PandemieGrippaleV1, PubMed, Checkpoint, bibRecord, 000148

Forecasting influenza activity using self-adaptive AI model and multi-source data in Chongqing, China.

Identifieur interne : 000148 ( PubMed/Checkpoint ); précédent : 000147; suivant : 000149

Forecasting influenza activity using self-adaptive AI model and multi-source data in Chongqing, China.

Source :

EBioMedicine [ 2352-3964 ] ; 2019.

RBID : pubmed:31477561

Descripteurs français

KwdFr :
- Algorithmes, Chine (épidémiologie), Grippe humaine (épidémiologie), Humains, Modèles statistiques, Pandémies, Prévision (), Surveillance de la population ().
MESH :
- épidémiologie : Chine, Grippe humaine.
- Algorithmes, Humains, Modèles statistiques, Pandémies, Prévision, Surveillance de la population.
Wicri :
- geographic : République populaire de Chine.

English descriptors

KwdEn :
- Algorithms, China (epidemiology), Forecasting (methods), Humans, Influenza, Human (epidemiology), Models, Statistical, Pandemics, Population Surveillance (methods).
MESH :
- geographic , epidemiology : China.
- epidemiology : Influenza, Human.
- methods : Forecasting, Population Surveillance.
- Algorithms, Humans, Models, Statistical, Pandemics.

Abstract

Early detection of influenza activity followed by timely response is a critical component of preparedness for seasonal influenza epidemic and influenza pandemic. However, most relevant studies were conducted at the regional or national level with regular seasonal influenza trends. There are few feasible strategies to forecast influenza activity at the local level with irregular trends.

DOI: 10.1016/j.ebiom.2019.08.024
PubMed: 31477561

Affiliations:

Links toward previous steps (curation, corpus...)

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pubmed:31477561

Le document en format XML

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<author><name sortKey="Li, Yafei" sort="Li, Yafei" uniqKey="Li Y" first="Yafei" last="Li">Yafei Li</name>
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<author><name sortKey="Li, Qin" sort="Li, Qin" uniqKey="Li Q" first="Qin" last="Li">Qin Li</name>
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<author><name sortKey="Lu, Shaofeng" sort="Lu, Shaofeng" uniqKey="Lu S" first="Shaofeng" last="Lu">Shaofeng Lu</name>
<affiliation wicri:level="3"><nlm:affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen</wicri:regionArea>
<placeName><settlement type="city">Shenzhen</settlement>
<region type="province">Guangdong</region>
</placeName>
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<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Chongqing Municipal Center for Disease Control and Prevention, Chongqing</wicri:regionArea>
<wicri:noRegion>Chongqing</wicri:noRegion>
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<author><name sortKey="Shen, Chaobo" sort="Shen, Chaobo" uniqKey="Shen C" first="Chaobo" last="Shen">Chaobo Shen</name>
<affiliation wicri:level="3"><nlm:affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen</wicri:regionArea>
<placeName><settlement type="city">Shenzhen</settlement>
<region type="province">Guangdong</region>
</placeName>
</affiliation>
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<author><name sortKey="Tang, Wenge" sort="Tang, Wenge" uniqKey="Tang W" first="Wenge" last="Tang">Wenge Tang</name>
<affiliation wicri:level="1"><nlm:affiliation>Chongqing Municipal Center for Disease Control and Prevention, Chongqing, People's Republic of China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Chongqing Municipal Center for Disease Control and Prevention, Chongqing</wicri:regionArea>
<wicri:noRegion>Chongqing</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Rong, Rong" sort="Rong, Rong" uniqKey="Rong R" first="Rong" last="Rong">Rong Rong</name>
<affiliation wicri:level="1"><nlm:affiliation>Chongqing Municipal Center for Disease Control and Prevention, Chongqing, People's Republic of China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Chongqing Municipal Center for Disease Control and Prevention, Chongqing</wicri:regionArea>
<wicri:noRegion>Chongqing</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Hong, Boran" sort="Hong, Boran" uniqKey="Hong B" first="Boran" last="Hong">Boran Hong</name>
<affiliation wicri:level="3"><nlm:affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen</wicri:regionArea>
<placeName><settlement type="city">Shenzhen</settlement>
<region type="province">Guangdong</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Ning, Yi" sort="Ning, Yi" uniqKey="Ning Y" first="Yi" last="Ning">Yi Ning</name>
<affiliation wicri:level="3"><nlm:affiliation>Meinian Institute of Health, Beijing, People's Republic of China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Meinian Institute of Health, Beijing</wicri:regionArea>
<placeName><settlement type="city">Pékin</settlement>
</placeName>
</affiliation>
</author>
<author><name sortKey="Long, Dongyan" sort="Long, Dongyan" uniqKey="Long D" first="Dongyan" last="Long">Dongyan Long</name>
<affiliation wicri:level="3"><nlm:affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen</wicri:regionArea>
<placeName><settlement type="city">Shenzhen</settlement>
<region type="province">Guangdong</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Xu, Jiaying" sort="Xu, Jiaying" uniqKey="Xu J" first="Jiaying" last="Xu">Jiaying Xu</name>
<affiliation wicri:level="3"><nlm:affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen</wicri:regionArea>
<placeName><settlement type="city">Shenzhen</settlement>
<region type="province">Guangdong</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Shi, Xuanling" sort="Shi, Xuanling" uniqKey="Shi X" first="Xuanling" last="Shi">Xuanling Shi</name>
<affiliation wicri:level="3"><nlm:affiliation>Comprehensive AIDS Research Center and Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, Tsinghua University, Beijing, People's Republic of China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Comprehensive AIDS Research Center and Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, Tsinghua University, Beijing</wicri:regionArea>
<placeName><settlement type="city">Pékin</settlement>
</placeName>
</affiliation>
</author>
<author><name sortKey="Yang, Zhihong" sort="Yang, Zhihong" uniqKey="Yang Z" first="Zhihong" last="Yang">Zhihong Yang</name>
<affiliation wicri:level="3"><nlm:affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen</wicri:regionArea>
<placeName><settlement type="city">Shenzhen</settlement>
<region type="province">Guangdong</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Zhang, Qi" sort="Zhang, Qi" uniqKey="Zhang Q" first="Qi" last="Zhang">Qi Zhang</name>
<affiliation wicri:level="3"><nlm:affiliation>Comprehensive AIDS Research Center and Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, Tsinghua University, Beijing, People's Republic of China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Comprehensive AIDS Research Center and Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, Tsinghua University, Beijing</wicri:regionArea>
<placeName><settlement type="city">Pékin</settlement>
</placeName>
</affiliation>
</author>
<author><name sortKey="Zhuang, Ziqi" sort="Zhuang, Ziqi" uniqKey="Zhuang Z" first="Ziqi" last="Zhuang">Ziqi Zhuang</name>
<affiliation wicri:level="3"><nlm:affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen</wicri:regionArea>
<placeName><settlement type="city">Shenzhen</settlement>
<region type="province">Guangdong</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Zhang, Linqi" sort="Zhang, Linqi" uniqKey="Zhang L" first="Linqi" last="Zhang">Linqi Zhang</name>
<affiliation wicri:level="3"><nlm:affiliation>Comprehensive AIDS Research Center and Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, Tsinghua University, Beijing, People's Republic of China. Electronic address: zhanglinqi@mail.tsinghua.edu.cn.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Comprehensive AIDS Research Center and Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, Tsinghua University, Beijing</wicri:regionArea>
<placeName><settlement type="city">Pékin</settlement>
</placeName>
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<author><name sortKey="Xiao, Jing" sort="Xiao, Jing" uniqKey="Xiao J" first="Jing" last="Xiao">Jing Xiao</name>
<affiliation wicri:level="3"><nlm:affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China. Electronic address: xiaojing661@pingan.com.cn.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen</wicri:regionArea>
<placeName><settlement type="city">Shenzhen</settlement>
<region type="province">Guangdong</region>
</placeName>
</affiliation>
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<author><name sortKey="Li, Yafei" sort="Li, Yafei" uniqKey="Li Y" first="Yafei" last="Li">Yafei Li</name>
<affiliation wicri:level="1"><nlm:affiliation>Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, People's Republic of China. Electronic address: liyafei2008@hotmail.com.</nlm:affiliation>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing</wicri:regionArea>
<wicri:noRegion>Chongqing</wicri:noRegion>
</affiliation>
</author>
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<series><title level="j">EBioMedicine</title>
<idno type="eISSN">2352-3964</idno>
<imprint><date when="2019" type="published">2019</date>
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<term>China (epidemiology)</term>
<term>Forecasting (methods)</term>
<term>Humans</term>
<term>Influenza, Human (epidemiology)</term>
<term>Models, Statistical</term>
<term>Pandemics</term>
<term>Population Surveillance (methods)</term>
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<term>Chine (épidémiologie)</term>
<term>Grippe humaine (épidémiologie)</term>
<term>Humains</term>
<term>Modèles statistiques</term>
<term>Pandémies</term>
<term>Prévision ()</term>
<term>Surveillance de la population ()</term>
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<term>Population Surveillance</term>
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<term>Prévision</term>
<term>Surveillance de la population</term>
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<front><div type="abstract" xml:lang="en">Early detection of influenza activity followed by timely response is a critical component of preparedness for seasonal influenza epidemic and influenza pandemic. However, most relevant studies were conducted at the regional or national level with regular seasonal influenza trends. There are few feasible strategies to forecast influenza activity at the local level with irregular trends.</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">31477561</PMID>
<DateCompleted><Year>2020</Year>
<Month>02</Month>
<Day>04</Day>
</DateCompleted>
<DateRevised><Year>2020</Year>
<Month>02</Month>
<Day>04</Day>
</DateRevised>
<Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">2352-3964</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>47</Volume>
<PubDate><Year>2019</Year>
<Month>Sep</Month>
</PubDate>
</JournalIssue>
<Title>EBioMedicine</Title>
<ISOAbbreviation>EBioMedicine</ISOAbbreviation>
</Journal>
<ArticleTitle>Forecasting influenza activity using self-adaptive AI model and multi-source data in Chongqing, China.</ArticleTitle>
<Pagination><MedlinePgn>284-292</MedlinePgn>
</Pagination>
<ELocationID EIdType="pii" ValidYN="Y">S2352-3964(19)30546-8</ELocationID>
<ELocationID EIdType="doi" ValidYN="Y">10.1016/j.ebiom.2019.08.024</ELocationID>
<Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Early detection of influenza activity followed by timely response is a critical component of preparedness for seasonal influenza epidemic and influenza pandemic. However, most relevant studies were conducted at the regional or national level with regular seasonal influenza trends. There are few feasible strategies to forecast influenza activity at the local level with irregular trends.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">Multi-source electronic data, including historical percentage of influenza-like illness (ILI%), weather data, Baidu search index and Sina Weibo data of Chongqing, China, were collected and integrated into an innovative Self-adaptive AI Model (SAAIM), which was constructed by integrating Seasonal Autoregressive Integrated Moving Average model and XGBoost model using a self-adaptive weight adjustment mechanism. SAAIM was applied to ILI% forecast in Chongqing from 2017 to 2018, of which the performance was compared with three previously available models on forecasting.</AbstractText>
<AbstractText Label="FINDINGS" NlmCategory="RESULTS">ILI% showed an irregular seasonal trend from 2012 to 2018 in Chongqing. Compared with three reference models, SAAIM achieved the best performance on forecasting ILI% of Chongqing with the mean absolute percentage error (MAPE) of 11·9%, 7·5%, and 11·9% during the periods of the year 2014-2016, 2017, and 2018 respectively. Among the three categories of source data, historical influenza activity contributed the most to the forecast accuracy by decreasing the MAPE by 19·6%, 43·1%, and 11·1%, followed by weather information (MAPE reduced by 3·3%, 17·1%, and 2·2%), and Internet-related public sentiment data (MAPE reduced by 1·1%, 0·9%, and 1·3%).</AbstractText>
<AbstractText Label="INTERPRETATION" NlmCategory="CONCLUSIONS">Accurate influenza forecast in areas with irregular seasonal influenza trends can be made by SAAIM with multi-source electronic data.</AbstractText>
<CopyrightInformation>Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Su</LastName>
<ForeName>Kun</ForeName>
<Initials>K</Initials>
<AffiliationInfo><Affiliation>Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, People's Republic of China; Chongqing Municipal Center for Disease Control and Prevention, Chongqing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Xu</LastName>
<ForeName>Liang</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Li</LastName>
<ForeName>Guanqiao</ForeName>
<Initials>G</Initials>
<AffiliationInfo><Affiliation>Comprehensive AIDS Research Center and Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, Tsinghua University, Beijing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Ruan</LastName>
<ForeName>Xiaowen</ForeName>
<Initials>X</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Li</LastName>
<ForeName>Xian</ForeName>
<Initials>X</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Deng</LastName>
<ForeName>Pan</ForeName>
<Initials>P</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Li</LastName>
<ForeName>Xinmi</ForeName>
<Initials>X</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Li</LastName>
<ForeName>Qin</ForeName>
<Initials>Q</Initials>
<AffiliationInfo><Affiliation>Chongqing Municipal Center for Disease Control and Prevention, Chongqing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Chen</LastName>
<ForeName>Xianxian</ForeName>
<Initials>X</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Xiong</LastName>
<ForeName>Yu</ForeName>
<Initials>Y</Initials>
<AffiliationInfo><Affiliation>Chongqing Municipal Center for Disease Control and Prevention, Chongqing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Lu</LastName>
<ForeName>Shaofeng</ForeName>
<Initials>S</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Qi</LastName>
<ForeName>Li</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>Chongqing Municipal Center for Disease Control and Prevention, Chongqing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Shen</LastName>
<ForeName>Chaobo</ForeName>
<Initials>C</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Tang</LastName>
<ForeName>Wenge</ForeName>
<Initials>W</Initials>
<AffiliationInfo><Affiliation>Chongqing Municipal Center for Disease Control and Prevention, Chongqing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Rong</LastName>
<ForeName>Rong</ForeName>
<Initials>R</Initials>
<AffiliationInfo><Affiliation>Chongqing Municipal Center for Disease Control and Prevention, Chongqing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Hong</LastName>
<ForeName>Boran</ForeName>
<Initials>B</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Ning</LastName>
<ForeName>Yi</ForeName>
<Initials>Y</Initials>
<AffiliationInfo><Affiliation>Meinian Institute of Health, Beijing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Long</LastName>
<ForeName>Dongyan</ForeName>
<Initials>D</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Xu</LastName>
<ForeName>Jiaying</ForeName>
<Initials>J</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Shi</LastName>
<ForeName>Xuanling</ForeName>
<Initials>X</Initials>
<AffiliationInfo><Affiliation>Comprehensive AIDS Research Center and Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, Tsinghua University, Beijing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Yang</LastName>
<ForeName>Zhihong</ForeName>
<Initials>Z</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Zhang</LastName>
<ForeName>Qi</ForeName>
<Initials>Q</Initials>
<AffiliationInfo><Affiliation>Comprehensive AIDS Research Center and Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, Tsinghua University, Beijing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Zhuang</LastName>
<ForeName>Ziqi</ForeName>
<Initials>Z</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Zhang</LastName>
<ForeName>Linqi</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>Comprehensive AIDS Research Center and Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, Tsinghua University, Beijing, People's Republic of China. Electronic address: zhanglinqi@mail.tsinghua.edu.cn.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Xiao</LastName>
<ForeName>Jing</ForeName>
<Initials>J</Initials>
<AffiliationInfo><Affiliation>Ping An Technology (Shenzhen) Co., Ltd, Shenzhen, People's Republic of China. Electronic address: xiaojing661@pingan.com.cn.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Li</LastName>
<ForeName>Yafei</ForeName>
<Initials>Y</Initials>
<AffiliationInfo><Affiliation>Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, People's Republic of China. Electronic address: liyafei2008@hotmail.com.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2019</Year>
<Month>08</Month>
<Day>30</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>Netherlands</Country>
<MedlineTA>EBioMedicine</MedlineTA>
<NlmUniqueID>101647039</NlmUniqueID>
<ISSNLinking>2352-3964</ISSNLinking>
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<CitationSubset>IM</CitationSubset>
<MeshHeadingList><MeshHeading><DescriptorName UI="D000465" MajorTopicYN="N">Algorithms</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D002681" MajorTopicYN="N" Type="Geographic">China</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005544" MajorTopicYN="Y">Forecasting</DescriptorName>
<QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D007251" MajorTopicYN="N">Influenza, Human</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015233" MajorTopicYN="Y">Models, Statistical</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011159" MajorTopicYN="Y">Population Surveillance</DescriptorName>
<QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName>
</MeshHeading>
</MeshHeadingList>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">AI</Keyword>
<Keyword MajorTopicYN="N">Forecast</Keyword>
<Keyword MajorTopicYN="N">Influenza</Keyword>
<Keyword MajorTopicYN="N">Influenza-like illness</Keyword>
<Keyword MajorTopicYN="N">Multi-source electronic data</Keyword>
</KeywordList>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2019</Year>
<Month>05</Month>
<Day>24</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="revised"><Year>2019</Year>
<Month>08</Month>
<Day>09</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted"><Year>2019</Year>
<Month>08</Month>
<Day>09</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed"><Year>2019</Year>
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Forecasting influenza activity using self-adaptive AI model and multi-source data in Chongqing, China.

Forecasting influenza activity using self-adaptive AI model and multi-source data in Chongqing, China.

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