Journal article
Embedding treatment in stronger care systems
- Abstract:
- A key lesson from the west Africa (2014–16) Ebola disease epidemic was that outbreak responses fail when they respond to patients through a narrow clinical lens without considering the broader community and social context of care. Here, in the second of two Series papers on the modern landscape of Ebola disease, we review progress made in the last decade to improve patient-centred care. Although the biosafety imperatives of treating Ebola disease remain, recent advances show how to mitigate these so that patients are cared for in a safe and dignified manner that encourages early treatment-seeking behaviour and provides support after the return of patients to their communities. We review advances in diagnostics, including faster Ebola disease detection via real-time RT-PCR, and consider design improvements in Ebola disease treatment units that enhance patient safety and dignity. We also review advances in care provision, such as the integration of palliative care and mobile communication into routine care, and address how greater access to research is possible through harmonised clinical trials. Finally, we discuss how strengthened community engagement and psychosocial programmes are addressing stigma and providing holistic support for survivors.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
-
-
(Preview, Accepted manuscript, pdf, 572.2KB, Terms of use)
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- Publisher copy:
- 10.1016/s1473-3099(24)00727-8
Authors
- Publisher:
- Elsevier
- Journal:
- Lancet Infectious Diseases More from this journal
- Volume:
- 25
- Issue:
- 3
- Pages:
- e177-e188
- Publication date:
- 2024-12-12
- Acceptance date:
- 2024-10-21
- DOI:
- EISSN:
-
1474-4457
- ISSN:
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1473-3099
- Language:
-
English
- Pubs id:
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2071481
- Local pid:
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pubs:2071481
- Deposit date:
-
2024-12-18
Terms of use
- Copyright holder:
- Elsevier Ltd
- Copyright date:
- 2024
- Rights statement:
- © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
- Notes:
- The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford’s Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
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