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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.
Increases in invasive group A streptococcal disease (iGAS) have recently been reported in multiple countries in the northern hemisphere, occurring during, and outside of, typical spring peaks. We report the epidemiology of iGAS among children in Australia from 1 July 2018 to 31 December 2022.
Seasonal influenza vaccine is effective against influenza hospitalisations, but little is known about non-specific effects of the vaccine on other respiratory pathogens with similar seasonal patterns. We aimed to assess the causal impact of seasonal influenza vaccine on laboratory-confirmed hospitalisations for respiratory syncytial virus (RSV) in children using an instrumental variable strategy.
Soil-transmitted helminth (STH) infection is driven by a complex interaction of demographic, socioeconomic and behavioural factors, including those related to water, sanitation and hygiene (WASH). Epidemiological studies that measure both infection and potential risk factors associated with infection help to understand the drivers of transmission in a population and therefore can provide information to optimise STH control programmes.
The COVID-19 pandemic is the first major pandemic of the digital age and has been characterised by unprecedented public consumption of spatial and temporal disease data, which can enable greater transparency and accountability of governments to the public for their public health decisions.
Influenza and COVID-19 infections during pregnancy may have serious adverse consequences for women as well as their infants. However, uptake of influenza and COVID-19 vaccines during pregnancy remains suboptimal. This study aims to assess the effectiveness of a multi-component nudge intervention to improve influenza and COVID-19 vaccine uptake among pregnant women.
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.
Regular intramuscular (i.m.) benzathine penicillin G (BPG) injections have been the cornerstone of rheumatic heart disease (RHD) secondary prophylaxis since the 1950s. Patient adherence to IM BPG is poor, largely due to pain, the need for regular injections every 3-4 weeks and health sector delivery challenges in resource-limited settings. There is an urgent need for new approaches for secondary prophylaxis, such as an implant which could provide sustained penicillin concentrations for more than 6 months.
Vaccination in pregnancy is the best strategy to reduce complications from influenza or pertussis infection in infants who are too young to be protected directly from vaccination. Pregnant women are also at risk of influenza complications preventable through antenatal vaccination. Both vaccines are funded under the National Immunisation Program for pregnant women in Australia, but coverage is not routinely reported nationally.