Last data update: May 06, 2024. (Total: 46732 publications since 2009)
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Query Trace: Bratcher A[original query] |
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Considerations for defining homelessness in public health data collection
Meehan AA , Waddell CJ , Marx GE , Clarke KEN , Bratcher A , Montgomery MP , Marcus R , Ramirez V , Mosites E . Public Health Rep 2023 333549231215850 Public health problems cannot be addressed without timely and accurate data. However, data that provide insight into populations that may be at disproportionate risk for disease, including people experiencing homelessness, are insufficiently captured. Although the associations between homelessness and disease have been well documented,1-6 data on housing status are not universally or consistently collected in routine public health data.7 Improving collection of data on housing status in public health data collection efforts is necessary to address health disparities among people experiencing homelessness and advance health equity research and practice. | Collecting data related to homelessness and disease is complicated for several reasons, but one of the most salient reasons is that defining homelessness is challenging. Several federal agencies use their own definitions to identify people who might be eligible for assistance programs, creating confusion about which definition should be used for public health purposes. In addition, definitions of homelessness at federal agencies have changed over time, further complicating the collection of homelessness data. The US Department of Housing and Urban Development (HUD) defines homelessness as lacking a fixed, regular, and adequate nighttime residence8; this definition includes both people with a primary nighttime residence of a public or private place not meant for human habitation (eg, cars, parks, public spaces, abandoned buildings) and people residing in temporary shelters (eg, emergency homeless shelter, transitional housing). The US Department of Education (DOE) uses a broader lens, defining homelessness to include school-aged children whose housing situation meets the HUD criteria for homelessness while also including those who share housing with other people by doubling up or couch surfing; those who live in motels, hotels, or trailer parks; and those who are abandoned at hospitals.9 |
The Global Meningitis Genome Partnership.
Rodgers E , Bentley SD , Borrow R , Bratcher HB , Brisse S , Brueggemann AB , Caugant DA , Findlow J , Fox L , Glennie L , Harrison LH , Harrison OB , Heyderman RS , van Rensburg MJ , Jolley KA , Kwambana-Adams B , Ladhani S , LaForce M , Levin M , Lucidarme J , MacAlasdair N , Maclennan J , Maiden MCJ , Maynard-Smith L , Muzzi A , Oster P , Rodrigues CMC , Serino ORL , Smith V , van der Ende A , Vazquez J , Wang X , Yezli S , Stuart JM . J Infect 2020 81 (4) 510-520 Genomic surveillance of bacterial meningitis pathogens is essential for effective disease control globally, enabling identification of emerging and expanding strains and consequent public health interventions. While there has been a rise in the use of whole genome sequencing, this has been driven predominately by a subset of countries with adequate capacity and resources. Global capacity to participate in surveillance needs to be expanded, particularly in low and middle-income countries with high disease burdens. In light of this, the WHO-led collaboration, Defeating Meningitis by 2030 Global Roadmap, has called for the establishment of a Global Meningitis Genome Partnership that links resources for: N. meningitidis (Nm), S. pneumoniae (Sp), H. influenzae (Hi) and S. agalactiae (Sa) to improve worldwide co-ordination of strain identification and tracking. Existing platforms containing relevant genomes include: PubMLST: Nm (31,622), Sp (15,132), Hi (1,935), Sa (9,026); The Wellcome Sanger Institute: Nm (13,711), Sp (>24,000), Sa (6,200), Hi (1738); and BMGAP: Nm (8,785), Hi (2,030). A steering group is being established to coordinate the initiative and encourage high-quality data curation. Next steps include: developing guidelines on open-access sharing of genomic data; defining a core set of metadata; and facilitating development of user-friendly interfaces that represent publicly available data. |
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