دورية أكاديمية
Statistical framework to support the epidemiological interpretation of SARS-CoV-2 concentration in municipal wastewater
| العنوان: | Statistical framework to support the epidemiological interpretation of SARS-CoV-2 concentration in municipal wastewater |
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| المؤلفون: | Xiaotian Dai, David Champredon, Aamir Fazil, Chand S. Mangat, Shelley W. Peterson, Edgard M. Mejia, Xuewen Lu, Thierry Chekouo |
| المصدر: | Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022) |
| بيانات النشر: | Nature Portfolio, 2022. |
| سنة النشر: | 2022 |
| المجموعة: | LCC:Medicine LCC:Science |
| مصطلحات موضوعية: | Medicine, Science |
| الوصف: | Abstract The ribonucleic acid (RNA) of the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is detectable in municipal wastewater as infected individuals can shed the virus in their feces. Viral concentration in wastewater can inform the severity of the COVID-19 pandemic but observations can be noisy and sparse and hence hamper the epidemiological interpretation. Motivated by a Canadian nationwide wastewater surveillance data set, unlike previous studies, we propose a novel Bayesian statistical framework based on the theories of functional data analysis to tackle the challenges embedded in the longitudinal wastewater monitoring data. By employing this framework to analyze the large-scale data set from the nationwide wastewater surveillance program covering 15 sampling sites across Canada, we successfully detect the true trends of viral concentration out of noisy and sparsely observed viral concentrations, and accurately forecast the future trajectory of viral concentrations in wastewater. Along with the excellent performance assessment using simulated data, this study shows that the proposed novel framework is a useful statistical tool and has a significant potential in supporting the epidemiological interpretation of noisy viral concentration measurements from wastewater samples in a real-life setting. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2045-2322 |
| Relation: | https://doaj.org/toc/2045-2322 |
| DOI: | 10.1038/s41598-022-17543-y |
| URL الوصول: | https://doaj.org/article/c64289c8357e44afa55ba8672d6e7c04 |
| رقم الأكسشن: | edsdoj.64289c8357e44afa55ba8672d6e7c04 |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 20452322 |
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| DOI: | 10.1038/s41598-022-17543-y |