[Dynamic basic reproduction number based evaluation for current prevention and control of COVID-19 outbreak in China].
Identifieur interne : 000087 ( PubMed/Checkpoint ); précédent : 000086; suivant : 000088[Dynamic basic reproduction number based evaluation for current prevention and control of COVID-19 outbreak in China].
Auteurs : L L Huang [République populaire de Chine] ; S P Shen [République populaire de Chine] ; P. Yu [République populaire de Chine] ; Y Y Wei [République populaire de Chine]Source :
- Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi [ 0254-6450 ] ; 2020.
Abstract
Objective: To evaluate the current status of the prevention and control of coronavirus disease (COVID-19) outbreak in China, establish a predictive model to evaluate the effects of the current prevention and control strategies, and provide scientific information for decision- making departments. Methods: Based on the epidemic data of COVID-19 openly accessed from national health authorities, we estimated the dynamic basic reproduction number R(0)(t) to evaluate the effects of the current COVID-19 prevention and control strategies in all the provinces (municipalities and autonomous regions) as well as in Wuhan and the changes in infectivity of COVID-19 over time. Results: For the stability of the results, 24 provinces (municipality) with more than 100 confirmed COVID-19 cases were included in the analysis. At the beginning of the outbreak, the R(0)(t) showed unstable trend with big variances. As the strengthening of the prevention and control strategies, R(0)(t) began to show a downward trend in late January, and became stable in February. By the time of data analysis, 18 provinces (municipality) (75%) had the R(0)(t)s less than 1. The results could be used for the decision making to free population floating conditionally. Conclusions: Dynamic R(0)(t) is useful in the evaluation of the change in infectivity of COVID-19, the prevention and control strategies for the COVID-19 outbreak have shown preliminary effects, if continues, it is expected to control the COVID-19 outbreak in China in near future.
DOI: 10.3760/cma.j.cn112338-20200209-00080
PubMed: 32113197
Affiliations:
Links toward previous steps (curation, corpus...)
Links to Exploration step
pubmed:32113197Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">[Dynamic basic reproduction number based evaluation for current prevention and control of COVID-19 outbreak in China].</title><author><name sortKey="Huang, L L" sort="Huang, L L" uniqKey="Huang L" first="L L" last="Huang">L L Huang</name><affiliation wicri:level="1"><nlm:affiliation>Department of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai 200032, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai 200032</wicri:regionArea><wicri:noRegion>Shanghai 200032</wicri:noRegion></affiliation></author><author><name sortKey="Shen, S P" sort="Shen, S P" uniqKey="Shen S" first="S P" last="Shen">S P Shen</name><affiliation wicri:level="1"><nlm:affiliation>Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166</wicri:regionArea><wicri:noRegion>Nanjing 211166</wicri:noRegion></affiliation></author><author><name sortKey="Yu, P" sort="Yu, P" uniqKey="Yu P" first="P" last="Yu">P. Yu</name><affiliation wicri:level="1"><nlm:affiliation>Jingan District Center for Disease Control and Prevention, Shanghai 200072, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Jingan District Center for Disease Control and Prevention, Shanghai 200072</wicri:regionArea><wicri:noRegion>Shanghai 200072</wicri:noRegion></affiliation></author><author><name sortKey="Wei, Y Y" sort="Wei, Y Y" uniqKey="Wei Y" first="Y Y" last="Wei">Y Y Wei</name><affiliation wicri:level="1"><nlm:affiliation>Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166</wicri:regionArea><wicri:noRegion>Nanjing 211166</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:32113197</idno><idno type="pmid">32113197</idno><idno type="doi">10.3760/cma.j.cn112338-20200209-00080</idno><idno type="wicri:Area/PubMed/Corpus">000941</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000941</idno><idno type="wicri:Area/PubMed/Curation">000941</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000941</idno><idno type="wicri:Area/PubMed/Checkpoint">000087</idno><idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">000087</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">[Dynamic basic reproduction number based evaluation for current prevention and control of COVID-19 outbreak in China].</title><author><name sortKey="Huang, L L" sort="Huang, L L" uniqKey="Huang L" first="L L" last="Huang">L L Huang</name><affiliation wicri:level="1"><nlm:affiliation>Department of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai 200032, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai 200032</wicri:regionArea><wicri:noRegion>Shanghai 200032</wicri:noRegion></affiliation></author><author><name sortKey="Shen, S P" sort="Shen, S P" uniqKey="Shen S" first="S P" last="Shen">S P Shen</name><affiliation wicri:level="1"><nlm:affiliation>Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166</wicri:regionArea><wicri:noRegion>Nanjing 211166</wicri:noRegion></affiliation></author><author><name sortKey="Yu, P" sort="Yu, P" uniqKey="Yu P" first="P" last="Yu">P. Yu</name><affiliation wicri:level="1"><nlm:affiliation>Jingan District Center for Disease Control and Prevention, Shanghai 200072, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Jingan District Center for Disease Control and Prevention, Shanghai 200072</wicri:regionArea><wicri:noRegion>Shanghai 200072</wicri:noRegion></affiliation></author><author><name sortKey="Wei, Y Y" sort="Wei, Y Y" uniqKey="Wei Y" first="Y Y" last="Wei">Y Y Wei</name><affiliation wicri:level="1"><nlm:affiliation>Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166</wicri:regionArea><wicri:noRegion>Nanjing 211166</wicri:noRegion></affiliation></author></analytic><series><title level="j">Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi</title><idno type="ISSN">0254-6450</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><b>Objective:</b> To evaluate the current status of the prevention and control of coronavirus disease (COVID-19) outbreak in China, establish a predictive model to evaluate the effects of the current prevention and control strategies, and provide scientific information for decision- making departments. <b>Methods:</b> Based on the epidemic data of COVID-19 openly accessed from national health authorities, we estimated the dynamic basic reproduction number <i>R(0)</i>(t) to evaluate the effects of the current COVID-19 prevention and control strategies in all the provinces (municipalities and autonomous regions) as well as in Wuhan and the changes in infectivity of COVID-19 over time. <b>Results:</b> For the stability of the results, 24 provinces (municipality) with more than 100 confirmed COVID-19 cases were included in the analysis. At the beginning of the outbreak, the <i>R(0)</i>(t) showed unstable trend with big variances. As the strengthening of the prevention and control strategies, <i>R(0)</i>(t) began to show a downward trend in late January, and became stable in February. By the time of data analysis, 18 provinces (municipality) (75%) had the <i>R(0)</i>(t)s less than 1. The results could be used for the decision making to free population floating conditionally. <b>Conclusions:</b> Dynamic <i>R(0)</i>(t) is useful in the evaluation of the change in infectivity of COVID-19, the prevention and control strategies for the COVID-19 outbreak have shown preliminary effects, if continues, it is expected to control the COVID-19 outbreak in China in near future.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32113197</PMID><DateRevised><Year>2020</Year><Month>03</Month><Day>01</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Print">0254-6450</ISSN><JournalIssue CitedMedium="Print"><Volume>41</Volume><Issue>4</Issue><PubDate><Year>2020</Year><Month>Mar</Month><Day>01</Day></PubDate></JournalIssue><Title>Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi</Title><ISOAbbreviation>Zhonghua Liu Xing Bing Xue Za Zhi</ISOAbbreviation></Journal><ArticleTitle>[Dynamic basic reproduction number based evaluation for current prevention and control of COVID-19 outbreak in China].</ArticleTitle><Pagination><MedlinePgn>466-469</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.3760/cma.j.cn112338-20200209-00080</ELocationID><Abstract><AbstractText><b>Objective:</b> To evaluate the current status of the prevention and control of coronavirus disease (COVID-19) outbreak in China, establish a predictive model to evaluate the effects of the current prevention and control strategies, and provide scientific information for decision- making departments. <b>Methods:</b> Based on the epidemic data of COVID-19 openly accessed from national health authorities, we estimated the dynamic basic reproduction number <i>R(0)</i>(t) to evaluate the effects of the current COVID-19 prevention and control strategies in all the provinces (municipalities and autonomous regions) as well as in Wuhan and the changes in infectivity of COVID-19 over time. <b>Results:</b> For the stability of the results, 24 provinces (municipality) with more than 100 confirmed COVID-19 cases were included in the analysis. At the beginning of the outbreak, the <i>R(0)</i>(t) showed unstable trend with big variances. As the strengthening of the prevention and control strategies, <i>R(0)</i>(t) began to show a downward trend in late January, and became stable in February. By the time of data analysis, 18 provinces (municipality) (75%) had the <i>R(0)</i>(t)s less than 1. The results could be used for the decision making to free population floating conditionally. <b>Conclusions:</b> Dynamic <i>R(0)</i>(t) is useful in the evaluation of the change in infectivity of COVID-19, the prevention and control strategies for the COVID-19 outbreak have shown preliminary effects, if continues, it is expected to control the COVID-19 outbreak in China in near future.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Huang</LastName><ForeName>L L</ForeName><Initials>LL</Initials><AffiliationInfo><Affiliation>Department of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai 200032, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Shen</LastName><ForeName>S P</ForeName><Initials>SP</Initials><AffiliationInfo><Affiliation>Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Yu</LastName><ForeName>P</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>Jingan District Center for Disease Control and Prevention, Shanghai 200072, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wei</LastName><ForeName>Y Y</ForeName><Initials>YY</Initials><AffiliationInfo><Affiliation>Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.</Affiliation></AffiliationInfo></Author></AuthorList><Language>chi</Language><GrantList CompleteYN="Y"><Grant><GrantID>81903407</GrantID><Agency>National Natural Science Foundation for Youth Scientists</Agency><Country></Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D004740">English Abstract</PublicationType><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>03</Month><Day>01</Day></ArticleDate></Article><MedlineJournalInfo><Country>China</Country><MedlineTA>Zhonghua Liu Xing Bing Xue Za Zhi</MedlineTA><NlmUniqueID>8208604</NlmUniqueID><ISSNLinking>0254-6450</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><OtherAbstract Type="Publisher" Language="chi"><AbstractText><b>目的：</b> 对全国各省份的新型冠状病毒肺炎（COVID-19）疫情防控现状进行分析，建立预测模型预估现有防控措施预期成效，为决策部门提供科学信息。 <b>方法：</b> 基于COVID-19疫情网络公开数据，估计全国、各省份以及武汉市不同时间基本再生数（<i>R(0)</i>）的动态变化<i>R(0)</i>（<i>t</i>），以评估在现有防控措施下，COVID-19传染速率随时间变化的趋势，预估现有防控措施的预期成效。 <b>结果：</b> 从结果稳定性考虑，选择累积确诊病例数>100例的地区进行分析，共24个省份纳入分析。在疫情初期，全国整体<i>R(0)</i>（<i>t</i>）不稳定，数值较大，误差也较大。随着防控措施的进一步加强，<i>R(0)</i>（<i>t</i>）普遍在1月下旬开始呈现下降趋势，2月始下降趋势稳定。截至数据分析日，纳入分析的24个省份中已有18个省份（75%）<i>R(0)</i>（<i>t</i>）降到1以下。这为有条件地开放人员流动提供了信息。 <b>结论：</b> 动态<i>R(0)</i>（<i>t</i>）有助于动态评估COVID-19传染速率变化情况，本次疫情防控措施已初显成效，如能继续保持，全国疫情有望短期内得到全面控制。.</AbstractText></OtherAbstract><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Coronavirus disease</Keyword><Keyword MajorTopicYN="N">Dynamic bosic reproduction number</Keyword><Keyword MajorTopicYN="N">Statistical prediction</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>3</Month><Day>2</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>3</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>3</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32113197</ArticleId><ArticleId IdType="doi">10.3760/cma.j.cn112338-20200209-00080</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>République populaire de Chine</li></country></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Huang, L L" sort="Huang, L L" uniqKey="Huang L" first="L L" last="Huang">L L Huang</name></noRegion><name sortKey="Shen, S P" sort="Shen, S P" uniqKey="Shen S" first="S P" last="Shen">S P Shen</name><name sortKey="Wei, Y Y" sort="Wei, Y Y" uniqKey="Wei Y" first="Y Y" last="Wei">Y Y Wei</name><name sortKey="Yu, P" sort="Yu, P" uniqKey="Yu P" first="P" last="Yu">P. Yu</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Sante/explor/CovidV2/Data/PubMed/Checkpoint
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000087 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/PubMed/Checkpoint/biblio.hfd -nk 000087 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Sante
|area= CovidV2
|flux= PubMed
|étape= Checkpoint
|type= RBID
|clé= pubmed:32113197
|texte= [Dynamic basic reproduction number based evaluation for current prevention and control of COVID-19 outbreak in China].
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/PubMed/Checkpoint/RBID.i -Sk "pubmed:32113197" \
| HfdSelect -Kh $EXPLOR_AREA/Data/PubMed/Checkpoint/biblio.hfd \
| NlmPubMed2Wicri -a CovidV2
| This area was generated with Dilib version V0.6.33. |  |