Classification of measles breakthrough cases in an elimination setting using a comprehensive algorithm of laboratory results: why sensitive and specific IgM assays are important
Objective: In 2006, a measles outbreak occurred in Catalonia (Spain), six years after endemic measles was declared eliminated. This study aimed to classify 19 confirmed measles breakthrough cases (BC) using a high-performance avidity assay developed in 2010. Methods: Serum specimens were tested by i...
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| Autores principales: | , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/303209ad01414ff7bd3aa3178fef565c |
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| Sumario: | Objective: In 2006, a measles outbreak occurred in Catalonia (Spain), six years after endemic measles was declared eliminated. This study aimed to classify 19 confirmed measles breakthrough cases (BC) using a high-performance avidity assay developed in 2010. Methods: Serum specimens were tested by indirect IgG, indirect IgM, capture IgM enzyme immunoassay, an endpoint-titer IgG avidity assay, and a plaque reduction neutralization assay. Serology and RNA detection results were combined in an algorithm for measles confirmation and classification of breakthrough cases and analyzed with clinical and epidemiological data. Results: Of 19 samples, thirteen (68%) were conclusive with the classification of BCs, and six (32%) had false-positive IgM results on an indirect-format assay; they were classified as rash and fever illness of undetermined etiology. BCs were primary vaccine failures (seven or 54%), secondary vaccine failures (four or 31%), and two (15%) could not be classified. Conclusions: In measles elimination settings, high-performing assays and a comprehensive algorithm of laboratory results (IgG, IgM, and RNA detection), including IgG avidity and PRN results when necessary, can assist in accurate laboratory confirmation and classification of suspected measles cases for surveillance. Highly specific IgM assays are required to minimize the number of false-positive results. |
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