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Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics
Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empiricall...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312821/ https://www.ncbi.nlm.nih.gov/pubmed/37398047 http://dx.doi.org/10.1101/2023.06.08.23291050 |
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author | Liu, Andrew Bo Lee, Daniel Jalihal, Amogh Prabhav Hanage, William P. Springer, Michael |
author_facet | Liu, Andrew Bo Lee, Daniel Jalihal, Amogh Prabhav Hanage, William P. Springer, Michael |
author_sort | Liu, Andrew Bo |
collection | PubMed |
description | Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Monitoring of air travel provides little benefit in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19. |
format | Online Article Text |
id | pubmed-10312821 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-103128212023-07-01 Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics Liu, Andrew Bo Lee, Daniel Jalihal, Amogh Prabhav Hanage, William P. Springer, Michael medRxiv Article Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Monitoring of air travel provides little benefit in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19. Cold Spring Harbor Laboratory 2023-10-06 /pmc/articles/PMC10312821/ /pubmed/37398047 http://dx.doi.org/10.1101/2023.06.08.23291050 Text en https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Liu, Andrew Bo Lee, Daniel Jalihal, Amogh Prabhav Hanage, William P. Springer, Michael Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics |
title | Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics |
title_full | Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics |
title_fullStr | Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics |
title_full_unstemmed | Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics |
title_short | Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics |
title_sort | quantitatively assessing early detection strategies for mitigating covid-19 and future pandemics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312821/ https://www.ncbi.nlm.nih.gov/pubmed/37398047 http://dx.doi.org/10.1101/2023.06.08.23291050 |
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