Detecting Differential Transmissibilities That Affect the Size of Self-Limited Outbreaks
Identifieur interne : 001102 ( Pmc/Checkpoint ); précédent : 001101; suivant : 001103Detecting Differential Transmissibilities That Affect the Size of Self-Limited Outbreaks
Auteurs : Seth Blumberg [États-Unis] ; Sebastian Funk [Royaume-Uni, États-Unis] ; Juliet R. C. Pulliam [États-Unis]Source :
- PLoS Pathogens [ 1553-7366 ] ; 2014.
Abstract
Our ability to respond appropriately to infectious diseases is enhanced by identifying differences in the potential for transmitting infection between individuals. Here, we identify epidemiological traits of self-limited infections (i.e. infections with an effective reproduction number satisfying
Url:
DOI: 10.1371/journal.ppat.1004452
PubMed: 25356657
PubMed Central: 4214794
Affiliations:
- Royaume-Uni, États-Unis
- Angleterre, Californie, Floride, Grand Londres, Maryland, New Jersey
- Londres, Princeton (New Jersey)
- Université de Princeton
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Proctor Foundation, University of California San Francisco, San Francisco, California, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Francis I. Proctor Foundation, University of California San Francisco, San Francisco, California</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation><affiliation wicri:level="2"><nlm:aff id="aff2"><addr-line>Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Fogarty International Center, National Institutes of Health, Bethesda, Maryland</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Funk, Sebastian" sort="Funk, Sebastian" uniqKey="Funk S" first="Sebastian" last="Funk">Sebastian Funk</name><affiliation wicri:level="3"><nlm:aff id="aff3"><addr-line>Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom</addr-line></nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London</wicri:regionArea><placeName><settlement type="city">Londres</settlement><region type="country">Angleterre</region><region type="région" nuts="1">Grand Londres</region></placeName></affiliation><affiliation wicri:level="4"><nlm:aff id="aff4"><addr-line>Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey</wicri:regionArea><placeName><region type="state">New Jersey</region><settlement type="city">Princeton (New Jersey)</settlement></placeName><orgName type="university">Université de Princeton</orgName></affiliation></author><author><name sortKey="Pulliam, Juliet R C" sort="Pulliam, Juliet R C" uniqKey="Pulliam J" first="Juliet R. C." last="Pulliam">Juliet R. C. Pulliam</name><affiliation wicri:level="2"><nlm:aff id="aff2"><addr-line>Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Fogarty International Center, National Institutes of Health, Bethesda, Maryland</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation><affiliation wicri:level="2"><nlm:aff id="aff5"><addr-line>Department of Biology, University of Florida, Gainesville, Florida, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biology, University of Florida, Gainesville, Florida</wicri:regionArea><placeName><region type="state">Floride</region></placeName></affiliation><affiliation wicri:level="2"><nlm:aff id="aff6"><addr-line>Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Emerging Pathogens Institute, University of Florida, Gainesville, Florida</wicri:regionArea><placeName><region type="state">Floride</region></placeName></affiliation></author></analytic><series><title level="j">PLoS Pathogens</title><idno type="ISSN">1553-7366</idno><idno type="eISSN">1553-7374</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Our ability to respond appropriately to infectious diseases is enhanced by identifying differences in the potential for transmitting infection between individuals. Here, we identify epidemiological traits of self-limited infections (i.e. infections with an effective reproduction number satisfying <inline-formula><inline-graphic xlink:href="ppat.1004452.e001.jpg"></inline-graphic></inline-formula>) that correlate with transmissibility. Our analysis is based on a branching process model that permits statistical comparison of both the strength and heterogeneity of transmission for two distinct types of cases. Our approach provides insight into a variety of scenarios, including the transmission of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in the Arabian peninsula, measles in North America, pre-eradication smallpox in Europe, and human monkeypox in the Democratic Republic of the Congo. When applied to chain size data for MERS-CoV transmission before 2014, our method indicates that despite an apparent trend towards improved control, there is not enough statistical evidence to indicate that <inline-formula><inline-graphic xlink:href="ppat.1004452.e002.jpg"></inline-graphic></inline-formula> has declined with time. Meanwhile, chain size data for measles in the United States and Canada reveal statistically significant geographic variation in <inline-formula><inline-graphic xlink:href="ppat.1004452.e003.jpg"></inline-graphic></inline-formula>, suggesting that the timing and coverage of national vaccination programs, as well as contact tracing procedures, may shape the size distribution of observed infection clusters. Infection source data for smallpox suggests that primary cases transmitted more than secondary cases, and provides a quantitative assessment of the effectiveness of control interventions. Human monkeypox, on the other hand, does not show evidence of differential transmission between animals in contact with humans, primary cases, or secondary cases, which assuages the concern that social mixing can amplify transmission by secondary cases. Lastly, we evaluate surveillance requirements for detecting a change in the human-to-human transmission of monkeypox since the cessation of cross-protective smallpox vaccination. Our studies lay the foundation for future investigations regarding how infection source, vaccination status or other putative transmissibility traits may affect self-limited transmission.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="De Serres, G" uniqKey="De Serres G">G De Serres</name></author><author><name sortKey="Gay, Nj" uniqKey="Gay N">NJ Gay</name></author><author><name sortKey="Farrington, Cp" uniqKey="Farrington C">CP Farrington</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Farrington, Cp" uniqKey="Farrington C">CP Farrington</name></author><author><name sortKey="Kanaan, Mn" uniqKey="Kanaan M">MN Kanaan</name></author><author><name sortKey="Gay, Nj" uniqKey="Gay N">NJ Gay</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Jansen, Vaa" uniqKey="Jansen V">Vaa Jansen</name></author><author><name sortKey="Stollenwerk, N" uniqKey="Stollenwerk N">N 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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS Pathog</journal-id><journal-id journal-id-type="iso-abbrev">PLoS Pathog</journal-id><journal-id journal-id-type="publisher-id">plos</journal-id><journal-id journal-id-type="pmc">plospath</journal-id><journal-title-group><journal-title>PLoS Pathogens</journal-title></journal-title-group><issn pub-type="ppub">1553-7366</issn><issn pub-type="epub">1553-7374</issn><publisher><publisher-name>Public Library of Science</publisher-name><publisher-loc>San Francisco, USA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">25356657</article-id><article-id pub-id-type="pmc">4214794</article-id><article-id pub-id-type="publisher-id">PPATHOGENS-D-14-00229</article-id><article-id pub-id-type="doi">10.1371/journal.ppat.1004452</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biology and Life Sciences</subject><subj-group><subject>Computational Biology</subject><subj-group><subject>Population Modeling</subject><subj-group><subject>Infectious Disease Modeling</subject></subj-group></subj-group></subj-group><subj-group><subject>Immunology</subject><subj-group><subject>Vaccination and Immunization</subject></subj-group></subj-group><subj-group><subject>Plant Science</subject><subj-group><subject>Plant Pathology</subject><subj-group><subject>Infectious Disease Epidemiology</subject></subj-group></subj-group></subj-group><subj-group><subject>Population Biology</subject><subj-group><subject>Population Dynamics</subject></subj-group></subj-group><subj-group><subject>Theoretical Biology</subject></subj-group><subj-group><subject>Veterinary Science</subject><subj-group><subject>Veterinary Diseases</subject><subj-group><subject>Zoonoses</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Medicine and Health Sciences</subject><subj-group><subject>Epidemiology</subject><subj-group><subject>Disease Dynamics</subject><subject>Epidemiological Methods and Statistics</subject></subj-group></subj-group><subj-group><subject>Infectious Diseases</subject><subj-group><subject>Viral Diseases</subject><subj-group><subject>Measles</subject><subject>Smallpox</subject></subj-group></subj-group><subj-group><subject>Travel-Associated Diseases</subject></subj-group></subj-group><subj-group><subject>Public and Occupational Health</subject><subj-group><subject>Disease Ecology</subject><subject>Global Health</subject><subject>Preventive Medicine</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Physical Sciences</subject><subj-group><subject>Mathematics</subject><subj-group><subject>Statistics (Mathematics)</subject><subj-group><subject>Biostatistics</subject></subj-group></subj-group></subj-group></subj-group></article-categories><title-group><article-title>Detecting Differential Transmissibilities That Affect the Size of Self-Limited Outbreaks</article-title><alt-title alt-title-type="running-head">Detecting Differential Transmissibilities of Self-Limited Outbreaks</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Blumberg</surname><given-names>Seth</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author"><name><surname>Funk</surname><given-names>Sebastian</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author"><name><surname>Pulliam</surname><given-names>Juliet R. C.</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="aff" rid="aff5"><sup>5</sup></xref><xref ref-type="aff" rid="aff6"><sup>6</sup></xref></contrib></contrib-group><aff id="aff1"><label>1</label><addr-line>Francis I. Proctor Foundation, University of California San Francisco, San Francisco, California, United States of America</addr-line></aff><aff id="aff2"><label>2</label><addr-line>Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></aff><aff id="aff3"><label>3</label><addr-line>Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom</addr-line></aff><aff id="aff4"><label>4</label><addr-line>Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America</addr-line></aff><aff id="aff5"><label>5</label><addr-line>Department of Biology, University of Florida, Gainesville, Florida, United States of America</addr-line></aff><aff id="aff6"><label>6</label><addr-line>Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Wilke</surname><given-names>Claus O.</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1"><addr-line>University of Texas at Austin, United States of America</addr-line></aff><author-notes><corresp id="cor1">* E-mail: <email>seth.blumberg@ucsf.edu</email></corresp><fn fn-type="COI-statement"><p>The authors have declared that no competing interests exist.</p></fn><fn fn-type="con"><p>Conceived and designed the experiments: SB SF JRCP. Performed the experiments: SB SF. Analyzed the data: SB. Wrote the paper: SB SF JRCP.</p></fn></author-notes><pub-date pub-type="collection"><month>10</month><year>2014</year></pub-date><pub-date pub-type="epub"><day>30</day><month>10</month><year>2014</year></pub-date><volume>10</volume><issue>10</issue><elocation-id>e1004452</elocation-id><history><date date-type="received"><day>26</day><month>1</month><year>2014</year></date><date date-type="accepted"><day>4</day><month>9</month><year>2014</year></date></history><permissions><copyright-year>2014</copyright-year><license xlink:href="https://creativecommons.org/publicdomain/zero/1.0/"><license-p>This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.</license-p></license></permissions><abstract><p>Our ability to respond appropriately to infectious diseases is enhanced by identifying differences in the potential for transmitting infection between individuals. Here, we identify epidemiological traits of self-limited infections (i.e. infections with an effective reproduction number satisfying <inline-formula><inline-graphic xlink:href="ppat.1004452.e001.jpg"></inline-graphic></inline-formula>) that correlate with transmissibility. Our analysis is based on a branching process model that permits statistical comparison of both the strength and heterogeneity of transmission for two distinct types of cases. Our approach provides insight into a variety of scenarios, including the transmission of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in the Arabian peninsula, measles in North America, pre-eradication smallpox in Europe, and human monkeypox in the Democratic Republic of the Congo. When applied to chain size data for MERS-CoV transmission before 2014, our method indicates that despite an apparent trend towards improved control, there is not enough statistical evidence to indicate that <inline-formula><inline-graphic xlink:href="ppat.1004452.e002.jpg"></inline-graphic></inline-formula> has declined with time. Meanwhile, chain size data for measles in the United States and Canada reveal statistically significant geographic variation in <inline-formula><inline-graphic xlink:href="ppat.1004452.e003.jpg"></inline-graphic></inline-formula>, suggesting that the timing and coverage of national vaccination programs, as well as contact tracing procedures, may shape the size distribution of observed infection clusters. Infection source data for smallpox suggests that primary cases transmitted more than secondary cases, and provides a quantitative assessment of the effectiveness of control interventions. Human monkeypox, on the other hand, does not show evidence of differential transmission between animals in contact with humans, primary cases, or secondary cases, which assuages the concern that social mixing can amplify transmission by secondary cases. Lastly, we evaluate surveillance requirements for detecting a change in the human-to-human transmission of monkeypox since the cessation of cross-protective smallpox vaccination. Our studies lay the foundation for future investigations regarding how infection source, vaccination status or other putative transmissibility traits may affect self-limited transmission.</p></abstract><abstract abstract-type="summary"><title>Author Summary</title><p>The goal of this paper is to identify epidemiological factors that correlate with either an increased or decreased risk of transmitting a particular disease. We are particularly interested in identifying such factors for diseases that are <italic>self-limited</italic> (meaning that infections tend to occur in isolated clusters), because targeted control of these diseases can facilitate public health goals for minimizing the risk of disease emergence or promoting disease elimination. For example, we show that there is a significant difference in the transmission of measles between the United States and Canada. In contrast, we find that an observed decrease in the transmission of Middle East respiratory syndrome coronavirus during the latter half of 2013 cannot be ascertained with sufficient confidence. We then quantify the degree to which control was effective in eradicating smallpox in Europe. We also consider how the transmission of monkeypox in humans depends on whether the infection source is an animal or a human. Finally, we demonstrate how our approach can be used by surveillance programs to detect changes in transmission that may occur over time.</p></abstract><funding-group><funding-statement>This work was supported by the National Institute of Health MIDAS program (Modeling Infectious Disease Agent Study) [grant number NIH NIGMS 1-U01-GM087728 to SB]; the RAPIDD program of the Science and Technology Directorate, Department of Homeland Security (Research and Policy for Infectious Disease Dynamics) [to SB and JRCP]; the National Institute of Health, Fogarty International Center [to SB and JP]; a Royal Society International Exchanges grant [to SF and SB]; a Medical Research Council Career Development Award in Biostatistics [to SF]; and the John S. McDonnell Foundation [to SF]. This work was also assisted through participation in the ‘modeling wildlife and virus zoonoses’ investigative workshop (November 2010) at the National Institute for Mathematical and Biological Synthesis, sponsored by the National Science Foundation, the U.S. Department of Homeland Security, and the U.S. Department of Agriculture through NSF Awards EF-0832858 and DBI-1300426, with additional support from The University of Tennessee, Knoxville [SB, SF and JRCP]; the ‘modeling and analysis of options for controlling persistent infectious diseases’ workshop (February, 2011) at the Banff International Research Station [SB and SF]; and the ‘infectious disease dynamics’ workshop (August 2013) at Isaac Newton Institute for Mathematical Sciences [SF and JRCP]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement></funding-group><counts><page-count count="14"></page-count></counts></article-meta></front></pmc><affiliations><list><country><li>Royaume-Uni</li><li>États-Unis</li></country><region><li>Angleterre</li><li>Californie</li><li>Floride</li><li>Grand Londres</li><li>Maryland</li><li>New Jersey</li></region><settlement><li>Londres</li><li>Princeton (New Jersey)</li></settlement><orgName><li>Université de Princeton</li></orgName></list><tree><country name="États-Unis"><region name="Californie"><name sortKey="Blumberg, Seth" sort="Blumberg, Seth" uniqKey="Blumberg S" first="Seth" last="Blumberg">Seth Blumberg</name></region><name sortKey="Blumberg, Seth" sort="Blumberg, Seth" uniqKey="Blumberg S" first="Seth" last="Blumberg">Seth Blumberg</name><name sortKey="Funk, Sebastian" sort="Funk, Sebastian" uniqKey="Funk S" first="Sebastian" last="Funk">Sebastian Funk</name><name sortKey="Pulliam, Juliet R C" sort="Pulliam, Juliet R C" uniqKey="Pulliam J" first="Juliet R. C." last="Pulliam">Juliet R. C. Pulliam</name><name sortKey="Pulliam, Juliet R C" sort="Pulliam, Juliet R C" uniqKey="Pulliam J" first="Juliet R. C." last="Pulliam">Juliet R. C. Pulliam</name><name sortKey="Pulliam, Juliet R C" sort="Pulliam, Juliet R C" uniqKey="Pulliam J" first="Juliet R. C." last="Pulliam">Juliet R. C. Pulliam</name></country><country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Funk, Sebastian" sort="Funk, Sebastian" uniqKey="Funk S" first="Sebastian" last="Funk">Sebastian Funk</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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