An Empirical Study on the Transformation of Asymptomatic Infected Persons into Confirmed Cases in Mainland China During the COVID-19 Pandemic

Liu Fangjun; Deng Xiaokai

doi:doi:10.11648/j.si.20231104.11

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An Empirical Study on the Transformation of Asymptomatic Infected Persons into Confirmed Cases in Mainland China During the COVID-19 Pandemic

Liu Fangjun, Deng Xiaokai

Published in Science Innovation (Volume 11, Issue 4)

Received: 5 May 2023 Accepted: 4 July 2023 Published: 11 July 2023

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Abstract

This study empirically investigates the conversion of asymptomatic infections to confirmed cases in mainland China during the COVID-19 pandemic using time series data. The study finds that asymptomatic infections from overseas and those released from medical observation on the same day do not have a significant impact on the conversion to confirmed cases on the same day. However, local asymptomatic infections and those still under medical observation have a significant impact on the conversion to confirmed cases on the same day. Specifically, on average, approximately 142 out of every 10,000 local asymptomatic infections will convert to confirmed cases, while approximately 17 out of every 10,000 asymptomatic infections still under medical observation will convert to confirmed cases. Additionally, the impact of asymptomatic infections from overseas on the conversion to confirmed cases is lagged, with a lag of up to 23 days. These findings are important for understanding the process of asymptomatic infections converting to confirmed cases and controlling the spread of the virus.

Published in	Science Innovation (Volume 11, Issue 4)
DOI	10.11648/j.si.20231104.11
Page(s)	179-183
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2023. Published by Science Publishing Group

Keywords

Novel Coronavirus, Asymptomatic Infected Persons, Confirmed Cases, Time Series Data

References

[1]	Dickey. D. A, W. A. Fuller. Distribution of the estimators for autoregressive time series with aunit root. Jounal of the American Statistical Association, 1979, 427-431.
[2]	孙敬水. 计量经济学 (第三版) [M]. 北京: 清华大学出版社, 2014年7月.
[3]	郑雯雯, 陆月明, 潘亚萍, 鲁文婧, 王心意, 李艳, 周礼霞. 新型冠状病毒肺炎无症状感染者心理困扰的状况及影响因素分析 [J]. 海军医学杂志, 2022, 43 (12).
[4]	周贵香, 吴雯, 王炎, 陆兵, 高雨蒙, 彭红红, 施超. 新型冠状病毒无症状感染特征研究 [J]. 南京医科大学学报 (自然科学版). 2022, 42 (09).
[5]	申川, 秦浩, 马路园, 李星宇, 宋枚芳, 张云涛, 高会霞, 王洋, 戴二黑, 赵彩彦. 新型冠状病毒肺炎无症状感染者的临床与免疫学特征分析 [J]. 传染病信息. 2022, 35 (04).
[6]	谭晓罗, 刘勋, 谭文艳, 谭徽, 李映霞, 陈柏塘, 朱韩武, 刘卫. 郴州市10例新冠肺炎无症状感染者的传染性分析 [J]. 实用预防医学. 2022, 29 (06).
[7]	马千里, 郭鑫, 申一骏. 基于SIR-B对无症状感染者在COVID-19中的分析与预测 [J]. 山西大学学报 (自然科学版), 2022, 45 (06).
[8]	黄梓, 健周滔. 新型冠状病毒肺炎无症状感染者研究现状 [J]. 现代医药卫生. 2021, 37 (22).
[9]	孙廷哲, 崔隽. 模拟新型冠状病毒肺炎无症状感染者传播风险 [J]. 中山大学学报 (自然科学版). 2021, 60 (05).
[10]	朱妮, 曹磊, 杨国婧, 陈飒, 宁少奇, 李欣欣, 年云鹏, 王刚, 张义. 陕西本土新型冠状病毒肺炎无症状感染者流行特征及传播途径 [J]. 西安交通大学学报 (医学版), 2021, 42 (02).
[11]	刘巧, 刘珏, 刘民. 无症状感染者对COVID-19流行的影响及其防控措施研究 [J]. 中国全科医学. 2021, 24 (08).
[12]	鲁丽娜, 华春秀, 张昱, 闫一杰. 2019冠状病毒病患者与无症状感染者不同暴露时间咽拭子和粪便标本病毒核酸检测结果分析 [J]. 病毒学报. 2020, 36 (06).
[13]	何飞, 邓旻, 董雷, 仲成, 蔡宛如. 新型冠状病毒肺炎无症状感染者早期中医干预探讨 [J]. 2020年 (第四十二届) 浙江省医学会呼吸系病学术大会论文汇编.
[14]	王艳芳, 陈建普, 王翔. 新型冠状病毒肺炎无症状感染者的CT影像分析 [J]. 武汉大学学报 (医学版). 2020, 41 (03).
[15]	罗晓琼, 刘华宝, 谢鑫, 宋翊, 冉传生, 魏大荣, 陈少云, 向阳, 赵玉华, 唐军. 新型冠状病毒无症状感染者50例中西医结合治疗临床观察 [J]. 成都中医药大学学报, 2020, 43 (04).

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APA Style

Liu Fangjun, Deng Xiaokai. (2023). An Empirical Study on the Transformation of Asymptomatic Infected Persons into Confirmed Cases in Mainland China During the COVID-19 Pandemic. Science Innovation, 11(4), 179-183. https://doi.org/10.11648/j.si.20231104.11

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ACS Style

Liu Fangjun; Deng Xiaokai. An Empirical Study on the Transformation of Asymptomatic Infected Persons into Confirmed Cases in Mainland China During the COVID-19 Pandemic. Sci. Innov. 2023, 11(4), 179-183. doi: 10.11648/j.si.20231104.11

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AMA Style

Liu Fangjun, Deng Xiaokai. An Empirical Study on the Transformation of Asymptomatic Infected Persons into Confirmed Cases in Mainland China During the COVID-19 Pandemic. Sci Innov. 2023;11(4):179-183. doi: 10.11648/j.si.20231104.11

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@article{10.11648/j.si.20231104.11,
  author = {Liu Fangjun and Deng Xiaokai},
  title = {An Empirical Study on the Transformation of Asymptomatic Infected Persons into Confirmed Cases in Mainland China During the COVID-19 Pandemic},
  journal = {Science Innovation},
  volume = {11},
  number = {4},
  pages = {179-183},
  doi = {10.11648/j.si.20231104.11},
  url = {https://doi.org/10.11648/j.si.20231104.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20231104.11},
  abstract = {This study empirically investigates the conversion of asymptomatic infections to confirmed cases in mainland China during the COVID-19 pandemic using time series data. The study finds that asymptomatic infections from overseas and those released from medical observation on the same day do not have a significant impact on the conversion to confirmed cases on the same day. However, local asymptomatic infections and those still under medical observation have a significant impact on the conversion to confirmed cases on the same day. Specifically, on average, approximately 142 out of every 10,000 local asymptomatic infections will convert to confirmed cases, while approximately 17 out of every 10,000 asymptomatic infections still under medical observation will convert to confirmed cases. Additionally, the impact of asymptomatic infections from overseas on the conversion to confirmed cases is lagged, with a lag of up to 23 days. These findings are important for understanding the process of asymptomatic infections converting to confirmed cases and controlling the spread of the virus.},
 year = {2023}
}

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TY  - JOUR
T1  - An Empirical Study on the Transformation of Asymptomatic Infected Persons into Confirmed Cases in Mainland China During the COVID-19 Pandemic
AU  - Liu Fangjun
AU  - Deng Xiaokai
Y1  - 2023/07/11
PY  - 2023
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DO  - 10.11648/j.si.20231104.11
T2  - Science Innovation
JF  - Science Innovation
JO  - Science Innovation
SP  - 179
EP  - 183
PB  - Science Publishing Group
SN  - 2328-787X
UR  - https://doi.org/10.11648/j.si.20231104.11
AB  - This study empirically investigates the conversion of asymptomatic infections to confirmed cases in mainland China during the COVID-19 pandemic using time series data. The study finds that asymptomatic infections from overseas and those released from medical observation on the same day do not have a significant impact on the conversion to confirmed cases on the same day. However, local asymptomatic infections and those still under medical observation have a significant impact on the conversion to confirmed cases on the same day. Specifically, on average, approximately 142 out of every 10,000 local asymptomatic infections will convert to confirmed cases, while approximately 17 out of every 10,000 asymptomatic infections still under medical observation will convert to confirmed cases. Additionally, the impact of asymptomatic infections from overseas on the conversion to confirmed cases is lagged, with a lag of up to 23 days. These findings are important for understanding the process of asymptomatic infections converting to confirmed cases and controlling the spread of the virus.
VL  - 11
IS  - 4
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Author Information

Liu Fangjun

School of Economics and Finance, Zhanjiang Institute of Science and Technology, Zhanjiang, China
Deng Xiaokai

School of Economics and Finance, Zhanjiang Institute of Science and Technology, Zhanjiang, China

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Plain Text BibTeX RIS

APA Style

Liu Fangjun, Deng Xiaokai. (2023). An Empirical Study on the Transformation of Asymptomatic Infected Persons into Confirmed Cases in Mainland China During the COVID-19 Pandemic. Science Innovation, 11(4), 179-183. https://doi.org/10.11648/j.si.20231104.11

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ACS Style

Liu Fangjun; Deng Xiaokai. An Empirical Study on the Transformation of Asymptomatic Infected Persons into Confirmed Cases in Mainland China During the COVID-19 Pandemic. Sci. Innov. 2023, 11(4), 179-183. doi: 10.11648/j.si.20231104.11

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AMA Style

Liu Fangjun, Deng Xiaokai. An Empirical Study on the Transformation of Asymptomatic Infected Persons into Confirmed Cases in Mainland China During the COVID-19 Pandemic. Sci Innov. 2023;11(4):179-183. doi: 10.11648/j.si.20231104.11

Copy | Download

@article{10.11648/j.si.20231104.11,
  author = {Liu Fangjun and Deng Xiaokai},
  title = {An Empirical Study on the Transformation of Asymptomatic Infected Persons into Confirmed Cases in Mainland China During the COVID-19 Pandemic},
  journal = {Science Innovation},
  volume = {11},
  number = {4},
  pages = {179-183},
  doi = {10.11648/j.si.20231104.11},
  url = {https://doi.org/10.11648/j.si.20231104.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20231104.11},
  abstract = {This study empirically investigates the conversion of asymptomatic infections to confirmed cases in mainland China during the COVID-19 pandemic using time series data. The study finds that asymptomatic infections from overseas and those released from medical observation on the same day do not have a significant impact on the conversion to confirmed cases on the same day. However, local asymptomatic infections and those still under medical observation have a significant impact on the conversion to confirmed cases on the same day. Specifically, on average, approximately 142 out of every 10,000 local asymptomatic infections will convert to confirmed cases, while approximately 17 out of every 10,000 asymptomatic infections still under medical observation will convert to confirmed cases. Additionally, the impact of asymptomatic infections from overseas on the conversion to confirmed cases is lagged, with a lag of up to 23 days. These findings are important for understanding the process of asymptomatic infections converting to confirmed cases and controlling the spread of the virus.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - An Empirical Study on the Transformation of Asymptomatic Infected Persons into Confirmed Cases in Mainland China During the COVID-19 Pandemic
AU  - Liu Fangjun
AU  - Deng Xiaokai
Y1  - 2023/07/11
PY  - 2023
N1  - https://doi.org/10.11648/j.si.20231104.11
DO  - 10.11648/j.si.20231104.11
T2  - Science Innovation
JF  - Science Innovation
JO  - Science Innovation
SP  - 179
EP  - 183
PB  - Science Publishing Group
SN  - 2328-787X
UR  - https://doi.org/10.11648/j.si.20231104.11
AB  - This study empirically investigates the conversion of asymptomatic infections to confirmed cases in mainland China during the COVID-19 pandemic using time series data. The study finds that asymptomatic infections from overseas and those released from medical observation on the same day do not have a significant impact on the conversion to confirmed cases on the same day. However, local asymptomatic infections and those still under medical observation have a significant impact on the conversion to confirmed cases on the same day. Specifically, on average, approximately 142 out of every 10,000 local asymptomatic infections will convert to confirmed cases, while approximately 17 out of every 10,000 asymptomatic infections still under medical observation will convert to confirmed cases. Additionally, the impact of asymptomatic infections from overseas on the conversion to confirmed cases is lagged, with a lag of up to 23 days. These findings are important for understanding the process of asymptomatic infections converting to confirmed cases and controlling the spread of the virus.
VL  - 11
IS  - 4
ER  -

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