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Community perception of vaccine safety influences vaccine uptake. Our objective was to assess current vaccine safety monitoring by examining factors that may influence the availability of post-vaccination survey data, and thereby the specificity and sensitivity of existing signal detection methods.
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.
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.
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.
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.
The ability for vaccines to protect against infectious diseases varies among individuals, but computational models employed to inform policy typically do not account for this variation. Here we examine this issue: we implement a model of vaccine efficacy developed in the context of SARS-CoV-2 in order to evaluate the general implications of modelling correlates of protection on the individual level.
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.
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.
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.
While most Australian children are vaccinated, delays in vaccination can put them at risk from preventable infections. Widespread mobile phone ownership in Australia could allow automated short message service (SMS) reminders to be used as a low-cost strategy to effectively 'nudge' parents towards vaccinating their children on time.