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This study provides a macro-level societal and health system focused analysis of child vaccination rates in 30 European countries, exploring the effect of context on coverage. The importance of demography and health system attributes on health care delivery are recognized in other fields, but generally overlooked in vaccination. The analysis is based on correlating systematic data built up by the Models of Child Health Appraised (MOCHA) Project with data from international sources, so as to exploit a one-off opportunity to set the analysis within an overall integrated study of primary care services for children, and the learning opportunities of the 'natural European laboratory'. The descriptive analysis shows an overall persistent variation of coverage across vaccines with no specific vaccination having a low rate in all the EU and EEA countries. However, contrasting with this, variation between total uptake per vaccine across Europe suggests that the challenge of low rates is related to country contexts of either policy, delivery, or public perceptions. Econometric analysis aiming to explore whether some population, policy and/or health system characteristics may influence vaccination uptake provides important results-GDP per capita and the level of the population's higher education engagement are positively linked with higher vaccination coverage, whereas mandatory vaccination policy is related to lower uptake rates. The health system characteristics that have a significant positive effect are a cohesive management structure; a high nurse/doctor ratio; and use of practical care delivery reinforcements such as the home-based record and the presence of child components of e-health strategies., Competing Interests: The authors have declared that no competing interests exist.

Limited information is available on the impact of the COVID-19 pandemic on the management of chronic myeloid leukaemia (CML). The Campus CML network collected retrospective information on 8 665 CML patients followed at 46 centres throughout Italy during the pandemic between February 2020 and January 2021. Within this cohort, we recorded 217 SARS-CoV-2-positive patients (2·5%). Most patients (57%) were diagnosed as having SARS-CoV-2 infection during the second peak of the pandemic (September 2020 to January 2021). The majority (35%) was aged between 50 and 65 years with a male prevalence (73%). Fifty-six percent of patients presented concomitant comorbidities. The median time from CML diagnosis to SARS-CoV-2 infection was six years (three months to 18 years). Twenty-one patients (9·6%) required hospitalization without the need of respiratory assistance, 18 (8·2%) were hospitalized for respiratory assistance, 8 (3·6%) were admitted to an intensive care unit, while 170 (78%) were only quarantined. Twenty-three percent of patients discontinued tyrosine kinase inhibitor (TKI) therapy during the infection. Twelve patients died due to COVID-19 with a mortality rate of 5·5% in the positive cohort and of 0·13% in the whole cohort. We could also document sequelae caused by the SARS-CoV-2 infection and an impact of the pandemic on the overall management of CML patients., (© 2021 British Society for Haematology and John Wiley & Sons Ltd.)

Different datasets have been deployed at national level to share data on COVID-19 already at the beginning of the epidemic spread in early 2020. They distribute daily updated information aggregated at local, gender and age levels. To facilitate the reuse of such data, FAIR principles should be applied to optimally find, access, understand and exchange them, to define intra- and inter-country analyses for different purposes, such as statistical. However, another aspect to be considered when analyzing these datasets is data quality. In this paper we link these two perspectives to analyze to what extent datasets published by national institutions to monitor diffusion of COVID-19 are reusable for scientific purposes, such as tracing the spread of the virus.

Since the beginning of the COVID-19 pandemic in March 2020, national and international authorities started to develop and update datasets to provide data to researchers, journalists and health care providers as well as public opinion. These data became one of the most important sources of information, which are updated daily and analysed by scientists in order to investigate and predict the spread of this epidemic. Despite this positive reaction from both national and international authorities in providing aggregated information on the diffusion of COVID-19, different challenges have been underlined in previously published studies. Different papers have discussed strengths and weaknesses of these types of datasets by focusing on different quality perspectives, which include the statistical methods adopted to analyse them; the lack of standards and models in the adoption of data for their management and distribution; and the analysis of different data quality characteristics. These studies have analysed datasets at the general level or by focusing the attention on specific indicators such as the number of cases or deaths. This paper further investigates issues and opportunities in the diffusion of these datasets under two main perspectives. At the general level, it analyses how data are organized and distributed to scientific and non-scientific communities. Moreover, it further explores the indicators adopted to describe the spread of the COVID-19 epidemic while also highlighting the level of detail used to describe them in terms of gender, age ranges and territorial units. The paper focuses on six European countries: Belgium, France, Germany, Italy, Spain and UK.

Context: The Covid-19 pandemic hit the developed world differentially due to accidental factors, and countries had to respond rapidly within existing resources, structures, and processes to manage totally new health challenges. This study aimed to identify which pre-existing structural factors facilitated better outcomes despite different starting points, as understanding of the relative impact of structural aspects should facilitate achieving optimal forward progress., Methods: Desk study, based on selecting and collecting a range of measures for 48 representative characteristics of 42 countries' demography, society, health system, and policy-making profiles, matched to three pandemic time points. Different analytic approaches were employed including correlation, multiple regression, and cluster analysis in order to seek triangulation., Findings: Population structure (except country size), and volume and nature of health resources, had only minor links to Covid impact. Depth of social inequality, poverty, population age structure, and strength of preventive health measures unexpectedly had no moderating effect. Strongest measured influences were population current enrolment in tertiary education, and country leaders' strength of seeking scientific evidence. The representativeness, and by interpretation the empathy, of government leadership also had positive effects., Conclusion: Strength of therapeutic health system, and indeed of preventive health services, surprisingly had little correlation with impact of the pandemic in the first nine months measured in death- or case-rates. However, specific political system features, including proportional representation electoral systems, and absence of a strong single party majority, were consistent features of the most successful national responses, as was being of a small or moderate population size, and with tertiary education facilitated. It can be interpreted that the way a country was lead, and whether leadership sought evidence and shared the reasoning behind resultant policies, had notable effects. This has significant implications within health system development and in promoting the population's health., Competing Interests: The authors have declared that no competing interests exist.

The high demand of hospitalization in the intensive care units (ICUs) during the first wave of the COVID-19 outbreak brought out the critical issues of the limited capacity of the regional systems to deal with high patient inflows in a short period of time. In this view, a rapid and efficient reallocation of resources is one of the main challenges to be addressed by regional systems to prevent overload and saturation. Aim of this study is to assess the spatial accessibility of ICU beds in the 20 Italian regions to capture the equity distribution of critical care services across the country. This analysis may contribute to gain a deeper understanding of the allocation of health resources. It can provide input for policy makers in view of a possible reorganization of the national system in terms of both its preparedness for emergency period and routine capability.

During COVID-19 emergency the majority of health structures in Europe saturated or nearly saturated their availabilities already in the first weeks of the epidemic period especially in some regions of Italy and Spain. The aim of this study is to analyse the efficiency in the management of hospital beds before the COVID-19 outbreak at regional level in France, Germany, Italy and Spain. This analysis can indicate a reference point for future analysis on resource management in emergency periods and help hospital managers, emergency planners as well as policy makers to put in place a rapid and effective response to an emergency situation. The results of this study clearly underline that France and Germany could rely on the robust structural components of the hospital system, compared to Italy and Spain. Presumably, this might have had an impact on the efficacy in the management of the COVID-19 diffusion. In particular, the high availability of beds in the majority of the France regions paired with the low occupancy rate and high turnover interval led these regions to have a high number of available beds. Consider also that this country generally manages complex cases. A similar structural component is present in the German regions where the number of available beds is significantly higher than in the other countries. The impact of the COVID-19 was completely different in Italy and Spain that had to deal with a relevant large number of patients relying on a reduced number of both hospital beds and professionals. A further critical factor compared to France and Germany concerns the dissimilar distribution of cases across regions. Even if in these countries the hospital beds were efficiently managed, the concentration of hospitalized patients and the scarcity of beds have put pressure on the hospital systems., Competing Interests: The authors have declared that no competing interests exist.

As the Italian health system is regionally based, COVID-19 emergency actions are based on a general lockdown imposed by national authority and then management at local level by 21 regional authorities. Therefore, the pandemic response plan developed by each region led to different approaches. The aim of this paper is to analyze whether differences in patient management may have influenced the local course of the epidemic. The analysis on the 21 Italian regions considers the strategies adopted in terms of hospitalization, treatment in the ICU and at home. Moreover, an in-depth analysis was carried out on: Lombardia, which adopted a hospitalization approach; Veneto, which tended to confine patients at home; and Emilia Romagna, which adopted a mixed hospitalization-home based approach. The majority of regions implemented a home-based approach, while the hospital approach was followed in three regions (Lombardia, Piemonte, and Lazio), mainly limited to the first period of the outbreak. All regions in the later phases tended to reduce hospitalization, preferring to confine patients at home. This comparison, highlighting the different phases of the pandemic, outlined that the adoption of home-based practices contributed to limiting infection rates among patients and health professionals as well as decreasing the number of deaths.