Who Gets the Flu? Individualized Validation of Influenza-like Illness in Urban Spaces

Urban dwellers are exposed to communicable diseases, such as influenza, in various urban spaces. Current disease models are able to predict health outcomes at the individual scale but are mostly validated at coarse scales due to the lack of fine-scaled ground truth data. Further, a large number of t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of environmental research and public health 2023-05, Vol.20 (10), p.5865
Hauptverfasser: Zhong, Shiran, Ma, Fenglong, Gao, Jing, Bian, Ling
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 10
container_start_page 5865
container_title International journal of environmental research and public health
container_volume 20
creator Zhong, Shiran
Ma, Fenglong
Gao, Jing
Bian, Ling
description Urban dwellers are exposed to communicable diseases, such as influenza, in various urban spaces. Current disease models are able to predict health outcomes at the individual scale but are mostly validated at coarse scales due to the lack of fine-scaled ground truth data. Further, a large number of transmission-driving factors have been considered in these models. Because of the lack of individual-scaled validations, the effectiveness of factors at their intended scale is not substantiated. These gaps significantly undermine the efficacy of the models in assessing the vulnerability of individuals, communities, and urban society. The objectives of this study are twofold. First, we aim to model and, most importantly, validate influenza-like illness (ILI) symptoms at the individual scale based on four sets of transmission-driving factors pertinent to home-work space, service space, ambient environment, and demographics. The effort is supported by an ensemble approach. For the second objective, we investigate the effectiveness of the factor sets through an impact analysis. The validation accuracy reaches 73.2-95.1%. The validation substantiates the effectiveness of factors pertinent to urban spaces and unveils the underlying mechanism that connects urban spaces and population health. With more fine-scaled health data becoming available, the findings of this study may see increasing value in informing policies that improve population health and urban livability.
doi_str_mv 10.3390/ijerph20105865
format Article
fullrecord <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10218228</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A752360671</galeid><sourcerecordid>A752360671</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3565-ec91f3787999079dc240d1cbfdffef936aab1da2f2c86478d6e926eed1be3bc83</originalsourceid><addsrcrecordid>eNptks9PFTEQxxujEQSvHk0TL1wW-2O3uz0RQgBfQuJBnxybbjvl9dnXPttdEvjr7YuIYMgcvpPOZ77NtIPQB0qOOZfks19D3q4YoaQbRPcK7VMhSNMKQl8_yffQu1LWhPChFfIt2uM947KTdB8tr1cJX8JU8LQCfBHmE7yI1t96O-vg78HiH1WtnnyKOLladGGGeK-b4H8CXoQQoRTsI17mUUf8basNlEP0xulQ4P2DHqDlxfn3sy_N1dfLxdnpVWN4J7oGjKSO90MvpSS9tIa1xFIzOuscOMmF1iO1mjlmBtH2gxUgmQCwdAQ-moEfoJM_vtt53IA1EKesg9pmv9H5TiXt1fNK9Ct1k24VJYwOjO0cjh4ccvo1Q5nUxhcDIegIaS6KDYxUtutIRT_9h67TnGOdr1JUtq3oufhH3egAykeX6sVmZ6pO-45xQURPK3X8AlXDwsabFMH5ev5Sg8mplAzucUhK1G4T1PNNqA0fnz7NI_736_lvon6vAA</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2819446736</pqid></control><display><type>article</type><title>Who Gets the Flu? Individualized Validation of Influenza-like Illness in Urban Spaces</title><source>MEDLINE</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central Open Access</source><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Zhong, Shiran ; Ma, Fenglong ; Gao, Jing ; Bian, Ling</creator><creatorcontrib>Zhong, Shiran ; Ma, Fenglong ; Gao, Jing ; Bian, Ling</creatorcontrib><description>Urban dwellers are exposed to communicable diseases, such as influenza, in various urban spaces. Current disease models are able to predict health outcomes at the individual scale but are mostly validated at coarse scales due to the lack of fine-scaled ground truth data. Further, a large number of transmission-driving factors have been considered in these models. Because of the lack of individual-scaled validations, the effectiveness of factors at their intended scale is not substantiated. These gaps significantly undermine the efficacy of the models in assessing the vulnerability of individuals, communities, and urban society. The objectives of this study are twofold. First, we aim to model and, most importantly, validate influenza-like illness (ILI) symptoms at the individual scale based on four sets of transmission-driving factors pertinent to home-work space, service space, ambient environment, and demographics. The effort is supported by an ensemble approach. For the second objective, we investigate the effectiveness of the factor sets through an impact analysis. The validation accuracy reaches 73.2-95.1%. The validation substantiates the effectiveness of factors pertinent to urban spaces and unveils the underlying mechanism that connects urban spaces and population health. With more fine-scaled health data becoming available, the findings of this study may see increasing value in informing policies that improve population health and urban livability.</description><identifier>ISSN: 1660-4601</identifier><identifier>ISSN: 1661-7827</identifier><identifier>EISSN: 1660-4601</identifier><identifier>DOI: 10.3390/ijerph20105865</identifier><identifier>PMID: 37239591</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Decision trees ; Demographics ; Disease transmission ; Epidemics ; Health aspects ; Health risk assessment ; Health risks ; Humans ; Illnesses ; Impact analysis ; Infections ; Influenza ; Influenza, Human - epidemiology ; Medical research ; Medicine, Experimental ; Neural networks ; Outdoor air quality ; Pandemics ; Policy ; Population ; Population Health ; Prognosis ; Public spaces ; Regression analysis ; Signs and symptoms ; Support vector machines ; Urban areas ; Urban health ; Virus Diseases</subject><ispartof>International journal of environmental research and public health, 2023-05, Vol.20 (10), p.5865</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 by the authors. 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3565-ec91f3787999079dc240d1cbfdffef936aab1da2f2c86478d6e926eed1be3bc83</cites><orcidid>0000-0002-4999-0303 ; 0000-0001-7616-0797</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10218228/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10218228/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,725,778,782,883,27907,27908,53774,53776</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37239591$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhong, Shiran</creatorcontrib><creatorcontrib>Ma, Fenglong</creatorcontrib><creatorcontrib>Gao, Jing</creatorcontrib><creatorcontrib>Bian, Ling</creatorcontrib><title>Who Gets the Flu? Individualized Validation of Influenza-like Illness in Urban Spaces</title><title>International journal of environmental research and public health</title><addtitle>Int J Environ Res Public Health</addtitle><description>Urban dwellers are exposed to communicable diseases, such as influenza, in various urban spaces. Current disease models are able to predict health outcomes at the individual scale but are mostly validated at coarse scales due to the lack of fine-scaled ground truth data. Further, a large number of transmission-driving factors have been considered in these models. Because of the lack of individual-scaled validations, the effectiveness of factors at their intended scale is not substantiated. These gaps significantly undermine the efficacy of the models in assessing the vulnerability of individuals, communities, and urban society. The objectives of this study are twofold. First, we aim to model and, most importantly, validate influenza-like illness (ILI) symptoms at the individual scale based on four sets of transmission-driving factors pertinent to home-work space, service space, ambient environment, and demographics. The effort is supported by an ensemble approach. For the second objective, we investigate the effectiveness of the factor sets through an impact analysis. The validation accuracy reaches 73.2-95.1%. The validation substantiates the effectiveness of factors pertinent to urban spaces and unveils the underlying mechanism that connects urban spaces and population health. With more fine-scaled health data becoming available, the findings of this study may see increasing value in informing policies that improve population health and urban livability.</description><subject>Decision trees</subject><subject>Demographics</subject><subject>Disease transmission</subject><subject>Epidemics</subject><subject>Health aspects</subject><subject>Health risk assessment</subject><subject>Health risks</subject><subject>Humans</subject><subject>Illnesses</subject><subject>Impact analysis</subject><subject>Infections</subject><subject>Influenza</subject><subject>Influenza, Human - epidemiology</subject><subject>Medical research</subject><subject>Medicine, Experimental</subject><subject>Neural networks</subject><subject>Outdoor air quality</subject><subject>Pandemics</subject><subject>Policy</subject><subject>Population</subject><subject>Population Health</subject><subject>Prognosis</subject><subject>Public spaces</subject><subject>Regression analysis</subject><subject>Signs and symptoms</subject><subject>Support vector machines</subject><subject>Urban areas</subject><subject>Urban health</subject><subject>Virus Diseases</subject><issn>1660-4601</issn><issn>1661-7827</issn><issn>1660-4601</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNptks9PFTEQxxujEQSvHk0TL1wW-2O3uz0RQgBfQuJBnxybbjvl9dnXPttdEvjr7YuIYMgcvpPOZ77NtIPQB0qOOZfks19D3q4YoaQbRPcK7VMhSNMKQl8_yffQu1LWhPChFfIt2uM947KTdB8tr1cJX8JU8LQCfBHmE7yI1t96O-vg78HiH1WtnnyKOLladGGGeK-b4H8CXoQQoRTsI17mUUf8basNlEP0xulQ4P2DHqDlxfn3sy_N1dfLxdnpVWN4J7oGjKSO90MvpSS9tIa1xFIzOuscOMmF1iO1mjlmBtH2gxUgmQCwdAQ-moEfoJM_vtt53IA1EKesg9pmv9H5TiXt1fNK9Ct1k24VJYwOjO0cjh4ccvo1Q5nUxhcDIegIaS6KDYxUtutIRT_9h67TnGOdr1JUtq3oufhH3egAykeX6sVmZ6pO-45xQURPK3X8AlXDwsabFMH5ev5Sg8mplAzucUhK1G4T1PNNqA0fnz7NI_736_lvon6vAA</recordid><startdate>20230518</startdate><enddate>20230518</enddate><creator>Zhong, Shiran</creator><creator>Ma, Fenglong</creator><creator>Gao, Jing</creator><creator>Bian, Ling</creator><general>MDPI AG</general><general>MDPI</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-4999-0303</orcidid><orcidid>https://orcid.org/0000-0001-7616-0797</orcidid></search><sort><creationdate>20230518</creationdate><title>Who Gets the Flu? Individualized Validation of Influenza-like Illness in Urban Spaces</title><author>Zhong, Shiran ; Ma, Fenglong ; Gao, Jing ; Bian, Ling</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3565-ec91f3787999079dc240d1cbfdffef936aab1da2f2c86478d6e926eed1be3bc83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Decision trees</topic><topic>Demographics</topic><topic>Disease transmission</topic><topic>Epidemics</topic><topic>Health aspects</topic><topic>Health risk assessment</topic><topic>Health risks</topic><topic>Humans</topic><topic>Illnesses</topic><topic>Impact analysis</topic><topic>Infections</topic><topic>Influenza</topic><topic>Influenza, Human - epidemiology</topic><topic>Medical research</topic><topic>Medicine, Experimental</topic><topic>Neural networks</topic><topic>Outdoor air quality</topic><topic>Pandemics</topic><topic>Policy</topic><topic>Population</topic><topic>Population Health</topic><topic>Prognosis</topic><topic>Public spaces</topic><topic>Regression analysis</topic><topic>Signs and symptoms</topic><topic>Support vector machines</topic><topic>Urban areas</topic><topic>Urban health</topic><topic>Virus Diseases</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhong, Shiran</creatorcontrib><creatorcontrib>Ma, Fenglong</creatorcontrib><creatorcontrib>Gao, Jing</creatorcontrib><creatorcontrib>Bian, Ling</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>International journal of environmental research and public health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhong, Shiran</au><au>Ma, Fenglong</au><au>Gao, Jing</au><au>Bian, Ling</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Who Gets the Flu? Individualized Validation of Influenza-like Illness in Urban Spaces</atitle><jtitle>International journal of environmental research and public health</jtitle><addtitle>Int J Environ Res Public Health</addtitle><date>2023-05-18</date><risdate>2023</risdate><volume>20</volume><issue>10</issue><spage>5865</spage><pages>5865-</pages><issn>1660-4601</issn><issn>1661-7827</issn><eissn>1660-4601</eissn><abstract>Urban dwellers are exposed to communicable diseases, such as influenza, in various urban spaces. Current disease models are able to predict health outcomes at the individual scale but are mostly validated at coarse scales due to the lack of fine-scaled ground truth data. Further, a large number of transmission-driving factors have been considered in these models. Because of the lack of individual-scaled validations, the effectiveness of factors at their intended scale is not substantiated. These gaps significantly undermine the efficacy of the models in assessing the vulnerability of individuals, communities, and urban society. The objectives of this study are twofold. First, we aim to model and, most importantly, validate influenza-like illness (ILI) symptoms at the individual scale based on four sets of transmission-driving factors pertinent to home-work space, service space, ambient environment, and demographics. The effort is supported by an ensemble approach. For the second objective, we investigate the effectiveness of the factor sets through an impact analysis. The validation accuracy reaches 73.2-95.1%. The validation substantiates the effectiveness of factors pertinent to urban spaces and unveils the underlying mechanism that connects urban spaces and population health. With more fine-scaled health data becoming available, the findings of this study may see increasing value in informing policies that improve population health and urban livability.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>37239591</pmid><doi>10.3390/ijerph20105865</doi><orcidid>https://orcid.org/0000-0002-4999-0303</orcidid><orcidid>https://orcid.org/0000-0001-7616-0797</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1660-4601
ispartof International journal of environmental research and public health, 2023-05, Vol.20 (10), p.5865
issn 1660-4601
1661-7827
1660-4601
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10218228
source MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central Open Access; MDPI - Multidisciplinary Digital Publishing Institute; PubMed Central; Free Full-Text Journals in Chemistry
subjects Decision trees
Demographics
Disease transmission
Epidemics
Health aspects
Health risk assessment
Health risks
Humans
Illnesses
Impact analysis
Infections
Influenza
Influenza, Human - epidemiology
Medical research
Medicine, Experimental
Neural networks
Outdoor air quality
Pandemics
Policy
Population
Population Health
Prognosis
Public spaces
Regression analysis
Signs and symptoms
Support vector machines
Urban areas
Urban health
Virus Diseases
title Who Gets the Flu? Individualized Validation of Influenza-like Illness in Urban Spaces
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-16T09%3A48%3A34IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Who%20Gets%20the%20Flu?%20Individualized%20Validation%20of%20Influenza-like%20Illness%20in%20Urban%20Spaces&rft.jtitle=International%20journal%20of%20environmental%20research%20and%20public%20health&rft.au=Zhong,%20Shiran&rft.date=2023-05-18&rft.volume=20&rft.issue=10&rft.spage=5865&rft.pages=5865-&rft.issn=1660-4601&rft.eissn=1660-4601&rft_id=info:doi/10.3390/ijerph20105865&rft_dat=%3Cgale_pubme%3EA752360671%3C/gale_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2819446736&rft_id=info:pmid/37239591&rft_galeid=A752360671&rfr_iscdi=true