Sara Cooper and colleagues argue that a better understanding of the complex sociopolitical drivers of distrust in vaccination will increase the potential of social media to rebuild vaccine confidence
Vaccination experts have become increasingly alarmed about the continued waning of public confidence in vaccines.1 Social media are considered to be major contributors to this decline, facilitating the rapid and widespread sharing of misinformation, enabling vaccine anxieties and rumours to travel rapidly around the world.23 Social media are also seen to have enabled vocal anti-vaccination groups to self-organise and communicate well beyond their local areas.45 The covid-19 pandemic has only magnified these concerns,6 as Tedros Adhanom Ghebreyesus, director general of the World Health Organization put it, “We’re not just fighting a pandemic; we’re fighting an infodemic.”7
This dominant narrative on mistrust in vaccines assumes that it is primarily the result of a lack of informa
Artificial intelligence has potential to counter vaccine hesitancy while building trust in vaccines, but it must be deployed ethically and responsibly, argue Heidi Larson and Leesa Lin
Given the sluggish pace of traditional scientific approaches, artificial intelligence (AI), particularly generative AI, has emerged as a significant opportunity to tackle complex health challenges, including those in public health.1 Against this backdrop, interest has focused on whether AI has a role in bolstering public trust in vaccines and helping to minimise vaccine hesitancy, which the World Health Organization named as one of the top 10 global health threats.2
Vaccine hesitancy is a state of indecision before accepting or refusing a vaccination.3 It is a dynamic and context specific challenge that varies across time, place, and vaccine type. It is influenced by a range of factors, including sociocultural and political dynamics, as well as individual and group psychology. Its multifaceted and tem
Elizabeth Mitgang and colleagues argue that building capacity in applied systems thinking and human centred design mindsets and methods can help improve quality of care, particularly in low and middle income settings
Health systems are social systems where outcomes for people and communities hinge on their ability to access high quality care when and where they need it. Yet globally, health systems often do not adequately take into consideration the interactions between people, communities, healthcare providers, and the enabling environment.1 The complementary approaches of applied systems thinking and human centred design are gaining traction as methods that can help tackle deficiencies and improve the quality of health services and experiences.1234
Systems thinking offers a practical way to see inter-relations and patterns of change rather than static “snapshots,” and to visualise emergent connections across the people and processes that comprise health systems.56 Human centred
Kevin Croke and colleagues consider how demand for quality health systems can be made a political and public priority to drive change in low and middle income countries
The root causes of gaps in quality of care in the health systems of low and middle income country generate considerable debate, and opinions differ about how to tackle these gaps. The debate is illustrated by three important reports published in 2018.123 The consensus view of major global health institutions is well captured by the 2018 report from the World Health Organization, World Bank, and Organisation for Economic Cooperation and Development, which emphasised technical strategies to improve system quality such as changes to payment systems, adoption of new technologies, and scale-up of facility level quality improvement interventions. This approach is consistent with most published evidence in the quality improvement field, which explicitly or implicitly takes the same approach. The Lancet Global Health Commissio