4.8 Article

A point-of-care diagnostic for differentiating Ebola from endemic febrile diseases

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SCIENCE TRANSLATIONAL MEDICINE
卷 10, 期 471, 页码 -

出版社

AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/scitranslmed.aat0944

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资金

  1. Paul G. Allen Family Foundation
  2. NIH Office of Research Services/Division of Veterinary Resources [NOR15003-001-00000]
  3. NIAID Division of Microbiology and Infectious Diseases [NOR15003-001-00000]
  4. NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES [R21AI115978] Funding Source: NIH RePORTER

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Hemorrhagic fever outbreaks such as Ebola are difficult to detect and control because of the lack of low-cost, easily deployable diagnostics and because initial clinical symptoms mimic other endemic diseases such as malaria. Current molecular diagnostic methods such as polymerase chain reaction require trained personnel and laboratory infrastructure, hindering diagnostics at the point of need. Although rapid tests such as lateral flow can be broadly deployed, they are typically not well-suited for differentiating among multiple diseases presenting with similar symptoms. Early detection and control of Ebola outbreaks require simple, easy-to-use assays that can detect and differentiate infection with Ebola virus from other more common febrile diseases. Here, we developed and tested an immunoassay technology that uses surface-enhanced Raman scattering (SERS) tags to simultaneously detect antigens from Ebola, Lassa, and malaria within a single blood sample. Results are provided in < 30 min for individual or batched samples. Using 190 clinical samples collected from the 2014 West African Ebola outbreak, along with 163 malaria positives and 233 negative controls, we demonstrated Ebola detection with 90.0% sensitivity and 97.9% specificity and malaria detection with 100.0% sensitivity and 99.6% specificity. These results, along with corresponding live virus and nonhuman primate testing of an Ebola, Lassa, and malaria 3-plex assay, indicate the potential of the SERS technology as an important tool for outbreak detection and clinical triage in low-resource settings.

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