Epidemic Models of Contact Tracing: Systematic Review of Transmission Studies of Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome.
Identifieur interne : 000579 ( PubMed/Checkpoint ); précédent : 000578; suivant : 000580Epidemic Models of Contact Tracing: Systematic Review of Transmission Studies of Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome.
Auteurs : Kin On Kwok [République populaire de Chine] ; Arthur Tang [Corée du Sud] ; Vivian W I. Wei [République populaire de Chine] ; Woo Hyun Park [Corée du Sud] ; Eng Kiong Yeoh [République populaire de Chine] ; Steven Riley [Royaume-Uni]Source :
- Computational and structural biotechnology journal [ 2001-0370 ] ; 2019.
Abstract
The emergence and reemergence of coronavirus epidemics sparked renewed concerns from global epidemiology researchers and public health administrators. Mathematical models that represented how contact tracing and follow-up may control Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) transmissions were developed for evaluating different infection control interventions, estimating likely number of infections as well as facilitating understanding of their likely epidemiology. We reviewed mathematical models for contact tracing and follow-up control measures of SARS and MERS transmission. Model characteristics, epidemiological parameters and intervention parameters used in the mathematical models from seven studies were summarized. A major concern identified in future epidemics is whether public health administrators can collect all the required data for building epidemiological models in a short period of time during the early phase of an outbreak. Also, currently available models do not explicitly model constrained resources. We urge for closed-loop communication between public health administrators and modelling researchers to come up with guidelines to delineate the collection of the required data in the midst of an outbreak and the inclusion of additional logistical details in future similar models.
DOI: 10.1016/j.csbj.2019.01.003
PubMed: 30809323
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Wei</name><affiliation wicri:level="4"><nlm:affiliation>The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region</wicri:regionArea><orgName type="university">Université chinoise de Hong Kong</orgName><placeName><settlement type="city">Sha Tin</settlement></placeName></affiliation></author><author><name sortKey="Park, Woo Hyun" sort="Park, Woo Hyun" uniqKey="Park W" first="Woo Hyun" last="Park">Woo Hyun Park</name><affiliation wicri:level="1"><nlm:affiliation>Department of Electrical and Computer Engineering, Sungkyunkwan University, South Korea.</nlm:affiliation><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Electrical and Computer Engineering, Sungkyunkwan University</wicri:regionArea><wicri:noRegion>Sungkyunkwan University</wicri:noRegion></affiliation></author><author><name sortKey="Yeoh, Eng Kiong" sort="Yeoh, Eng Kiong" uniqKey="Yeoh E" first="Eng Kiong" last="Yeoh">Eng Kiong Yeoh</name><affiliation wicri:level="4"><nlm:affiliation>The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region</wicri:regionArea><orgName type="university">Université chinoise de Hong Kong</orgName><placeName><settlement type="city">Sha Tin</settlement></placeName></affiliation></author><author><name sortKey="Riley, Steven" sort="Riley, Steven" uniqKey="Riley S" first="Steven" last="Riley">Steven Riley</name><affiliation wicri:level="1"><nlm:affiliation>MRC Centre for Outbreak Analysis and Modelling, Department for Infectious Disease Epidemiology, Imperial College London, United Kingdom.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>MRC Centre for Outbreak Analysis and Modelling, Department for Infectious Disease Epidemiology, Imperial College London</wicri:regionArea><wicri:noRegion>Imperial College London</wicri:noRegion></affiliation></author></analytic><series><title level="j">Computational and structural biotechnology journal</title><idno type="ISSN">2001-0370</idno><imprint><date when="2019" type="published">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The emergence and reemergence of coronavirus epidemics sparked renewed concerns from global epidemiology researchers and public health administrators. Mathematical models that represented how contact tracing and follow-up may control Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) transmissions were developed for evaluating different infection control interventions, estimating likely number of infections as well as facilitating understanding of their likely epidemiology. We reviewed mathematical models for contact tracing and follow-up control measures of SARS and MERS transmission. Model characteristics, epidemiological parameters and intervention parameters used in the mathematical models from seven studies were summarized. A major concern identified in future epidemics is whether public health administrators can collect all the required data for building epidemiological models in a short period of time during the early phase of an outbreak. Also, currently available models do not explicitly model constrained resources. We urge for closed-loop communication between public health administrators and modelling researchers to come up with guidelines to delineate the collection of the required data in the midst of an outbreak and the inclusion of additional logistical details in future similar models.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">30809323</PMID><DateRevised><Year>2020</Year><Month>03</Month><Day>10</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">2001-0370</ISSN><JournalIssue CitedMedium="Print"><Volume>17</Volume><PubDate><Year>2019</Year></PubDate></JournalIssue><Title>Computational and structural biotechnology journal</Title><ISOAbbreviation>Comput Struct Biotechnol J</ISOAbbreviation></Journal><ArticleTitle>Epidemic Models of Contact Tracing: Systematic Review of Transmission Studies of Severe Acute Respiratory Syndrome and Middle East Respiratory Syndrome.</ArticleTitle><Pagination><MedlinePgn>186-194</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.csbj.2019.01.003</ELocationID><Abstract><AbstractText>The emergence and reemergence of coronavirus epidemics sparked renewed concerns from global epidemiology researchers and public health administrators. Mathematical models that represented how contact tracing and follow-up may control Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) transmissions were developed for evaluating different infection control interventions, estimating likely number of infections as well as facilitating understanding of their likely epidemiology. We reviewed mathematical models for contact tracing and follow-up control measures of SARS and MERS transmission. Model characteristics, epidemiological parameters and intervention parameters used in the mathematical models from seven studies were summarized. A major concern identified in future epidemics is whether public health administrators can collect all the required data for building epidemiological models in a short period of time during the early phase of an outbreak. Also, currently available models do not explicitly model constrained resources. We urge for closed-loop communication between public health administrators and modelling researchers to come up with guidelines to delineate the collection of the required data in the midst of an outbreak and the inclusion of additional logistical details in future similar models.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Kwok</LastName><ForeName>Kin On</ForeName><Initials>KO</Initials><AffiliationInfo><Affiliation>The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Stanley Ho Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Shenzhen Research Institute of The Chinese University of Hong Kong, Shenzhen, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tang</LastName><ForeName>Arthur</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Department of Software, Sungkyunkwan University, South Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wei</LastName><ForeName>Vivian W I</ForeName><Initials>VWI</Initials><AffiliationInfo><Affiliation>The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Park</LastName><ForeName>Woo Hyun</ForeName><Initials>WH</Initials><AffiliationInfo><Affiliation>Department of Electrical and Computer Engineering, Sungkyunkwan University, South Korea.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Yeoh</LastName><ForeName>Eng Kiong</ForeName><Initials>EK</Initials><AffiliationInfo><Affiliation>The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Riley</LastName><ForeName>Steven</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>MRC Centre for Outbreak Analysis and Modelling, Department for Infectious Disease Epidemiology, Imperial College London, United Kingdom.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>MR/R015600/1</GrantID><Acronym>MRC_</Acronym><Agency>Medical Research Council</Agency><Country>United Kingdom</Country></Grant><Grant><GrantID>U01 GM110721</GrantID><Acronym>GM</Acronym><Agency>NIGMS NIH HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D016454">Review</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2019</Year><Month>01</Month><Day>26</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Comput Struct Biotechnol J</MedlineTA><NlmUniqueID>101585369</NlmUniqueID><ISSNLinking>2001-0370</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Co-V, Coronavirus</Keyword><Keyword MajorTopicYN="N">Contact Tracing</Keyword><Keyword MajorTopicYN="N">Coronavirus Epidemics</Keyword><Keyword MajorTopicYN="N">MERS</Keyword><Keyword MajorTopicYN="N">MERS, Middle East Respiratory Syndrome</Keyword><Keyword MajorTopicYN="N">R0, Basic reproduction number</Keyword><Keyword MajorTopicYN="N">SARS</Keyword><Keyword MajorTopicYN="N">SARS, Severe Acute Respiratory Syndrome</Keyword><Keyword MajorTopicYN="N">SEIR, Susceptible Exposed Infectious Recovered</Keyword><Keyword MajorTopicYN="N">Transmission Modelling</Keyword><Keyword MajorTopicYN="N">WHO, World Health 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Kwok</name></noRegion><name sortKey="Wei, Vivian W I" sort="Wei, Vivian W I" uniqKey="Wei V" first="Vivian W I" last="Wei">Vivian W I. Wei</name><name sortKey="Yeoh, Eng Kiong" sort="Yeoh, Eng Kiong" uniqKey="Yeoh E" first="Eng Kiong" last="Yeoh">Eng Kiong Yeoh</name></country><country name="Corée du Sud"><noRegion><name sortKey="Tang, Arthur" sort="Tang, Arthur" uniqKey="Tang A" first="Arthur" last="Tang">Arthur Tang</name></noRegion><name sortKey="Park, Woo Hyun" sort="Park, Woo Hyun" uniqKey="Park W" first="Woo Hyun" last="Park">Woo Hyun Park</name></country><country name="Royaume-Uni"><noRegion><name sortKey="Riley, Steven" sort="Riley, Steven" uniqKey="Riley S" first="Steven" last="Riley">Steven Riley</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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