
The need for coronavirus 2019 (COVID-19) vaccination in different age groups and populations is a subject of great uncertainty and an ongoing global debate. Critical knowledge gaps regarding COVID-19 vaccination include the duration of protection offered by different priming and booster vaccination regimens in different populations, including homologous or heterologous schedules.
Respiratory syncytial virus (RSV) seasonality is dependent on the local climate. We assessed the stability of RSV seasonality prior to the SARS-CoV-2 pandemic in Western Australia (WA), a state spanning temperate and tropical regions.