F1000Research

Introduction The COVID-19 pandemic was marked by an unprecedented use and dissemination of statistical data and analyses. In its early phases, public communication focused primarily on epidemic dynamics; by late 2020, however, attention increasingly shifted toward the effectiveness and safety of COVID-19 vaccines—initially on the basis of evidence from clinical trials and, following the launch of the vaccination campaign, on data collected through integrated surveillance systems.

1. Introduction The health sector within the global economy is characterized by a contradictory reality where spending on healthcare rose but does not directly result in a rise in frontier and developing economies’ outcomes. Total global health spending reached $7.9 trillion USD in 2017 and is projected to rise to $11.0 trillion USD by 2030, amounting to 8.6% of the global economy in 2016.1 Irrespective of this expansion, persistent and glaring inequalities exist.

1. Introduction The COVID-19 pandemic gave rise to an intensified debate about open science (OS) (Benson Marshall et al., 2024). Some advocates of OS argued that the pandemic was a ‘stress test’ of the value of OS and would act as a ‘catalyst’ for change involving more widespread adoption of open practices in the global scientific community.

1. Key messages • The modern paradigm of urban health has evolved with a strengthening evidence base, deeper understanding of the wider determinants of health in towns and cities, and a recognition that effective action requires a multi-sectoral systems approach. • Access to the highest attainable standard of health has come to be recognised as a right of urban residents.

Introduction In 2021, UNESCO created a Recommendation on Open Science, which is defined as “a set of principles and practices that aim to make scientific research from all fields accessible to everyone for the benefit of scientists and society as a whole (UNESCO).” The Open Science movement focuses on, among others, the accessibility of scientific results in the form of publications, data, source materials and digital representations (Sönke Bartling & Friesike, 2014).

1. Introduction The domain of healthcare has seen a significant rise in the implementation of artificial intelligence, and liver transplantation is no exception, especially from the perspective of data analytics. Liver transplantation is the last therapeutic option for patients with end-stage liver disease,1 and is the second most common organ transplantation.

Introduction Scientific discovery and the translation of findings into practice requires complete, transparent and unbiased reporting. Although fundamental to the scientific method, sound reporting practices are not always adhered to.

Traditional closed peer review typically follows a single- or double-blinded process. This allows journal editors and reviewers to decide what research is published where and introduces the potential for bias. At Wellcome Open Research, we do things differently. We prioritise openness, transparency, and collaboration across the full publishing process, including peer review, offering a fully open post-publication peer review model.

If you've forgotten your password, please enter your email address below and we'll send you instructions on how to reset your password. The email address should be the one you originally registered with F1000. Code not correct, please try again Email us for further assistance. Server error, please try again. If your email address is registered with us, we will email you instructions to reset your password.

Introduction Open science (OS) is a global movement aiming to “make scientific research from all fields accessible to everyone” (UNESCO, 2023). It encapsulates a range of practices that seek to provide free and unrestricted access to research findings (i.e., publishing research papers in publicly available venues) but also to the research process itself (e.g., sharing software, code, protocols, or datasets used in research).