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Background 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. Methods We used domain expert knowledge and data in combination and iteratively, to construct, parameterise and validate a causal BN to predict causative pathogens for childhood pneumonia. Expert knowledge elicitation occurred through a series of group workshops, surveys and one-on-one meetings involving 6-8 experts from diverse domain areas. The model performance was evaluated based on both quantitative metrics and qualitative expert validation. Sensitivity analyses were conducted to investigate how the target output is influenced by varying key assumptions of a particularly high degree of uncertainty around data or domain expert knowledge. Results Designed to apply to a cohort of children with X-ray confirmed pneumonia who presented to a tertiary paediatric hospital in Australia, the resulting BN offers explainable and quantitative predictions on a range of variables of interest, including the diagnosis of bacterial pneumonia, detection of respiratory pathogens in the nasopharynx, and the clinical phenotype of a pneumonia episode. Satisfactory numeric performance has been achieved including an area under the receiver operating characteristic curve of 0.8 in predicting clinically-confirmed bacterial pneumonia with sensitivity 88% and specificity 66% given certain input scenarios (i.e., information that is available and entered into the model) and trade-off preferences (i.e., relative weightings of the consequences of false positive versus false negative predictions). We specifically highlight that a desirable model output threshold for practical use is very dependent upon different input scenarios and trade-off preferences. Three commonly encountered scenarios were presented to demonstrate the potential usefulness of the BN outputs in various clinical pictures. Conclusions To our knowledge, this is the first causal model developed to help determine the causative pathogen for paediatric pneumonia. We have shown how the method works and how it would help decision making on the use of antibiotics, providing insight into how computational model predictions may be translated to actionable decisions in practice. We discussed key next steps including external validation, adaptation and implementation. Our model framework and the methodological approach can be adapted beyond our context to broad respiratory infections and geographical and healthcare settings.

Introduction Influenza vaccination of children with medical comorbidities is critical due their increased risks for severe influenza disease. In Australia, hospitals are an avenue for influenza vaccine delivery to children with comorbidities but are not always effectively utilised. Qualitative enquiry sought to ascertainment the barriers and enablers for influenza vaccination recommendation, delivery, and recording of these children at Australian hospitals. Methods Semi-structured interviews and discussion group sessions were conducted with paediatricians and nurses at four tertiary paediatric specialist hospitals and two general community hospitals in three Australian states. Transcripts from interviews and group sessions were inductively analysed for themes. The Capability, Opportunity, Motivation, and Behaviour (COM-B) model was used to explore the elements of each theme and identify potential interventions to increase influenza vaccination recommendation and delivery behaviours by providers. Results Fifteen discussion sessions with 28 paediatricians and 26 nurses, and nine in-depth interviews (five paediatricians and four nurses) were conducted. Two central thematic domains were identified: 1. The interaction between hospital staff and parents/patients for influenza vaccine recommendation, and 2. Vaccination delivery and recording in the hospital environment. Six themes across these domains emerged detailing the importance of dedicated immunisation services, hospital leadership, paediatricians’ vaccine recommendation role, the impact of comorbidities, vaccination recording, and cocooning vaccinations. Supportive hospital leadership, engaged providers, and dedicated immunisation services were identified as essential for influenza vaccination of children with comorbidities in Australian hospital. Conclusion Recommendation of influenza vaccination for Australian children with comorbidities is impacted by the beliefs of paediatricians and the perceived impact of influenza disease on children’s comorbidities. Dedicated immunisation services and supportive hospital leadership were drivers for influenza vaccine delivery at hospitals. Future interventions targeting hospital-based influenza vaccine delivery for children with comorbidities should take a rounded approach targeting providers’ attitudes, the hospital environment and leadership support.

Background There is limited empiric evidence on the coverage of pneumococcal conjugate vaccines (PCVs) required to generate substantial indirect protection. We investigate the association between population PCV coverage and indirect protection against invasive pneumococcal disease (IPD) and pneumonia hospitalisations among undervaccinated Australian children. Methods and findings Birth and vaccination records, IPD notifications, and hospitalisations were individually linked for children aged, In an observational study, Jocelyn Chan and colleagues investigate associations between pneumococcal conjugate vaccine coverage and incidence of invasive pneumococcal disease and pneumonia among children under 5 years in Australia., Author summary Why was this study done? Pneumococcal conjugate vaccines (PCVs) reduce the burden of pneumococcal disease in vaccinated and unvaccinated populations through both direct and indirect (herd) effects. The indirect effects of a vaccine comprise a substantial component of overall vaccine impact, contributing to the cost-effectiveness of the vaccine, but little is known about what factors contribute to herd protection, including vaccination coverage. In this study, we examined associations between PCV coverage and indirect effects within diverse populations in Australia. What did the researchers do and find? Using a large dataset of 1.3 million children from 2 states in Australia, we quantified the relationship between PCV coverage within small geographical units and indirect protection against pneumococcal disease. We also performed similar analyses for infants too young to be fully vaccinated, urban, rural, and Indigenous populations. There were strong inverse relationships between PCV coverage and the incidence of severe invasive disease due to vaccine types and pneumonia hospitalisations among undervaccinated children, i.e., higher coverage was associated with greater reductions in disease due to indirect effects. We also found substantial indirect effects at relatively low levels of PCV coverage. We estimated that 50% and 90% coverage of 7-valent PCV (PCV7) among children under 5 years of age prevented almost three-quarters (72.5%, 95% confidence interval [CI] 51.6 to 84.4) and almost all (95.2%, 95% CI 89.4 to 97.8) of PCV7-type severe invasive disease, respectively. For pneumonia, we estimated that 50% and 90% coverage was sufficient to prevent one-third (33.3%, 95% CI 27.3 to 38.8) and about half (51.7%, 95% CI 43.7 to 58.6) of all-cause pneumonia hospitalisations among undervaccinated children. These trends were similar for children less than 4 months old, urban, rural, and Indigenous populations, although these effects were smaller for rural and Indigenous populations. There was also a trend towards decreasing incidence of PCV13-type IPD among undervaccinated children as PCV13 coverage increased. What do these findings mean? Our results challenge existing assumptions that high PCV coverage is required to achieve substantial indirect protection. Understanding the determinants of indirect effects are particularly urgent as countries that have controlled vaccine-type pneumococcal disease consider using reducing the number of PCV doses (from 3 to 2). Reduced dose schedules have the potential to significantly lower program costs while maintaining vaccine impact, providing indirect protection is achieved and preserved.

Background Broad community acceptance of a COVID-19 vaccination will be critical for effectively halting the spread of the virus. In this study, we focus on factors that differentiate those who are undecided from those who are either willing or unwilling to accept a prospective COVID-19 vaccine. Methods An online survey in May 2020 assessed Australian adults’ willingness to receive a COVID-19 vaccine (yes, maybe, no). A multinomial logistical regression of responses (N = 1,313) was used to identify correlates of vaccine willingness between the three groups. Results 65% were willing to vaccinate, with 27% being in the ‘maybe’ category. Respondents were more likely to be in the ‘maybe’ than the ‘yes’ group when they perceived COVID-19 to be less severe, had less trust in science, were less willing to vaccinate for influenza, and were female. They were more likely to be in the ‘maybe’ than ‘no’ group when they perceived COVID-19 as severe, and less likely to be a hoax, had more trust in science, and greater willingness to vaccinate for influenza. A repeat of the survey in November 2020 with a subset of participants found fewer of them saying yes to the vaccine (56%) and more saying maybe (31%). Conclusions The effectiveness of any COVID-19 vaccine rollout will be reliant on maximizing uptake. The significant number of people who remain undecided about whether or not to get a COVID-19 vaccine, despite the ongoing devastating consequences of the virus for individuals, communities, and economies, is concerning. Our findings aid current research seeking to inform policy regarding how to convince the undecided to vaccinate.

IntroductionOtitis media (OM) is one of the most common infectious diseases affecting children globally and the most common reason for antibiotic prescription and paediatric surgery. Australian Aboriginal children have higher rates of OM than non-Aboriginal children; however, there are no data comparing OM hospitalization rates between them at the population level. We report temporal trends for OM hospitalizations and in-hospital tympanostomy tube insertion (TTI) in a cohort of 469,589 Western Australian children born between 1996 and 2012.Materials and methodsWe used the International Classification of Diseases codes version 10 to identify hospitalizations for OM or TTI recorded as a surgical procedure. Using age-specific population denominators, we calculated hospitalization rates per 1,000 child-years by age, year and level of socio-economic deprivation.ResultsThere were 534,674 hospitalizations among 221,588 children hospitalized at least once before age 15 years. Aboriginal children had higher hospitalization rates for OM than non-Aboriginal children (23.3/1,000 [95% Confidence Interval (CI) 22.8,24.0] vs 2.4/1,000 [95% CI 2.3,2.4] child-years) with no change in disparity over time. Conversely non-Aboriginal children had higher rates of TTI than Aboriginal children (13.5 [95% CI 13.2,13.8] vs 10.1 [95% CI 8.9,11.4]). Children from lower socio-economic backgrounds had higher OM hospitalization rates than those from higher socio-economic backgrounds, although for Aboriginal children hospitalization rates were not statistically different across all levels of socio-economic disadvantage. Hospitalizations for TTI among non-Aboriginal children were more common among those from higher socio-economic backgrounds. This was also true for Aboriginal children; however, the difference was not statistically significant. There was a decline in OM hospitalization rates between 1998 and 2005 and remained stable thereafter.ConclusionAboriginal children and children from lower socio-economic backgrounds were over-represented with OM-related hospitalizations but had fewer TTIs. Despite a decrease in OM and TTI hospitalization rates during the first half of the study for all groups, the disparity between Aboriginal and non-Aboriginal children and between those of differing socioeconomic deprivation remained.

Background Influenza causes annual epidemics and often results in extensive outbreaks in closed communities. To minimize transmission, a range of interventions have been suggested. For these to be effective, an accurate and timely diagnosis of influenza is required. This is confirmed by a positive laboratory test result in an individual whose symptoms are consistent with a predefined clinical case definition. However, the utility of these clinical case definitions and laboratory testing in mass gathering outbreaks remains unknown. Methods and Results An influenza outbreak was identified during World Youth Day 2008 in Sydney. From the data collected on pilgrims presenting to a single clinic, a Markov model was developed and validated against the actual epidemic curve. Simulations were performed to examine the utility of different clinical case definitions and laboratory testing strategies for containment of influenza outbreaks. Clinical case definitions were found to have the greatest impact on averting further cases with no added benefit when combined with any laboratory test. Although nucleic acid testing (NAT) demonstrated higher utility than indirect immunofluorescence antigen or on-site point-of-care testing, this effect was lost when laboratory NAT turnaround times was included. The main benefit of laboratory confirmation was limited to identification of true influenza cases amenable to interventions such as antiviral therapy. Conclusions Continuous re-evaluation of case definitions and laboratory testing strategies are essential for effective management of influenza outbreaks during mass gatherings.