دورية أكاديمية
Influenza infection rates, measurement errors and the interpretation of paired serology.
| العنوان: | Influenza infection rates, measurement errors and the interpretation of paired serology. |
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| المؤلفون: | Simon Cauchemez, Peter Horby, Annette Fox, Le Quynh Mai, Le Thi Thanh, Pham Quang Thai, Le Nguyen Minh Hoa, Nguyen Tran Hien, Neil M Ferguson |
| المصدر: | PLoS Pathogens, Vol 8, Iss 12, p e1003061 (2012) |
| بيانات النشر: | Public Library of Science (PLoS), 2012. |
| سنة النشر: | 2012 |
| المجموعة: | LCC:Immunologic diseases. Allergy LCC:Biology (General) |
| مصطلحات موضوعية: | Immunologic diseases. Allergy, RC581-607, Biology (General), QH301-705.5 |
| الوصف: | Serological studies are the gold standard method to estimate influenza infection attack rates (ARs) in human populations. In a common protocol, blood samples are collected before and after the epidemic in a cohort of individuals; and a rise in haemagglutination-inhibition (HI) antibody titers during the epidemic is considered as a marker of infection. Because of inherent measurement errors, a 2-fold rise is usually considered as insufficient evidence for infection and seroconversion is therefore typically defined as a 4-fold rise or more. Here, we revisit this widely accepted 70-year old criterion. We develop a Markov chain Monte Carlo data augmentation model to quantify measurement errors and reconstruct the distribution of latent true serological status in a Vietnamese 3-year serological cohort, in which replicate measurements were available. We estimate that the 1-sided probability of a 2-fold error is 9.3% (95% Credible Interval, CI: 3.3%, 17.6%) when antibody titer is below 10 but is 20.2% (95% CI: 15.9%, 24.0%) otherwise. After correction for measurement errors, we find that the proportion of individuals with 2-fold rises in antibody titers was too large to be explained by measurement errors alone. Estimates of ARs vary greatly depending on whether those individuals are included in the definition of the infected population. A simulation study shows that our method is unbiased. The 4-fold rise case definition is relevant when aiming at a specific diagnostic for individual cases, but the justification is less obvious when the objective is to estimate ARs. In particular, it may lead to large underestimates of ARs. Determining which biological phenomenon contributes most to 2-fold rises in antibody titers is essential to assess bias with the traditional case definition and offer improved estimates of influenza ARs. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1553-7366 1553-7374 |
| العلاقة: | http://europepmc.org/articles/PMC3521724?pdf=renderTest; https://doaj.org/toc/1553-7366Test; https://doaj.org/toc/1553-7374Test |
| DOI: | 10.1371/journal.ppat.1003061 |
| الوصول الحر: | https://doaj.org/article/a398148eae124387a63c9fbbc7f1b055Test |
| رقم الانضمام: | edsdoj.398148eae124387a63c9fbbc7f1b055 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 15537366 15537374 |
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| DOI: | 10.1371/journal.ppat.1003061 |