Cargando…
Accounting for incomplete testing in the estimation of epidemic parameters
As the COVID-19 pandemic spreads across the world, it is important to understand its features and responses to public health interventions in real-time. The field of infectious diseases epidemiology has highly advanced modeling strategies that yield relevant estimates. These include the doubling tim...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273303/ https://www.ncbi.nlm.nih.gov/pubmed/32511535 http://dx.doi.org/10.1101/2020.04.08.20058313 |
_version_ | 1783542376863629312 |
---|---|
author | Betensky, R.A. Feng, Y. |
author_facet | Betensky, R.A. Feng, Y. |
author_sort | Betensky, R.A. |
collection | PubMed |
description | As the COVID-19 pandemic spreads across the world, it is important to understand its features and responses to public health interventions in real-time. The field of infectious diseases epidemiology has highly advanced modeling strategies that yield relevant estimates. These include the doubling time of the epidemic and various other representations of the numbers of cases identified over time. Crude estimates of these quantities suffer from dependence on the underlying testing strategies within communities. We clarify the functional relationship between testing and the epidemic parameters, and thereby derive sensitivity analyses that explore the range of possible truths under various testing dynamics. We derive the required adjustment to the estimates of interest for New York City. We demonstrate that crude estimates that assume stable testing or complete testing can be biased. |
format | Online Article Text |
id | pubmed-7273303 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-72733032020-06-07 Accounting for incomplete testing in the estimation of epidemic parameters Betensky, R.A. Feng, Y. medRxiv Article As the COVID-19 pandemic spreads across the world, it is important to understand its features and responses to public health interventions in real-time. The field of infectious diseases epidemiology has highly advanced modeling strategies that yield relevant estimates. These include the doubling time of the epidemic and various other representations of the numbers of cases identified over time. Crude estimates of these quantities suffer from dependence on the underlying testing strategies within communities. We clarify the functional relationship between testing and the epidemic parameters, and thereby derive sensitivity analyses that explore the range of possible truths under various testing dynamics. We derive the required adjustment to the estimates of interest for New York City. We demonstrate that crude estimates that assume stable testing or complete testing can be biased. Cold Spring Harbor Laboratory 2020-05-10 /pmc/articles/PMC7273303/ /pubmed/32511535 http://dx.doi.org/10.1101/2020.04.08.20058313 Text en http://creativecommons.org/licenses/by-nc-nd/4.0/It is made available under a CC-BY-NC-ND 4.0 International license (http://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Article Betensky, R.A. Feng, Y. Accounting for incomplete testing in the estimation of epidemic parameters |
title | Accounting for incomplete testing in the estimation of epidemic parameters |
title_full | Accounting for incomplete testing in the estimation of epidemic parameters |
title_fullStr | Accounting for incomplete testing in the estimation of epidemic parameters |
title_full_unstemmed | Accounting for incomplete testing in the estimation of epidemic parameters |
title_short | Accounting for incomplete testing in the estimation of epidemic parameters |
title_sort | accounting for incomplete testing in the estimation of epidemic parameters |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273303/ https://www.ncbi.nlm.nih.gov/pubmed/32511535 http://dx.doi.org/10.1101/2020.04.08.20058313 |
work_keys_str_mv | AT betenskyra accountingforincompletetestingintheestimationofepidemicparameters AT fengy accountingforincompletetestingintheestimationofepidemicparameters |