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Quantitative assessment of the effects of massive nucleic acid testing in controlling a COVID-19 outbreak
BACKGROUND: From 20 July to 26 August 2021, local outbreaks of COVID-19 occurred in Nanjing City and Yangzhou City (Jiangsu Province, China). We analyzed the characteristics of these outbreaks in an effort to develop specific and effective intervention strategies. METHODS: Publicly available data on...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652905/ https://www.ncbi.nlm.nih.gov/pubmed/36371145 http://dx.doi.org/10.1186/s12879-022-07816-2 |
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author | Zhu, Wenlong Zhu, Yue Wen, Zexuan Zheng, Bo Xu, Ao Yao, Ye Wang, Weibing |
author_facet | Zhu, Wenlong Zhu, Yue Wen, Zexuan Zheng, Bo Xu, Ao Yao, Ye Wang, Weibing |
author_sort | Zhu, Wenlong |
collection | PubMed |
description | BACKGROUND: From 20 July to 26 August 2021, local outbreaks of COVID-19 occurred in Nanjing City and Yangzhou City (Jiangsu Province, China). We analyzed the characteristics of these outbreaks in an effort to develop specific and effective intervention strategies. METHODS: Publicly available data on the characteristics of the COVID-19 outbreaks in Jiangsu Province were collected. Logistic regression was used to assess the association of age and sex with clinical severity. Analysis of onset dates, generation time distributions, and locations were used to estimate the mean transmission distance. A branching process model was used to evaluate different management strategies. RESULTS: From 20 July to 26 August 2021, 820 patients were diagnosed with COVID-19 in Jiangsu Province, with 235 patients (28.7%) from Nanjing, 570 (69.5%) from Yangzhou, and 15 (1.8%) from other cities. Overall, 57.9% of the patients were female, 13.7% were under 20 years-old, and 58.3% had moderate disease status. The mean transmission distance was 4.12 km, and closed-loop management of the area within 2.23 km of cases seemed sufficient to control an outbreak. The model predicted that the cumulative cases in Yangzhou would increase from 311 to 642 if the interval between rounds of nucleic acid amplification testing (NAAT) increased from 1 to 6 days. It also predicted there would be 44.7% more patients if the NAAT started 10 days (rather than 0 days) after diagnosis of the first case. The proportion of cases detected by NAAT would increase from 11.16 to 44.12% when the rounds of NAAT increased from 1 to 7 within 17 days. When the effective vaccine coverage was 50%, the outbreak would be controlled even when using the most relaxed non-pharmaceutical interventions. CONCLUSIONS: The model predicted that a timely closed-loop management of a 2.23 km area around positive COVID-19 cases was sufficient to control the outbreak. Prompt serial NAAT is likely to contain an outbreak quickly, and our model results indicated that three rounds of NAAT sufficiently controlled local transmission. Trial registration We did not involve clinical trial. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07816-2. |
format | Online Article Text |
id | pubmed-9652905 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96529052022-11-14 Quantitative assessment of the effects of massive nucleic acid testing in controlling a COVID-19 outbreak Zhu, Wenlong Zhu, Yue Wen, Zexuan Zheng, Bo Xu, Ao Yao, Ye Wang, Weibing BMC Infect Dis Research BACKGROUND: From 20 July to 26 August 2021, local outbreaks of COVID-19 occurred in Nanjing City and Yangzhou City (Jiangsu Province, China). We analyzed the characteristics of these outbreaks in an effort to develop specific and effective intervention strategies. METHODS: Publicly available data on the characteristics of the COVID-19 outbreaks in Jiangsu Province were collected. Logistic regression was used to assess the association of age and sex with clinical severity. Analysis of onset dates, generation time distributions, and locations were used to estimate the mean transmission distance. A branching process model was used to evaluate different management strategies. RESULTS: From 20 July to 26 August 2021, 820 patients were diagnosed with COVID-19 in Jiangsu Province, with 235 patients (28.7%) from Nanjing, 570 (69.5%) from Yangzhou, and 15 (1.8%) from other cities. Overall, 57.9% of the patients were female, 13.7% were under 20 years-old, and 58.3% had moderate disease status. The mean transmission distance was 4.12 km, and closed-loop management of the area within 2.23 km of cases seemed sufficient to control an outbreak. The model predicted that the cumulative cases in Yangzhou would increase from 311 to 642 if the interval between rounds of nucleic acid amplification testing (NAAT) increased from 1 to 6 days. It also predicted there would be 44.7% more patients if the NAAT started 10 days (rather than 0 days) after diagnosis of the first case. The proportion of cases detected by NAAT would increase from 11.16 to 44.12% when the rounds of NAAT increased from 1 to 7 within 17 days. When the effective vaccine coverage was 50%, the outbreak would be controlled even when using the most relaxed non-pharmaceutical interventions. CONCLUSIONS: The model predicted that a timely closed-loop management of a 2.23 km area around positive COVID-19 cases was sufficient to control the outbreak. Prompt serial NAAT is likely to contain an outbreak quickly, and our model results indicated that three rounds of NAAT sufficiently controlled local transmission. Trial registration We did not involve clinical trial. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07816-2. BioMed Central 2022-11-12 /pmc/articles/PMC9652905/ /pubmed/36371145 http://dx.doi.org/10.1186/s12879-022-07816-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Zhu, Wenlong Zhu, Yue Wen, Zexuan Zheng, Bo Xu, Ao Yao, Ye Wang, Weibing Quantitative assessment of the effects of massive nucleic acid testing in controlling a COVID-19 outbreak |
title | Quantitative assessment of the effects of massive nucleic acid testing in controlling a COVID-19 outbreak |
title_full | Quantitative assessment of the effects of massive nucleic acid testing in controlling a COVID-19 outbreak |
title_fullStr | Quantitative assessment of the effects of massive nucleic acid testing in controlling a COVID-19 outbreak |
title_full_unstemmed | Quantitative assessment of the effects of massive nucleic acid testing in controlling a COVID-19 outbreak |
title_short | Quantitative assessment of the effects of massive nucleic acid testing in controlling a COVID-19 outbreak |
title_sort | quantitative assessment of the effects of massive nucleic acid testing in controlling a covid-19 outbreak |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652905/ https://www.ncbi.nlm.nih.gov/pubmed/36371145 http://dx.doi.org/10.1186/s12879-022-07816-2 |
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