Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases
Identifieur interne : 000910 ( Pmc/Curation ); précédent : 000909; suivant : 000911Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases
Auteurs : Sung-Mok Jung ; Andrei R. Akhmetzhanov ; Katsuma Hayashi ; Natalie M. Linton ; Yichi Yang ; Baoyin Yuan ; Tetsuro Kobayashi ; Ryo Kinoshita ; Hiroshi Nishiura [Japon]Source :
- Journal of Clinical Medicine [ 2077-0383 ] ; 2020.
Abstract
The exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number—the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% confidence interval [CI]: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.
Url:
DOI: 10.3390/jcm9020523
PubMed: 32075152
PubMed Central: 7074479
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases</title><author><name sortKey="Jung, Sung Mok" sort="Jung, Sung Mok" uniqKey="Jung S" first="Sung-Mok" last="Jung">Sung-Mok Jung</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Akhmetzhanov, Andrei R" sort="Akhmetzhanov, Andrei R" uniqKey="Akhmetzhanov A" first="Andrei R." last="Akhmetzhanov">Andrei R. Akhmetzhanov</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Hayashi, Katsuma" sort="Hayashi, Katsuma" uniqKey="Hayashi K" first="Katsuma" last="Hayashi">Katsuma Hayashi</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Linton, Natalie M" sort="Linton, Natalie M" uniqKey="Linton N" first="Natalie M." last="Linton">Natalie M. Linton</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Yang, Yichi" sort="Yang, Yichi" uniqKey="Yang Y" first="Yichi" last="Yang">Yichi Yang</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Yuan, Baoyin" sort="Yuan, Baoyin" uniqKey="Yuan B" first="Baoyin" last="Yuan">Baoyin Yuan</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Kobayashi, Tetsuro" sort="Kobayashi, Tetsuro" uniqKey="Kobayashi T" first="Tetsuro" last="Kobayashi">Tetsuro Kobayashi</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Kinoshita, Ryo" sort="Kinoshita, Ryo" uniqKey="Kinoshita R" first="Ryo" last="Kinoshita">Ryo Kinoshita</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Nishiura, Hiroshi" sort="Nishiura, Hiroshi" uniqKey="Nishiura H" first="Hiroshi" last="Nishiura">Hiroshi Nishiura</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation><affiliation wicri:level="1"><nlm:aff id="af2-jcm-09-00523">Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama 332-0012, Japan</nlm:aff><country xml:lang="fr">Japon</country><wicri:regionArea>Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama 332-0012</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">32075152</idno><idno type="pmc">7074479</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7074479</idno><idno type="RBID">PMC:7074479</idno><idno type="doi">10.3390/jcm9020523</idno><date when="2020">2020</date><idno type="wicri:Area/Pmc/Corpus">000910</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000910</idno><idno type="wicri:Area/Pmc/Curation">000910</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000910</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases</title><author><name sortKey="Jung, Sung Mok" sort="Jung, Sung Mok" uniqKey="Jung S" first="Sung-Mok" last="Jung">Sung-Mok Jung</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Akhmetzhanov, Andrei R" sort="Akhmetzhanov, Andrei R" uniqKey="Akhmetzhanov A" first="Andrei R." last="Akhmetzhanov">Andrei R. Akhmetzhanov</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Hayashi, Katsuma" sort="Hayashi, Katsuma" uniqKey="Hayashi K" first="Katsuma" last="Hayashi">Katsuma Hayashi</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Linton, Natalie M" sort="Linton, Natalie M" uniqKey="Linton N" first="Natalie M." last="Linton">Natalie M. Linton</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Yang, Yichi" sort="Yang, Yichi" uniqKey="Yang Y" first="Yichi" last="Yang">Yichi Yang</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Yuan, Baoyin" sort="Yuan, Baoyin" uniqKey="Yuan B" first="Baoyin" last="Yuan">Baoyin Yuan</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Kobayashi, Tetsuro" sort="Kobayashi, Tetsuro" uniqKey="Kobayashi T" first="Tetsuro" last="Kobayashi">Tetsuro Kobayashi</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Kinoshita, Ryo" sort="Kinoshita, Ryo" uniqKey="Kinoshita R" first="Ryo" last="Kinoshita">Ryo Kinoshita</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation></author><author><name sortKey="Nishiura, Hiroshi" sort="Nishiura, Hiroshi" uniqKey="Nishiura H" first="Hiroshi" last="Nishiura">Hiroshi Nishiura</name><affiliation><nlm:aff id="af1-jcm-09-00523">Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</nlm:aff></affiliation><affiliation wicri:level="1"><nlm:aff id="af2-jcm-09-00523">Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama 332-0012, Japan</nlm:aff><country xml:lang="fr">Japon</country><wicri:regionArea>Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama 332-0012</wicri:regionArea></affiliation></author></analytic><series><title level="j">Journal of Clinical Medicine</title><idno type="eISSN">2077-0383</idno><imprint><date when="2020">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>The exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number—the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% confidence interval [CI]: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Li, Q" uniqKey="Li Q">Q. Li</name></author><author><name sortKey="Guan, X" uniqKey="Guan X">X. Guan</name></author><author><name sortKey="Wu, P" uniqKey="Wu P">P. Wu</name></author><author><name sortKey="Wang, X" uniqKey="Wang X">X. Wang</name></author><author><name sortKey="Zhou, L" uniqKey="Zhou L">L. Zhou</name></author><author><name sortKey="Tong, Y" uniqKey="Tong Y">Y. Tong</name></author><author><name sortKey="Ren, R" uniqKey="Ren R">R. 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<front><journal-meta><journal-id journal-id-type="nlm-ta">J Clin Med</journal-id><journal-id journal-id-type="iso-abbrev">J Clin Med</journal-id><journal-id journal-id-type="publisher-id">jcm</journal-id><journal-title-group><journal-title>Journal of Clinical Medicine</journal-title></journal-title-group><issn pub-type="epub">2077-0383</issn><publisher><publisher-name>MDPI</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">32075152</article-id><article-id pub-id-type="pmc">7074479</article-id><article-id pub-id-type="doi">10.3390/jcm9020523</article-id><article-id pub-id-type="publisher-id">jcm-09-00523</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases</article-title></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0002-0787-4515</contrib-id><name><surname>Jung</surname><given-names>Sung-mok</given-names></name><xref ref-type="aff" rid="af1-jcm-09-00523">1</xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0003-3269-7351</contrib-id><name><surname>Akhmetzhanov</surname><given-names>Andrei R.</given-names></name><xref ref-type="aff" rid="af1-jcm-09-00523">1</xref></contrib><contrib contrib-type="author"><name><surname>Hayashi</surname><given-names>Katsuma</given-names></name><xref ref-type="aff" rid="af1-jcm-09-00523">1</xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0002-5464-0076</contrib-id><name><surname>Linton</surname><given-names>Natalie M.</given-names></name><xref ref-type="aff" rid="af1-jcm-09-00523">1</xref></contrib><contrib contrib-type="author"><name><surname>Yang</surname><given-names>Yichi</given-names></name><xref ref-type="aff" rid="af1-jcm-09-00523">1</xref></contrib><contrib contrib-type="author"><name><surname>Yuan</surname><given-names>Baoyin</given-names></name><xref ref-type="aff" rid="af1-jcm-09-00523">1</xref></contrib><contrib contrib-type="author"><name><surname>Kobayashi</surname><given-names>Tetsuro</given-names></name><xref ref-type="aff" rid="af1-jcm-09-00523">1</xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0002-0116-4598</contrib-id><name><surname>Kinoshita</surname><given-names>Ryo</given-names></name><xref ref-type="aff" rid="af1-jcm-09-00523">1</xref></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0003-0941-8537</contrib-id><name><surname>Nishiura</surname><given-names>Hiroshi</given-names></name><xref ref-type="aff" rid="af1-jcm-09-00523">1</xref><xref ref-type="aff" rid="af2-jcm-09-00523">2</xref><xref rid="c1-jcm-09-00523" ref-type="corresp">*</xref></contrib></contrib-group><aff id="af1-jcm-09-00523"><label>1</label>Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan;<email>seductmd@med.hokudai.ac.jp</email> (S.-m.J.);<email>akhmetzhanov@gmail.com</email> (A.R.A.);<email>katsuma5miffy@gmail.com</email> (K.H.);<email>nlinton@gmail.com</email> (N.M.L.);<email>lukeyang1993@eis.hokudai.ac.jp</email> (Y.Y.);<email>baoyinyuan@gmail.com</email> (B.Y.);<email>tootsieroll2910@gmail.com</email> (T.K.);<email>kinoshitaryo@gmail.com</email> (R.K.)</aff><aff id="af2-jcm-09-00523"><label>2</label>Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama 332-0012, Japan</aff><author-notes><corresp id="c1-jcm-09-00523"><label>*</label>Correspondence: <email>nishiurah@med.hokudai.ac.jp</email>; Tel.: +81-11-706-5066</corresp></author-notes><pub-date pub-type="epub"><day>14</day><month>2</month><year>2020</year></pub-date><pub-date pub-type="collection"><month>2</month><year>2020</year></pub-date><volume>9</volume><issue>2</issue><elocation-id>523</elocation-id><history><date date-type="received"><day>29</day><month>1</month><year>2020</year></date><date date-type="accepted"><day>12</day><month>2</month><year>2020</year></date></history><permissions><copyright-statement>© 2020 by the authors.</copyright-statement><copyright-year>2020</copyright-year><license license-type="open-access"><license-p>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 (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>).</license-p></license></permissions><abstract><p>The exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number—the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% confidence interval [CI]: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.</p></abstract><kwd-group><kwd>mortality</kwd><kwd>censoring</kwd><kwd>travel</kwd><kwd>migration</kwd><kwd>importation</kwd><kwd>emerging infectious diseases</kwd></kwd-group></article-meta></front><floats-group><fig id="jcm-09-00523-f001" orientation="portrait" position="float"><label>Figure 1</label><caption><p>Estimates of the mean and standard deviation (SD) of the time from illness onset to reporting and death cases, accounting for right truncation, with novel coronavirus (COVID-19) infection in China, 2020. Inference of A and B was conducted among (<bold>A</bold>) exported cases observed in other countries and (<bold>B</bold>) deceased cases in China. (<bold>A</bold>) Frequency distribution of the time from illness onset to reporting among exported cases employing a gamma distribution with a mean of 7.1 days (95% confidence interval [CI]: 5.9, 8.4) and SD of 4.4 days (95% CI: 3.5, 5.7). (<bold>B</bold>) Frequency distribution of the time from illness onset to death with a mean of 19.9 days (95% CI: 14.9, 29.0) (shown in black) and SD of 11.4 days (95% CI: 6.5, 21.6) employing a lognormal distribution and accounting for right truncation. For reference, the estimate of the mean and its 95% credible intervals without accounting for right truncation are shown in grey. The values for distribution of time from illness onset to death are adopted from an earlier study [<xref rid="B14-jcm-09-00523" ref-type="bibr">14</xref>]. The blue bars show empirically observed data collected from governmental reports (as of 24 January 2020).</p></caption><graphic xlink:href="jcm-09-00523-g001"></graphic></fig><fig id="jcm-09-00523-f002" orientation="portrait" position="float"><label>Figure 2</label><caption><p>Cumulative incidence and the confirmed case fatality risk of the novel coronavirus (COVID-19) outbreak in China, 2020. (<bold>A</bold>,<bold>B</bold>) Observed and estimated cumulative number of cases in China by the date of report. An exponential growth curve was extrapolated using the exported case data. Scenario 1 extrapolated the exponential growth from December to first case on 8 December 2019, while Scenario 2 started the estimation of the exponential growth only from 13 January 2020. The black line and shaded area represent median and 95% credible interval of the cumulative incidence in China, respectively. The blue bars show the cumulative number of reported cases from the government of mainland China. The cumulative number of reported cases was not used for fitting, but it was shown for comparison between the cumulative number of reported and estimated cases in China. There is a decrease in the cumulative number of reported cases in early January, because only 41 cases tested positive for the novel coronavirus among the reported 59 cases on 10 January 2020. Left-top panels on both <bold>A</bold> and <bold>B</bold> show the cumulative numbers of exported cases observed in other countries and the cumulative number of deaths in China, represented by dark and light green bars, respectively. (<bold>C</bold>,<bold>D</bold>) Confirmed case fatality risk (cCFR) by the date of reporting. Each value of cCFR was estimated as the ratio of cumulative number of estimated incidence to death at time <italic>t</italic>. The points and error bars represent the median and its 95% credible interval of the cCFR. All 95% credible intervals were derived from Markov chain Monte Carlo simulations.</p></caption><graphic xlink:href="jcm-09-00523-g002"></graphic></fig><fig id="jcm-09-00523-f003" orientation="portrait" position="float"><label>Figure 3</label><caption><p>Basic reproduction number of novel coronavirus (COVID-19) infections in China, 2020. Black lines and grey shades represent the median and 95% credible intervals of the basic reproduction number. Panel <bold>A</bold> shows the result of Scenario 1, in which an exponential growth started from the assumed illness onset date of index case, while Panel <bold>B</bold> shows the result from exponential growth from the first exported case (Scenario 2). The 95% credible intervals were derived from Markov chain Monte Carlo method.</p></caption><graphic xlink:href="jcm-09-00523-g003"></graphic></fig><table-wrap id="jcm-09-00523-t001" orientation="portrait" position="float"><object-id pub-id-type="pii">jcm-09-00523-t001_Table 1</object-id><label>Table 1</label><caption><p>Exportation events and estimated incidence in China, 2020.</p></caption><table frame="hsides" rules="groups"><thead><tr><th rowspan="2" align="center" valign="middle" style="border-top:solid thin;border-bottom:solid thin" colspan="1">Importing Locations</th><th rowspan="2" align="center" valign="middle" style="border-top:solid thin;border-bottom:solid thin" colspan="1">Date of Report (2020)</th><th rowspan="2" align="center" valign="middle" style="border-top:solid thin;border-bottom:solid thin" colspan="1">Cumulative Count</th><th colspan="2" align="center" valign="middle" style="border-top:solid thin;border-bottom:solid thin" rowspan="1">Estimated Incidence in China (95% CI)</th></tr><tr><th align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Scenario 1</th><th align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Scenario 2</th></tr></thead><tbody><tr><td align="center" valign="middle" rowspan="1" colspan="1">Thailand</td><td align="center" valign="middle" rowspan="1" colspan="1">13 January</td><td align="center" valign="middle" rowspan="1" colspan="1">1</td><td align="center" valign="middle" rowspan="1" colspan="1">1828 (1397 2288)</td><td align="center" valign="middle" rowspan="1" colspan="1">1369 (1003 1782)</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Japan</td><td align="center" valign="middle" rowspan="1" colspan="1">16 January</td><td align="center" valign="middle" rowspan="1" colspan="1">2</td><td align="center" valign="middle" rowspan="1" colspan="1">2120 (1605 2672)</td><td align="center" valign="middle" rowspan="1" colspan="1">1829 (1392 2309)</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Thailand</td><td align="center" valign="middle" rowspan="1" colspan="1">17 January</td><td align="center" valign="middle" rowspan="1" colspan="1">3</td><td align="center" valign="middle" rowspan="1" colspan="1">2458 (1845 3119)</td><td align="center" valign="middle" rowspan="1" colspan="1">2444 (1894 3033)</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">South Korea</td><td align="center" valign="middle" rowspan="1" colspan="1">20 January </td><td align="center" valign="middle" rowspan="1" colspan="1">4</td><td align="center" valign="middle" rowspan="1" colspan="1">3832 (2802 4962)</td><td align="center" valign="middle" rowspan="1" colspan="1">5882 (4252 7629)</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Taiwan, United States</td><td align="center" valign="middle" rowspan="1" colspan="1">21 January </td><td align="center" valign="middle" rowspan="1" colspan="1">6</td><td align="center" valign="middle" rowspan="1" colspan="1">4443 (3220 5792)</td><td align="center" valign="middle" rowspan="1" colspan="1">7901 (5425, 10,662)</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Thailand</td><td align="center" valign="middle" rowspan="1" colspan="1">22 January </td><td align="center" valign="middle" rowspan="1" colspan="1">8</td><td align="center" valign="middle" rowspan="1" colspan="1">5151 (3700 6761)</td><td align="center" valign="middle" rowspan="1" colspan="1">10,626 (6897, 15,003)</td></tr><tr><td align="center" valign="middle" rowspan="1" colspan="1">Singapore, Vietnam</td><td align="center" valign="middle" rowspan="1" colspan="1">23 January </td><td align="center" valign="middle" rowspan="1" colspan="1">11</td><td align="center" valign="middle" rowspan="1" colspan="1">5972 (4252 7892)</td><td align="center" valign="middle" rowspan="1" colspan="1">14,308 (8661, 21,250)</td></tr><tr><td align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">Japan, Nepal, South Korea, Singapore, Thailand, United States</td><td align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">24 January </td><td align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">20</td><td align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">6924 (4885 9211)</td><td align="center" valign="middle" style="border-bottom:solid thin" rowspan="1" colspan="1">19,289 (10,901, 30,158)</td></tr></tbody></table><table-wrap-foot><fn><p>CI, confidence interval (the 95% CI was derived from the Markov chain Monte Carlo method). Scenario 1 indicates the estimated exponential growth rate with the assumed illness onset date of the first COVID-19 case (i.e., 8 December 2019), while Scenario 2 presents the estimated exponential growth rate from the date of first exportation event (i.e., 13 January 2020).</p></fn></table-wrap-foot></table-wrap></floats-group></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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