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A cost-effective plan for global testing - an infection rate stratified, algorithm guided, multiple-level, continuously pooled testing strategy

The most effective measure to prevent or stop the spread of infectious diseases is the early identification and isolation of infected individuals through comprehensive screening. At present, in the COVID-19 pandemic, such screening is often limited to isolated regions as determined by local governme...

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Autores principales: Gu, Tianshu, Yao, Lan, Meng, Xia, Graff, J. Carolyn, Thomason, Donald, Li, Jing, Dong, Wei, Jiao, Yan, Aleya, Lotfi, Maida, Marcello, Wang, Cong-Yi, Zangerl, Barbara, Genini, Sem, Ray, Kunal, Goldman, Emanuel, Ji, Jiafu, Alexandrov, Andrei V., Sun, Dianjun, Gu, Weikuan, Wang, Yongjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833620/
https://www.ncbi.nlm.nih.gov/pubmed/33387925
http://dx.doi.org/10.1016/j.scitotenv.2020.144251
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author Gu, Tianshu
Yao, Lan
Meng, Xia
Graff, J. Carolyn
Thomason, Donald
Li, Jing
Dong, Wei
Jiao, Yan
Aleya, Lotfi
Maida, Marcello
Wang, Cong-Yi
Zangerl, Barbara
Genini, Sem
Ray, Kunal
Goldman, Emanuel
Ji, Jiafu
Alexandrov, Andrei V.
Sun, Dianjun
Gu, Weikuan
Wang, Yongjun
author_facet Gu, Tianshu
Yao, Lan
Meng, Xia
Graff, J. Carolyn
Thomason, Donald
Li, Jing
Dong, Wei
Jiao, Yan
Aleya, Lotfi
Maida, Marcello
Wang, Cong-Yi
Zangerl, Barbara
Genini, Sem
Ray, Kunal
Goldman, Emanuel
Ji, Jiafu
Alexandrov, Andrei V.
Sun, Dianjun
Gu, Weikuan
Wang, Yongjun
author_sort Gu, Tianshu
collection PubMed
description The most effective measure to prevent or stop the spread of infectious diseases is the early identification and isolation of infected individuals through comprehensive screening. At present, in the COVID-19 pandemic, such screening is often limited to isolated regions as determined by local governments. Screening of potentially infectious individuals should be conducted through coordinated national or global unified actions. Our current research focuses on using resources to conduct comprehensive national and regional regular testing with a risk rate based, algorithmic guided, multiple-level, pooled testing strategy. Here, combining methodologies with mathematical logistic models, we present an analytic procedure of an overall plan for coordinating state, national, or global testing. The proposed plan includes three parts 1) organization, resource allocation, and distribution; 2) screening based on different risk levels and business types; and 3) algorithm guided, multiple level, continuously screening the entire population in a region. This strategy will overcome the false positive and negative results in the polymerase chain reaction (PCR) test and missing samples during initial tests. Based on our proposed protocol, the population screening of 300,000,000 in the US can be done weekly with between 15,000,000 and 6,000,000 test kits. The strategy can be used for population screening for current COVID-19 and any future severe infectious disease when drugs or vaccines are not available.
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spelling pubmed-78336202021-01-26 A cost-effective plan for global testing - an infection rate stratified, algorithm guided, multiple-level, continuously pooled testing strategy Gu, Tianshu Yao, Lan Meng, Xia Graff, J. Carolyn Thomason, Donald Li, Jing Dong, Wei Jiao, Yan Aleya, Lotfi Maida, Marcello Wang, Cong-Yi Zangerl, Barbara Genini, Sem Ray, Kunal Goldman, Emanuel Ji, Jiafu Alexandrov, Andrei V. Sun, Dianjun Gu, Weikuan Wang, Yongjun Sci Total Environ Article The most effective measure to prevent or stop the spread of infectious diseases is the early identification and isolation of infected individuals through comprehensive screening. At present, in the COVID-19 pandemic, such screening is often limited to isolated regions as determined by local governments. Screening of potentially infectious individuals should be conducted through coordinated national or global unified actions. Our current research focuses on using resources to conduct comprehensive national and regional regular testing with a risk rate based, algorithmic guided, multiple-level, pooled testing strategy. Here, combining methodologies with mathematical logistic models, we present an analytic procedure of an overall plan for coordinating state, national, or global testing. The proposed plan includes three parts 1) organization, resource allocation, and distribution; 2) screening based on different risk levels and business types; and 3) algorithm guided, multiple level, continuously screening the entire population in a region. This strategy will overcome the false positive and negative results in the polymerase chain reaction (PCR) test and missing samples during initial tests. Based on our proposed protocol, the population screening of 300,000,000 in the US can be done weekly with between 15,000,000 and 6,000,000 test kits. The strategy can be used for population screening for current COVID-19 and any future severe infectious disease when drugs or vaccines are not available. Elsevier B.V. 2021-04-15 2020-12-24 /pmc/articles/PMC7833620/ /pubmed/33387925 http://dx.doi.org/10.1016/j.scitotenv.2020.144251 Text en © 2020 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Gu, Tianshu
Yao, Lan
Meng, Xia
Graff, J. Carolyn
Thomason, Donald
Li, Jing
Dong, Wei
Jiao, Yan
Aleya, Lotfi
Maida, Marcello
Wang, Cong-Yi
Zangerl, Barbara
Genini, Sem
Ray, Kunal
Goldman, Emanuel
Ji, Jiafu
Alexandrov, Andrei V.
Sun, Dianjun
Gu, Weikuan
Wang, Yongjun
A cost-effective plan for global testing - an infection rate stratified, algorithm guided, multiple-level, continuously pooled testing strategy
title A cost-effective plan for global testing - an infection rate stratified, algorithm guided, multiple-level, continuously pooled testing strategy
title_full A cost-effective plan for global testing - an infection rate stratified, algorithm guided, multiple-level, continuously pooled testing strategy
title_fullStr A cost-effective plan for global testing - an infection rate stratified, algorithm guided, multiple-level, continuously pooled testing strategy
title_full_unstemmed A cost-effective plan for global testing - an infection rate stratified, algorithm guided, multiple-level, continuously pooled testing strategy
title_short A cost-effective plan for global testing - an infection rate stratified, algorithm guided, multiple-level, continuously pooled testing strategy
title_sort cost-effective plan for global testing - an infection rate stratified, algorithm guided, multiple-level, continuously pooled testing strategy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833620/
https://www.ncbi.nlm.nih.gov/pubmed/33387925
http://dx.doi.org/10.1016/j.scitotenv.2020.144251
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