Adult immunization is a critical yet underdeveloped area within European public health, as fragmented systems and implementation barriers persist. With a growing burden of vaccine-preventable diseases among adults due to demographic aging and emerging pathogens, this policy comment aims to address key barriers impeding a high vaccination uptake, including data availability, feasibility issues, political and financial constraints, vaccine confidence and literacy among the population and healthcare providers, and access issues and organization. Drawing on insights from Adult Immunization Board (AIB) meetings and discussions, a decalogue of actionable policy recommendations is proposed to overcome these barriers. This comprehensive strategy underscores the need for coordinated, multidisciplinary efforts and sustained political commitment to optimize adult immunization programs, leveraging lessons from the recent COVID-19 pandemic response.

• Following DRG implementation, the cost structure for hospitalized children with Kawasaki disease underwent moderate adjustments, with stable medical insurance reimbursement rates. • The positive correlation between length of stay and total costs slightly weakened, accompanied by a minor decrease in average hospitalization days. • DRG demonstrated more pronounced cost changes for male patients and older children aged 36 months and above. Kawasaki disease (KD), prevalent among children, represents a significant public health concern globally. Epidemiological evidence suggests that the incidence of KD has increased over the past few decades, imposing considerable economic burdens on families attributable to hospitalization costs. This study utilized descriptive statistics, non-parametric tests, Spearman correlation analysis and multivariate generalized linear models on discharge data (2020-2022) from KD inpatients to explore the association between the Diagnosis-Related Group (DRG) system in China and hospitalization costs (in CNY), specifically comparing the total costs and cost composition before and after DRG implementation and examine the differences between subgroups. After DRG implementation, the median total hospitalization cost showed an upward trend, and the medical insurance reimbursement amount also increased simultaneously. Significant cost reductions occurred in material costs, while Western medicine costs increased. The cost structure changed modestly. The correlation between length of stay and total hospitalization cost remained significant but weakened slightly. Reimbursement rates remained stable and cost changes were more pronounced in males and older children (> 36 months), although these interaction effects were not statistically significant in the model. DRG effectively standardizes specific costs and alters cost structure. Under the premise of maintaining a stable medical insurance reimbursement ratio, the direct burden on patients had not increased. Its impact varies by age and gender, suggesting that refined DRG grouping criteria could improve policy precision for pediatric KD patients.

• Vaccines with higher effectiveness and longer protection were preferred • Risk of side effects significantly reduced vaccine acceptance likelihood • Vaccines from the US, UK, and EU were preferred over Chinese and Russian ones • Two latent classes identified: pro-vaccine and vaccine-resistant groups • Trust, attitudes, and prior experience derived class membership The objective of this study was to quantify public preferences for alternative vaccination programme strategies, combining vaccine attributes and policy measures, that could be deployed in future outbreaks similar to COVID-19 in South Africa. A discrete choice experiment (DCE) was conducted among 3,002 South African respondents. Attributes included vaccine effectiveness, duration of protection, side-effect risk, vaccine origin, approval time, and social restrictions including stringency of restrictions and vaccine mandate. Multinomial Logit (MNL) and Latent Class (LC) models were estimated to explore preferences. Vaccines with higher effectiveness were consistently preferred by South African respondents. Similarly, vaccines offering longer immunity durations and those approved after longer evaluation periods were preferred. Vaccines originating from the EU, UK, and US were preferred over those from China. In contrast, vaccines associated with higher risks of severe side effects were significantly less preferred. A latent class model identified two distinct groups: a majority (68.3%) classified as “provaccine,” who demonstrated strong preference for vaccination, often driven by trust in institutions and positive vaccine attitudes; and a minority (31.7%) categorised as “vaccine-resistant” who exhibited reluctance towards vaccination, likely driven by lower institutional trust, negative vaccine attitudes, and reduced health risk aversion. COVID19 vaccine preferences in South Africa were strongly influenced by perceived effectiveness, approval time, origin of the vaccine, duration of protection, risks of side effects, social restrictions and vaccine mandates. Respondents exhibited diverse preference patterns, and public health strategies should be designed to reflect these differences. Understanding how people make decisions about vaccines can help improve public health communication and planning. This research used a method that asked South Africans to imagine different vaccine scenarios and choose which ones they would prefer. People preferred vaccines that were highly effective, lasted longer, and had fewer side effects. Vaccines made in Western countries like the US, UK, and EU were preferred over those from China or Russia. Importantly, not everyone thinks about vaccines the same way. We found two main groups: one willing to vaccinate, trusting institutions and prioritising community health, and another prioritising individual rights, and not willing to vaccinate. By recognizing and addressing the diverse values that influence decision-making, public health initiatives can better support informed choices and strengthen community engagement during future outbreaks.

• Though Gen AI is increasingly being explored in various fields, including healthcare, there is little to no research into health professional perspectives. • Generally, there is a support for the use of Gen AI in healthcare for both clinical use and administrative offloading, however, there are still concerns with regards to data privacy and technical errors. • Organisational support and the provision of guidelines and guardrails remain the crucial priority for health professional use of Gen AI technologies in the workplace. Generative Artificial Intelligence (Gen AI) has become an increasingly prevalent conversation in healthcare over the past few years. Though there have been research projects and articles exploring the administrative and clinical uses of such technologies, there has been little exploration of health professional perspectives, hopes and concerns. This study sought to explore perspectives and examine the barriers and enablers of Gen AI in healthcare. Australian health professionals participated in a mixed-methods study. A survey (n=31) explored the Six Dimensions of Healthcare Quality Framework, capturing quantitative (Likert-scale responses) and qualitative (free-text) data. Semi-structured interviews (n=10) explored participant perceptions of Gen AI. Quantitative data was analysed using descriptive statistics. Qualitative data was thematically analysed. Most survey respondents (74.14%) reported having used Gen AI to support their work, but only a few (25.81%) reported organisational supports for use of these technologies. Analysis of the qualitative data aligned with the survey responses. Five themes were generated through thematic analysis, aligning with health professional’s perceived use of Gen AI chatbots, benefits, risks, as well as drivers of safe use and opportunities for the future. Health professionals see potential for using Gen AI to support their work, with enthusiasm about the potential of Gen AI to reduce workloads, particularly in offloading administrative tasks. There is also awareness that Gen AI chatbots pose risks both at the individual level such as limited capability in using these technologies and at the organisational level such as lack of training to support in upskilling, and systemic concerns around policy gaps. Generative Artificial Intelligence (Gen AI) is increasingly topical in all aspects of life, and the health sector is no exception. Though there have research projects focusing on Gen AI in healthcare, there has been little exploration of health professional views and concerns. This study spoke to health professionals and found that though there is a lot of interest in potential applications of Gen AI in healthcare, particularly in administrative offloading and clinical support, the benefits don’t yet outweigh the risks. Software developers must work alongside health professionals in developing a substantially beneficial program to support the safe use of Gen AI in healthcare as well as be well supported on an organisational level. There is also opportunities to develop education to build health professionals capacity to use GenAI safely and effectively, and for health service organisations to develop guidance and policies to clearly articulate what safe use looks like.