New technologies in predicting, preventing and controlling emerging infectious diseases
Identifieur interne : 000049 ( Pmc/Curation ); précédent : 000048; suivant : 000050New technologies in predicting, preventing and controlling emerging infectious diseases
Auteurs : Eirini Christaki [Grèce, États-Unis]Source :
- Virulence [ 2150-5594 ] ; 2015.
Abstract
Surveillance of emerging infectious diseases is vital for the early identification of public health threats. Emergence of novel infections is linked to human factors such as population density, travel and trade and ecological factors like climate change and agricultural practices. A wealth of new technologies is becoming increasingly available for the rapid molecular identification of pathogens but also for the more accurate monitoring of infectious disease activity. Web-based surveillance tools and epidemic intelligence methods, used by all major public health institutions, are intended to facilitate risk assessment and timely outbreak detection. In this review, we present new methods for regional and global infectious disease surveillance and advances in epidemic modeling aimed to predict and prevent future infectious diseases threats.
Url:
DOI: 10.1080/21505594.2015.1040975
PubMed: 26068569
PubMed Central: 4720248
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<affiliation wicri:level="1"><nlm:aff id="af0002"><institution>Infectious Diseases Division; Alpert School of Medicine of Brown University</institution>
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<front><div type="abstract" xml:lang="en"><p>Surveillance of emerging infectious diseases is vital for the early identification of public health threats. Emergence of novel infections is linked to human factors such as population density, travel and trade and ecological factors like climate change and agricultural practices. A wealth of new technologies is becoming increasingly available for the rapid molecular identification of pathogens but also for the more accurate monitoring of infectious disease activity. Web-based surveillance tools and epidemic intelligence methods, used by all major public health institutions, are intended to facilitate risk assessment and timely outbreak detection. In this review, we present new methods for regional and global infectious disease surveillance and advances in epidemic modeling aimed to predict and prevent future infectious diseases threats.</p>
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<front><journal-meta><journal-id journal-id-type="nlm-ta">Virulence</journal-id>
<journal-id journal-id-type="iso-abbrev">Virulence</journal-id>
<journal-id journal-id-type="pmc">KVIR</journal-id>
<journal-title-group><journal-title>Virulence</journal-title>
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<issn pub-type="ppub">2150-5594</issn>
<issn pub-type="epub">2150-5608</issn>
<publisher><publisher-name>Taylor & Francis</publisher-name>
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<article-id pub-id-type="publisher-id">1040975</article-id>
<article-id pub-id-type="doi">10.1080/21505594.2015.1040975</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Review</subject>
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<title-group><article-title>New technologies in predicting, preventing and controlling emerging infectious diseases</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Christaki</surname>
<given-names>Eirini</given-names>
</name>
<xref ref-type="aff" rid="af0001"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="af0002"><sup>2</sup>
</xref>
<xref ref-type="corresp" rid="an0001"><sup>*</sup>
</xref>
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<aff id="af0001"><label>1</label>
<institution>Hellenic Center for Disease Control and Prevention; First Department of Internal Medicine; AHEPA University Hospital</institution>
; Thessaloniki,<country>Greece</country>
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<aff id="af0002"><label>2</label>
<institution>Infectious Diseases Division; Alpert School of Medicine of Brown University</institution>
; Providence, RI<country>USA</country>
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<author-notes><corresp id="an0001"><label>*</label>
Correspondence to: Eirini Christaki; Email: <email xlink:href="eirini.christaki@gmail.com">eirini.christaki@gmail.com</email>
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<pub-date pub-type="collection"><season>Aug-Sep</season>
<year>2015</year>
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<pub-date pub-type="epub"><day>11</day>
<month>6</month>
<year>2015</year>
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<volume>6</volume>
<issue>6</issue>
<fpage seq="8">558</fpage>
<lpage>565</lpage>
<history><date date-type="received"><day>3</day>
<month>9</month>
<year>2014</year>
</date>
<date date-type="rev-recd"><day>3</day>
<month>4</month>
<year>2015</year>
</date>
<date date-type="accepted"><day>7</day>
<month>4</month>
<year>2015</year>
</date>
</history>
<permissions><copyright-statement>© 2015 Taylor & Francis Group, LLC</copyright-statement>
<copyright-year>2015</copyright-year>
<copyright-holder>Taylor & Francis Group, LLC</copyright-holder>
</permissions>
<self-uri content-type="pdf" xlink:href="kvir-06-06-1040975.pdf"></self-uri>
<abstract><p>Surveillance of emerging infectious diseases is vital for the early identification of public health threats. Emergence of novel infections is linked to human factors such as population density, travel and trade and ecological factors like climate change and agricultural practices. A wealth of new technologies is becoming increasingly available for the rapid molecular identification of pathogens but also for the more accurate monitoring of infectious disease activity. Web-based surveillance tools and epidemic intelligence methods, used by all major public health institutions, are intended to facilitate risk assessment and timely outbreak detection. In this review, we present new methods for regional and global infectious disease surveillance and advances in epidemic modeling aimed to predict and prevent future infectious diseases threats.</p>
</abstract>
<kwd-group kwd-group-type="author"><title>Keywords</title>
<kwd>Emerging infectious diseases</kwd>
<kwd>event-based surveillance</kwd>
<kwd>epidemic modeling</kwd>
<kwd>outbreak</kwd>
<kwd>surveillance</kwd>
</kwd-group>
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