A Bayesian Inferential Approach to Quantify the Transmission Intensity of Disease Outbreak
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Auteurs : Adiveppa S. Kadi [Inde] ; Shivakumari R. Avaradi [Inde]Source :
- Computational and Mathematical Methods in Medicine [ 1748-670X ] ; 2015.
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DOI: 10.1155/2015/256319
PubMed: 25784956
PubMed Central: 4345055
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A Bayesian Inferential Approach to Quantify the Transmission Intensity of Disease Outbreak</title><author><name sortKey="Kadi, Adiveppa S" sort="Kadi, Adiveppa S" uniqKey="Kadi A" first="Adiveppa S." last="Kadi">Adiveppa S. Kadi</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Studies in Statistics, Karnatak University, Dharwad 580003, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Studies in Statistics, Karnatak University, Dharwad 580003</wicri:regionArea><wicri:noRegion>Dharwad 580003</wicri:noRegion></affiliation></author><author><name sortKey="Avaradi, Shivakumari R" sort="Avaradi, Shivakumari R" uniqKey="Avaradi S" first="Shivakumari R." last="Avaradi">Shivakumari R. Avaradi</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Studies in Statistics, Karnatak University, Dharwad 580003, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Studies in Statistics, Karnatak University, Dharwad 580003</wicri:regionArea><wicri:noRegion>Dharwad 580003</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">25784956</idno><idno type="pmc">4345055</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4345055</idno><idno type="RBID">PMC:4345055</idno><idno type="doi">10.1155/2015/256319</idno><date when="2015">2015</date><idno type="wicri:Area/Pmc/Corpus">000943</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000943</idno><idno type="wicri:Area/Pmc/Curation">000943</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000943</idno><idno type="wicri:Area/Pmc/Checkpoint">000433</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">000433</idno><idno type="wicri:Area/Ncbi/Merge">000B46</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">A Bayesian Inferential Approach to Quantify the Transmission Intensity of Disease Outbreak</title><author><name sortKey="Kadi, Adiveppa S" sort="Kadi, Adiveppa S" uniqKey="Kadi A" first="Adiveppa S." last="Kadi">Adiveppa S. Kadi</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Studies in Statistics, Karnatak University, Dharwad 580003, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Studies in Statistics, Karnatak University, Dharwad 580003</wicri:regionArea><wicri:noRegion>Dharwad 580003</wicri:noRegion></affiliation></author><author><name sortKey="Avaradi, Shivakumari R" sort="Avaradi, Shivakumari R" uniqKey="Avaradi S" first="Shivakumari R." last="Avaradi">Shivakumari R. Avaradi</name><affiliation wicri:level="1"><nlm:aff id="I1">Department of Studies in Statistics, Karnatak University, Dharwad 580003, India</nlm:aff><country xml:lang="fr">Inde</country><wicri:regionArea>Department of Studies in Statistics, Karnatak University, Dharwad 580003</wicri:regionArea><wicri:noRegion>Dharwad 580003</wicri:noRegion></affiliation></author></analytic><series><title level="j">Computational and Mathematical Methods in Medicine</title><idno type="ISSN">1748-670X</idno><idno type="eISSN">1748-6718</idno><imprint><date when="2015">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><italic>Background</italic>. Emergence of infectious diseases like influenza pandemic (H1N1) 2009 has become great concern, which posed new challenges to the health authorities worldwide. To control these diseases various studies have been developed in the field of mathematical modelling, which is useful tool for understanding the epidemiological dynamics and their dependence on social mixing patterns. <italic>Method</italic>. We have used Bayesian approach to quantify the disease outbreak through key epidemiological parameter basic reproduction number (<italic>R</italic><sub>0</sub>), using effective contacts, defined as sum of the product of incidence cases and probability of generation time distribution. We have estimated <italic>R</italic><sub>0</sub> from daily case incidence data for pandemic influenza A/H1N1 2009 in India, for the initial phase. <italic>Result</italic>. The estimated <italic>R</italic><sub>0</sub> with 95% credible interval is consistent with several other studies on the same strain. Through sensitivity analysis our study indicates that infectiousness affects the estimate of <italic>R</italic><sub>0</sub>. <italic>Conclusion</italic>. Basic reproduction number <italic>R</italic><sub>0</sub> provides the useful information to the public health system to do some effort in controlling the disease by using mitigation strategies like vaccination, quarantine, and so forth.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Diekmann, O" uniqKey="Diekmann O">O. Diekmann</name></author><author><name sortKey="Heesterbeek, J A P" uniqKey="Heesterbeek J">J. A. P. Heesterbeek</name></author><author><name sortKey="Metz, J A J" uniqKey="Metz J">J. A. J. Metz</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Anderson, R M" uniqKey="Anderson R">R. M. Anderson</name></author><author><name sortKey="May, R M" uniqKey="May R">R. M. May</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Dietz, K" uniqKey="Dietz K">K. Dietz</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Gani, S R" uniqKey="Gani S">S. R. Gani</name></author><author><name sortKey="Ali, S T" uniqKey="Ali S">S. T. Ali</name></author><author><name sortKey="Kadi, A S" uniqKey="Kadi A">A. S. Kadi</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Heffernan, J M" uniqKey="Heffernan J">J. M. Heffernan</name></author><author><name sortKey="Wahl, L M" uniqKey="Wahl L">L. M. Wahl</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kermack, W O" uniqKey="Kermack W">W. O. Kermack</name></author><author><name sortKey="Mckendrick, A G" uniqKey="Mckendrick A">A. G. McKendrick</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Feller, W" uniqKey="Feller W">W. Feller</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Levin, B R" uniqKey="Levin B">B. R. Levin</name></author><author><name sortKey="Bull, J J" uniqKey="Bull J">J. J. Bull</name></author><author><name sortKey="Stewart, F M" uniqKey="Stewart F">F. M. Stewart</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Heesterbeek, J A P" uniqKey="Heesterbeek J">J. A. P. Heesterbeek</name></author><author><name sortKey="Dietz, K" uniqKey="Dietz K">K. Dietz</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Metz, J A J" uniqKey="Metz J">J. A. J. Metz</name></author><author><name sortKey="Diekmann, O" uniqKey="Diekmann O">O. Diekmann</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wallinga, J" uniqKey="Wallinga J">J. Wallinga</name></author><author><name sortKey="Lipsitch, M" uniqKey="Lipsitch M">M. Lipsitch</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Chowell, G" uniqKey="Chowell G">G. Chowell</name></author><author><name sortKey="Nishiura, H" uniqKey="Nishiura H">H. Nishiura</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Svensson, A" uniqKey="Svensson A">A. Svensson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wallinga, J" uniqKey="Wallinga J">J. Wallinga</name></author><author><name sortKey="Teunis, P" uniqKey="Teunis P">P. Teunis</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Haydon, D T" uniqKey="Haydon D">D. T. Haydon</name></author><author><name sortKey="Chase Topping, M" uniqKey="Chase Topping M">M. Chase-Topping</name></author><author><name sortKey="Shaw, D J" uniqKey="Shaw D">D. J. Shaw</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Nishiura, H" uniqKey="Nishiura H">H. Nishiura</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Robert, C P" uniqKey="Robert C">C. P. Robert</name></author><author><name sortKey="Casella, G" uniqKey="Casella G">G. Casella</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Anscombe, F J" uniqKey="Anscombe F">F. J. Anscombe</name></author><author><name sortKey="Bayes, T" uniqKey="Bayes T">T. Bayes</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Anderson, R M" uniqKey="Anderson R">R. M. Anderson</name></author><author><name sortKey="Fraser, C" uniqKey="Fraser C">C. Fraser</name></author><author><name sortKey="Ghani, A C" uniqKey="Ghani A">A. C. Ghani</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="White, L F" uniqKey="White L">L. F. White</name></author><author><name sortKey="Pagano, M" uniqKey="Pagano M">M. Pagano</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Garske, T" uniqKey="Garske T">T. Garske</name></author><author><name sortKey="Clarke, P" uniqKey="Clarke P">P. Clarke</name></author><author><name sortKey="Ghani, A C" uniqKey="Ghani A">A. C. Ghani</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Cowling, B J" uniqKey="Cowling B">B. J. Cowling</name></author><author><name sortKey="Fang, V J" uniqKey="Fang V">V. J. Fang</name></author><author><name sortKey="Riley, S" uniqKey="Riley S">S. Riley</name></author><author><name sortKey="Peiris, J S M" uniqKey="Peiris J">J. S. M. Peiris</name></author><author><name sortKey="Leung, G M" uniqKey="Leung G">G. M. Leung</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Cauchemez, S" uniqKey="Cauchemez S">S. Cauchemez</name></author><author><name sortKey="Donnelly, C A" uniqKey="Donnelly C">C. A. Donnelly</name></author><author><name sortKey="Reed, C" uniqKey="Reed C">C. Reed</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ferguson, N M" uniqKey="Ferguson N">N. M. Ferguson</name></author><author><name sortKey="Cummings, D A T" uniqKey="Cummings D">D. A. T. Cummings</name></author><author><name sortKey="Cauchemez, S" uniqKey="Cauchemez S">S. Cauchemez</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Samsuzzoha, M D" uniqKey="Samsuzzoha M">M. D. Samsuzzoha</name></author><author><name sortKey="Singh, M" uniqKey="Singh M">M. Singh</name></author><author><name sortKey="Lucy, D" uniqKey="Lucy D">D. Lucy</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Yang, Y" uniqKey="Yang Y">Y. Yang</name></author><author><name sortKey="Sugimoto, J D" uniqKey="Sugimoto J">J. D. Sugimoto</name></author><author><name sortKey="Elizabeth Halloran, M" uniqKey="Elizabeth Halloran M">M. Elizabeth Halloran</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ghani, A" uniqKey="Ghani A">A. Ghani</name></author><author><name sortKey="Baguelin, M" uniqKey="Baguelin M">M. Baguelin</name></author><author><name sortKey="Griffin, J" uniqKey="Griffin J">J. Griffin</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Pourbohloul, B" uniqKey="Pourbohloul B">B. Pourbohloul</name></author><author><name sortKey="Ahued, A" uniqKey="Ahued A">A. Ahued</name></author><author><name sortKey="Davoudi, B" uniqKey="Davoudi B">B. Davoudi</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Baguelin, M" uniqKey="Baguelin M">M. Baguelin</name></author><author><name sortKey="Hoek, A J V" uniqKey="Hoek A">A. J. V. Hoek</name></author><author><name sortKey="Jit, M" uniqKey="Jit M">M. Jit</name></author><author><name sortKey="Flasche, S" uniqKey="Flasche S">S. Flasche</name></author><author><name sortKey="White, P J" uniqKey="White P">P. J. White</name></author><author><name sortKey="Edmunds, W J" uniqKey="Edmunds W">W. J. Edmunds</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wu, J T" uniqKey="Wu J">J. T. Wu</name></author><author><name sortKey="Ma, E S K" uniqKey="Ma E">E. S. K. Ma</name></author><author><name sortKey="Lee, C K" uniqKey="Lee C">C. K. Lee</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Birrell, P J" uniqKey="Birrell P">P. J. Birrell</name></author><author><name sortKey="Ketsetzis, G" uniqKey="Ketsetzis G">G. Ketsetzis</name></author><author><name sortKey="Gay, N J" uniqKey="Gay N">N. J. Gay</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Nishiura, H" uniqKey="Nishiura H">H. Nishiura</name></author></analytic></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Comput Math Methods Med</journal-id><journal-id journal-id-type="iso-abbrev">Comput Math Methods Med</journal-id><journal-id journal-id-type="publisher-id">CMMM</journal-id><journal-title-group><journal-title>Computational and Mathematical Methods in Medicine</journal-title></journal-title-group><issn pub-type="ppub">1748-670X</issn><issn pub-type="epub">1748-6718</issn><publisher><publisher-name>Hindawi Publishing Corporation</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">25784956</article-id><article-id pub-id-type="pmc">4345055</article-id><article-id pub-id-type="doi">10.1155/2015/256319</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title>A Bayesian Inferential Approach to Quantify the Transmission Intensity of Disease Outbreak</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Kadi</surname><given-names>Adiveppa S.</given-names></name><xref ref-type="aff" rid="I1"></xref></contrib><contrib contrib-type="author"><name><surname>Avaradi</surname><given-names>Shivakumari R.</given-names></name><xref ref-type="aff" rid="I1"></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib></contrib-group><aff id="I1">Department of Studies in Statistics, Karnatak University, Dharwad 580003, India</aff><author-notes><corresp id="cor1">*Shivakumari R. Avaradi: <email>shiv.avaradi@gmail.com</email></corresp><fn fn-type="other"><p>Academic Editor: Xiaojun Yao</p></fn></author-notes><pub-date pub-type="ppub"><year>2015</year></pub-date><pub-date pub-type="epub"><day>15</day><month>2</month><year>2015</year></pub-date><volume>2015</volume><elocation-id>256319</elocation-id><history><date date-type="received"><day>30</day><month>10</month><year>2014</year></date><date date-type="rev-recd"><day>16</day><month>1</month><year>2015</year></date><date date-type="accepted"><day>20</day><month>1</month><year>2015</year></date></history><permissions><copyright-statement>Copyright © 2015 A. S. Kadi and S. R. Avaradi.</copyright-statement><copyright-year>2015</copyright-year><license xlink:href="https://creativecommons.org/licenses/by/3.0/"><license-p>This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions><abstract><p><italic>Background</italic>. Emergence of infectious diseases like influenza pandemic (H1N1) 2009 has become great concern, which posed new challenges to the health authorities worldwide. To control these diseases various studies have been developed in the field of mathematical modelling, which is useful tool for understanding the epidemiological dynamics and their dependence on social mixing patterns. <italic>Method</italic>. We have used Bayesian approach to quantify the disease outbreak through key epidemiological parameter basic reproduction number (<italic>R</italic><sub>0</sub>), using effective contacts, defined as sum of the product of incidence cases and probability of generation time distribution. We have estimated <italic>R</italic><sub>0</sub> from daily case incidence data for pandemic influenza A/H1N1 2009 in India, for the initial phase. <italic>Result</italic>. The estimated <italic>R</italic><sub>0</sub> with 95% credible interval is consistent with several other studies on the same strain. Through sensitivity analysis our study indicates that infectiousness affects the estimate of <italic>R</italic><sub>0</sub>. <italic>Conclusion</italic>. Basic reproduction number <italic>R</italic><sub>0</sub> provides the useful information to the public health system to do some effort in controlling the disease by using mitigation strategies like vaccination, quarantine, and so forth.</p></abstract></article-meta></front><floats-group><fig id="fig1" orientation="portrait" position="float"><label>Figure 1</label><caption><p>Daily reported cases of influenza A/H1N1 2009 of India.</p></caption><graphic xlink:href="CMMM2015-256319.001"></graphic></fig><fig id="fig2" orientation="portrait" position="float"><label>Figure 2</label><caption><p>Transmission tree for contact patterns.</p></caption><graphic xlink:href="CMMM2015-256319.002"></graphic></fig><fig id="fig3" orientation="portrait" position="float"><label>Figure 3</label><caption><p>Histogram of posterior distribution of <italic>R</italic><sub>0</sub> by using different values of prior choices for beta distribution.</p></caption><graphic xlink:href="CMMM2015-256319.003"></graphic></fig><table-wrap id="tab1" orientation="portrait" position="float"><label>Table 1</label><caption><p>Sensitivity analysis of basic reproduction number R<sub>0</sub> is depending on generation time distribution as Weibull distribution for time since infection <italic>s</italic> for 7 days as well as 10 days.</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="1" colspan="1">Prior distribution <break></break>for <italic>s</italic> = 7 days</th><th align="center" rowspan="1" colspan="1">Basic reproduction number R<sub>0</sub>
<break></break>(with 95% CrI)</th><th align="center" rowspan="1" colspan="1">Prior distribution<break></break>for <italic>s</italic> = 10 days</th><th align="center" rowspan="1" colspan="1">Basic reproduction number R<sub>0</sub>
<break></break>(with 95% CrI)</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Beta(1,1)</td><td align="center" rowspan="1" colspan="1"><bold>1.2548</bold>
<break></break>(1.2223, 1.2923)</td><td align="center" rowspan="1" colspan="1">Bata(2,1)</td><td align="center" rowspan="1" colspan="1"><bold>1.3392</bold>
<break></break>(1.3128, 1.3938)</td></tr><tr><td align="center" colspan="4" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Beta(4,2)</td><td align="center" rowspan="1" colspan="1"><bold>1.2543</bold>
<break></break>(1.2250, 1.2850)</td><td align="center" rowspan="1" colspan="1">Beta(3.46,5.2)</td><td align="center" rowspan="1" colspan="1"><bold>1.3323</bold>
<break></break>(1.2962, 1.3762)</td></tr><tr><td align="center" colspan="4" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Beta(3.46,5.2)</td><td align="center" rowspan="1" colspan="1"><bold>1.2578</bold>
<break></break>(1.2309, 1.2909)</td><td align="center" rowspan="1" colspan="1">Beta(4.4,2.2)</td><td align="center" rowspan="1" colspan="1"><bold>1.3296</bold>
<break></break>(1.2895, 1.3695)</td></tr><tr><td align="center" colspan="4" rowspan="1"><hr></hr></td></tr><tr><td align="left" rowspan="1" colspan="1">Beta(1.75,3.5)</td><td align="center" rowspan="1" colspan="1"><bold>1.2569</bold>
<break></break>(1.2279, 1.2879)</td><td align="center" rowspan="1" colspan="1">Beta(7,3.5)</td><td align="center" rowspan="1" colspan="1"><bold>1.3303</bold>
<break></break>(1.2969, 1.3669)</td></tr></tbody></table></table-wrap></floats-group></pmc><affiliations><list><country><li>Inde</li></country></list><tree><country name="Inde"><noRegion><name sortKey="Kadi, Adiveppa S" sort="Kadi, Adiveppa S" uniqKey="Kadi A" first="Adiveppa S." last="Kadi">Adiveppa S. Kadi</name></noRegion><name sortKey="Avaradi, Shivakumari R" sort="Avaradi, Shivakumari R" uniqKey="Avaradi S" first="Shivakumari R." last="Avaradi">Shivakumari R. Avaradi</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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