SARS-CoV-2 seroassay optimization and performance in a population with high background reactivity in Mali.


Journal

medRxiv : the preprint server for health sciences
Titre abrégé: medRxiv
Pays: United States
ID NLM: 101767986

Informations de publication

Date de publication:
12 Mar 2021
Historique:
pubmed: 25 3 2021
medline: 25 3 2021
entrez: 24 3 2021
Statut: epublish

Résumé

Serological tests are an indispensable tool to understand the epidemiology of the SARS-CoV-2 pandemic, particularly in areas where molecular diagnostics are limited. Poor assay performance may hinder the utility of these tests, including high rates of false-positivity previously reported in sub-Saharan Africa. From 312 Malian samples collected prior to 2020, we measured antibodies to the commonly tested SARS-CoV-2 antigens and four other betacoronaviruses by ELISA, and assessed functional cross-reactivity in a subset by SARS-CoV-2 pseudovirus neutralization assay. We then evaluated the performance of an ELISA developed in the US, using two-antigen SARS-CoV-2 spike protein and receptor-binding domain. To optimize test performance, we compared single and two-antigen approaches using existing assay cutoffs and population-specific cutoffs for Malian control samples (positive and negative). Background reactivity to SARS-CoV-2 antigens was common in pre-pandemic samples compared to US controls (43.4% (135/311) for spike protein, 22.8% (71/312) for RBD, and 33.9% (79/233) for nucleocapsid protein). SARS-CoV-2 reactivity correlated weakly with other betacoronavirus reactivity, varied between Malian communities, and increased with age. No pre-pandemic samples demonstrated functional activity. Regardless of the cutoffs applied, specificity improved using a two-antigen approach. Test performance was optimal using a two-antigen assay with population-specific cutoffs derived from ROC curve analysis [Sensitivity: 73.9% (51.6-89.8), Specificity: 99.4% (97.7-99.9)]. In the setting of high background reactivity, such as sub-Saharan Africa, SARS-CoV-2 serological assays need careful qualification is to characterize the epidemiology of disease, prevent unnecessary harm, and allocate resources for targeted control measures.

Identifiants

pubmed: 33758883
doi: 10.1101/2021.03.08.21252784
pmc: PMC7987042
pii:
doi:

Types de publication

Preprint

Langues

eng

Subventions

Organisme : CCR NIH HHS
ID : HHSN261200800001C
Pays : United States
Organisme : NCI NIH HHS
ID : HHSN261200800001E
Pays : United States

Commentaires et corrections

Type : UpdateIn

Auteurs

Classifications MeSH