As thousands of people arrive at the USA border requesting asylum, it is only fair that they are treated with the same dignity as any other person.
The commentary offers a proposal to aid the meaningful contribution of all voices in youth mental health research.
This Article supports SDGs 3 and 10 by showing that in Austria, Greece, Spain, and the UK, there is a dearth of targeted, tailored cancer prevention programmes for people experiencing homelessness, and concern from health professionals that cancer is not being spotted at early stages in this population.
The article emphasizes the importance of providing training and supporting resources alongside open science initiatives to enhance accessibility and reduce barriers in the field. It suggests that these educational resources should be customized to cater to diverse user profiles, including neuroscientists, computational scientists, and educators.
climate change interacts with historical colonialism to shape fisheries in small island developing states. Greater attention to fish as food can improve food sovereignty and reduce historical inequalities
Population-based surveys are expensive and time consuming. By determining state-level seropositivity using national testing service data and a Bayesian linear model, a map of HIV prevalence was generated across the whole of Nigeria. By identifying the areas in which HIV is most prevalent interventions can be targeted. This less resource intense Bayseian method allows for national monitoring of HIV prevalence.
This paper reviews the unique perspective that Indigenous People have on the HIV/AIDS epidemic, and the interactions between Indigenous Identities and HIV. The authors call for a human rights based approach to ending the HIV epidemic among Indigenous Peoples.
Explores the impact and consequences of not being able to make trips because of transport disadvantage. Explicitly does so in relation to SDG goal 11.2.
This Perspective explores the sources of bias in medical machine learning, and how these can contribute to unequal performance, for example for women. The authors discuss methods for mitigating bias, hopefully leading to more equitable use of machine learning in healthcare.
Recognising our customers' exceptional work to achieve the United Nations' Sustainable Development Goals
