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Making the invisible visible: using national surveillance data to identify people experiencing homelessness in England with COVID-19

Title: Making the invisible visible: using national surveillance data to identify people experiencing homelessness in England with COVID-19
Authors: Capelastegui, Fernando; Flannagan, Joe; Augarde, Elizabeth; Tessier, Elise; Chudasama, Dimple; Dabrera, Gavin; Lamagni, Theresa; Campos-Matos, Ines
Source: Epidemiology and Infection ; volume 151 ; ISSN 0950-2688 1469-4409
Publisher Information: Cambridge University Press (CUP)
Publication Year: 2023
Description: Persons experiencing homelessness (PEH) or rough sleeping are a vulnerable population, likely to be disproportionately affected by the coronavirus disease 2019 (COVID-19) pandemic. The impact of COVID-19 infection on this population is yet to be fully described in England. We present a novel method to identify COVID-19 cases in this population and describe its findings. A phenotype was developed and validated to identify PEH or rough sleeping in a national surveillance system. Confirmed COVID-19 cases in England from March 2020 to March 2022 were address-matched to known homelessness accommodations and shelters. Further cases were identified using address-based indicators, such as NHS pseudo postcodes. In total, 1835 cases were identified by the phenotype. Most were
Document Type: article in journal/newspaper
Language: English
DOI: 10.1017/s095026882300033x
Availability: https://doi.org/10.1017/s095026882300033x; https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S095026882300033X
Rights: http://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.5F87605B
Database: BASE