Identifying Paucisymptomatic or Asymptomatic and Unrecognized Ebola Virus Disease Among Close Contacts Based on Exposure Risk Assessments and Screening Algorithms

Dehkontee Gayedyu-Dennis¹, Mosoka P Fallah^{1

2}, Clara Drew³, Moses Badio^{1

4}, J S Moses^{1

4}, Tamba Fayiah¹, Kumblytee Johnson¹, Eugene T Richardson^{5

6}, Sheri D Weiser⁷, Travis C Porco^{4

8}, Jeffrey N Martin⁴, Michael C Sneller⁹, George W Rutherford^{4

10}, Cavan Reilly^{1

3}, Christina P Lindan⁴, J D Kelly^{1

4

8

10}

Affiliations

¹ Partnership for Research on Vaccines and Infectious Diseases in Liberia (PREVAIL), Monrovia, Liberia.
² A.M. Dogliotti College of Medicine, University of Liberia, Monrovia, Liberia.
³ Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota, USA.
⁴ Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA.
⁵ Department of Medicine, Brigham and Women's Hospital, Boston, Minnesota, USA.
⁶ Department of Global Health and Social Medicine, Harvard Medical School, Boston, Minnesota, USA.
⁷ Division of HIV, Infectious Disease, and Global Medicine, Department of Medicine, University of California, San Francisco, California, USA.
⁸ Francis I. Proctor Foundation, University of California, San Francisco, California, USA.
⁹ Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland, USA.
¹⁰ Institute for Global Health Sciences, University of California, San Francisco, California, USA.

PMID: 36047331
PMCID: PMC10319948
DOI: 10.1093/infdis/jiac359

Identifying Paucisymptomatic or Asymptomatic and Unrecognized Ebola Virus Disease Among Close Contacts Based on Exposure Risk Assessments and Screening Algorithms

Dehkontee Gayedyu-Dennis et al. J Infect Dis. 2023.

. 2023 Apr 12;227(7):878-887.

doi: 10.1093/infdis/jiac359.

Authors

Affiliations

¹ Partnership for Research on Vaccines and Infectious Diseases in Liberia (PREVAIL), Monrovia, Liberia.
² A.M. Dogliotti College of Medicine, University of Liberia, Monrovia, Liberia.
³ Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota, USA.
⁴ Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA.
⁵ Department of Medicine, Brigham and Women's Hospital, Boston, Minnesota, USA.
⁶ Department of Global Health and Social Medicine, Harvard Medical School, Boston, Minnesota, USA.
⁷ Division of HIV, Infectious Disease, and Global Medicine, Department of Medicine, University of California, San Francisco, California, USA.
⁸ Francis I. Proctor Foundation, University of California, San Francisco, California, USA.
⁹ Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, Bethesda, Maryland, USA.
¹⁰ Institute for Global Health Sciences, University of California, San Francisco, California, USA.

PMID: 36047331
PMCID: PMC10319948
DOI: 10.1093/infdis/jiac359

Abstract

Background: There is limited evidence to evaluate screening algorithms with rapid antigen testing and exposure assessments as identification strategies for paucisymptomatic or asymptomatic Ebola virus (EBOV) infection and unrecognized EBOV disease (EVD).

Methods: We used serostatus and self-reported postexposure symptoms from a cohort study to classify contact-participants as having no infection, paucisymptomatic or asymptomatic infection, or unrecognized EVD. Exposure risk was categorized as low, intermediate, or high. We created hypothetical scenarios to evaluate the World Health Organization (WHO) case definition with or without rapid diagnostic testing (RDT) or exposure assessments.

Results: This analysis included 990 EVD survivors and 1909 contacts, of whom 115 (6%) had paucisymptomatic or asymptomatic EBOV infection, 107 (6%) had unrecognized EVD, and 1687 (88%) were uninfected. High-risk exposures were drivers of unrecognized EVD (adjusted odds ratio, 3.5 [95% confidence interval, 2.4-4.9]). To identify contacts with unrecognized EVD who test negative by the WHO case definition, the sensitivity was 96% with RDT (95% confidence interval, 91%-99%), 87% with high-risk exposure (82%-92%), and 97% with intermediate- to high-risk exposures (93%-99%). The proportion of false-positives was 2% with RDT and 53%-93% with intermediate- and/or high-risk exposures.

Conclusion: We demonstrated the utility and trade-offs of sequential screening algorithms with RDT or exposure risk assessments as identification strategies for contacts with unrecognized EVD.

Keywords: Ebola virus disease; Filovirus; Liberia; epidemiology; infection control; screening tests.

Published by Oxford University Press on behalf of Infectious Diseases Society of America 2022.

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Conflict of interest statement

Potential conflicts of interest. All authors: No reported conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

Figures

**Figure 1.**
Flow diagrams of study populations for exposure assessments and hypothetical scenarios. A, Ebola virus disease (EVD) survivors (n = 990) who were symptomatic (n = 981), with results according to the World Health Organization (WHO) case definition. B, Contacts (n = 1909) who were seropositive with unrecognized symptomatic EVD (n = 107) or who were seronegative and symptomatic (n = 516), with WHO case definition results for the symptomatic individuals.

**Figure 2.**
Kernal density plot of anti–Ebola virus antibody concentrations by group (Ebola virus disease [EVD] survivors, contacts with unrecognized EVD, contacts with paucisymptomatic or asymptomatic infection, and uninfected contacts). Abbreviation: EU, enzyme immunoassay units.

See this image and copyright information in PMC

References

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Identifying Paucisymptomatic or Asymptomatic and Unrecognized Ebola Virus Disease Among Close Contacts Based on Exposure Risk Assessments and Screening Algorithms

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Identifying Paucisymptomatic or Asymptomatic and Unrecognized Ebola Virus Disease Among Close Contacts Based on Exposure Risk Assessments and Screening Algorithms

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