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Obtaining Prevalence Estimates of COVID-19: A Model to Inform Decision-making
We evaluate whether randomly sampling and testing a set number of individuals for coronavirus disease 2019 (COVID-19) while adjusting for misclassification error captures the true prevalence. We also quantify the impact of misclassification error bias on publicly reported case data in Maryland. Usin...
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| Publicat a: | Am J Epidemiol |
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| Autors principals: | , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Oxford University Press
2021
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8083389/ https://ncbi.nlm.nih.gov/pubmed/33831172 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/aje/kwab079 |
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