Prioritizing persons deprived of liberty in global guidelines for tuberculosis preventive treatment

Persons deprived of liberty (PDLs) are disproportionately impacted by tuberculosis, with high incidence rates and often limited access to diagnostics, treatment, and preventive measures. The World Health Organization (WHO) expanded its recommendations for tuberculosis preventive treatment (TPT) to many high-risk populations, but their guidance does not include PDL, and most low- and middle-income countries do not routinely provide edforthoseusedthroughoutthetext TPT in prisons. :Pleaseverifythatallentriesarecorrectlyabbreviated: Recent studies demonstrate high acceptability and completion rates of short-course TPT regimens in jails and prisons; costs of these regimens have been markedly reduced through international agreements, making this an opportune for further expanding their use. We argue that PDL should be a priority group for TPT in national guidelines and discuss implementation considerations and resource needs for TPT programs in carceral facilities. Scaling access to TPT for PDL is important for reducing disease and transmission in this population; it is also critical to advancing an equitable response to tuberculosis

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost