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Cystic fibrosis (CF) is a rare, inherited, life-limiting condition predominantly affecting the lungs, for which there is no cure. The disease is characterized by recurrent pulmonary exacerbations (PEx), which are thought to drive progressive lung damage. Management of these episodes is complex and generally involves multiple interventions targeting different aspects of disease. The emergence of innovative trials and use of Bayesian statistical methods has created renewed opportunities for studying heterogeneous populations in rare diseases.
Untreated hepatitis C virus (HCV) infection can result in cirrhosis and hepatocellular cancer. Direct-acting antiviral (DAA) therapies are highly effective and have few side effects compared to older interferon-based therapy. Despite the Australian government providing subsidised and unrestricted access to DAA therapy for chronic HCV infection, uptake has not been sufficient to meet the global target of eliminating HCV as a public health threat by 2030.
Group A streptococcus (GAS) infections, such as pharyngitis and impetigo, can lead to rheumatic fever and rheumatic heart disease (RHD). Australian Aboriginal and Torres Strait Islander populations experience high rates of RHD and GAS skin infection, yet rates of GAS pharyngitis are unclear.
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.
Diagnosing urinary tract infections (UTIs) in children in the emergency department (ED) is challenging due to the variable clinical presentations and difficulties in obtaining a urine sample free from contamination.
The implications of climate change for malaria eradication this century remain poorly resolved. Many studies focus on parasite and vector ecology in isolation, neglecting the interactions between climate, malaria control and the socioeconomic environment, including disruption from extreme weather. Here we integrate 25 years of African data on climate, malaria burden and control, socioeconomic factors, and extreme weather.
Estimating the temporal trends in infectious disease activity is crucial for monitoring disease spread and the impact of interventions. Surveillance indicators routinely collected to monitor these trends are often a composite of multiple pathogens. For example, "influenza-like illness"-routinely monitored as a proxy for influenza infections-is a symptom definition that could be caused by a wide range of pathogens, including multiple subtypes of influenza, SARS-CoV-2, and RSV.
Acute rheumatic fever is a preventable condition that can lead to chronic illness and early death. Standard prevention with 4-weekly intramuscular (IM) benzathine penicillin G (BPG) injections for ≥10 years may be associated with poor adherence. High-dose 10-weekly subcutaneous penicillin injections (SCIP) may improve adherence by reducing injection frequency.
Vaccine policy and guideline recommendations require high quality evidence. A review of the evidence quality used to inform vaccine clinical practice guidelines could help guide researchers on how to improve the design of their clinical studies to produce evidence of greater value to decision-makers.
To assess potential benefits and direct healthcare cost savings with expansion of an existing childhood influenza immunisation program, we developed a dynamic transmission model for the state of Western Australia, evaluating increasing coverage in children < 5 years and routinely immunising school-aged children.