Transmission dynamics of Covid-19 in Italy, Germany and Turkey considering social distancing, testing and quarantine.
Identifieur interne : 000111 ( Main/Exploration ); précédent : 000110; suivant : 000112Transmission dynamics of Covid-19 in Italy, Germany and Turkey considering social distancing, testing and quarantine.
Auteurs : Serdar Gul [Turquie] ; Kagan Tuncay [Turquie] ; Baris Binici [Turquie] ; Beyazit Bestami Aydin [Turquie]Source :
- Journal of infection in developing countries [ 1972-2680 ] ; 2020.
Descripteurs français
- KwdFr :
- Adolescent (MeSH), Adulte (MeSH), Adulte d'âge moyen (MeSH), Allemagne (épidémiologie), Caractéristiques familiales (MeSH), Enfant (MeSH), Humains (MeSH), Infections à coronavirus (diagnostic), Infections à coronavirus (mortalité), Infections à coronavirus (transmission), Infections à coronavirus (épidémiologie), Isolement social (MeSH), Italie (épidémiologie), Jeune adulte (MeSH), Méthode de Monte Carlo (MeSH), Pandémies (MeSH), Pneumopathie virale (diagnostic), Pneumopathie virale (mortalité), Pneumopathie virale (transmission), Pneumopathie virale (épidémiologie), Quarantaine (MeSH), Répartition par âge (MeSH), Réseautage social (MeSH), Sujet âgé (MeSH), Taux de reproduction de base (MeSH), Techniques de laboratoire clinique (statistiques et données numériques), Turquie (épidémiologie).
- MESH :
- diagnostic : Infections à coronavirus, Pneumopathie virale.
- mortalité : Infections à coronavirus, Pneumopathie virale.
- statistiques et données numériques : Techniques de laboratoire clinique.
- épidémiologie : Allemagne, Infections à coronavirus, Italie, Pneumopathie virale, Turquie.
- Adolescent, Adulte, Adulte d'âge moyen, Caractéristiques familiales, Enfant, Humains, Isolement social, Jeune adulte, Méthode de Monte Carlo, Pandémies, Quarantaine, Répartition par âge, Réseautage social, Sujet âgé, Taux de reproduction de base.
- Wicri :
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Age Distribution (MeSH), Aged (MeSH), Basic Reproduction Number (MeSH), Child (MeSH), Clinical Laboratory Techniques (statistics & numerical data), Coronavirus Infections (diagnosis), Coronavirus Infections (epidemiology), Coronavirus Infections (mortality), Coronavirus Infections (transmission), Family Characteristics (MeSH), Germany (epidemiology), Humans (MeSH), Italy (epidemiology), Middle Aged (MeSH), Monte Carlo Method (MeSH), Pandemics (MeSH), Pneumonia, Viral (diagnosis), Pneumonia, Viral (epidemiology), Pneumonia, Viral (mortality), Pneumonia, Viral (transmission), Quarantine (MeSH), Social Isolation (MeSH), Social Networking (MeSH), Turkey (epidemiology), Young Adult (MeSH).
- MESH :
- geographic , epidemiology : Germany, Italy, Turkey.
- diagnosis : Coronavirus Infections, Pneumonia, Viral.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- mortality : Coronavirus Infections, Pneumonia, Viral.
- statistics & numerical data : Clinical Laboratory Techniques.
- transmission : Coronavirus Infections, Pneumonia, Viral.
- Adolescent, Adult, Age Distribution, Aged, Basic Reproduction Number, Child, Family Characteristics, Humans, Middle Aged, Monte Carlo Method, Pandemics, Quarantine, Social Isolation, Social Networking, Young Adult.
Abstract
INTRODUCTION
There are significant differences in the active cases and fatality rates of Covid-19 for different European countries.
METHODOLOGY
The present study employs Monte Carlo based transmission growth simulations for Italy, Germany and Turkey. The probabilities of transmission at home, work and social networks and the number of initial cases have been calibrated to match the basic reproduction number and the reported fatality curves. Parametric studies were conducted to observe the effect of social distancing, work closure, testing and quarantine of the family and colleagues of positively tested individuals.
RESULTS
It is observed that estimates of the number of initial cases in Italy compared to Turkey and Germany are higher. Turkey will probably experience about 30% less number of fatalities than Germany due its smaller elderly population. If social distancing and work contacts are limited to 25% of daily routines, Germany and Turkey may limit the number of fatalities to a few thousands as the reproduction number decreases to about 1.3 from 2.8. Random testing may reduce the number of fatalities by 10% upon testing least 5/1000 of the population. Quarantining of family and workmates of positively tested individuals may reduce the total number of fatalities by about 50%.
CONCLUSIONS
The fatality rate of Covid-19 is estimated to be about 1.5% based on the simulation results. This may further be reduced by limiting the number of non-family contacts to two, conducting tests more than 0.5% of the population and immediate quarantine of the contacts for positively tested individuals.
DOI: 10.3855/jidc.12844
PubMed: 32794459
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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scheme="Wicri" type="geographic" xml:lang="fr"><term>Allemagne</term><term>Italie</term><term>Turquie</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>INTRODUCTION</b></p><p>There are significant differences in the active cases and fatality rates of Covid-19 for different European countries.</p></div><div type="abstract" xml:lang="en"><p><b>METHODOLOGY</b></p><p>The present study employs Monte Carlo based transmission growth simulations for Italy, Germany and Turkey. The probabilities of transmission at home, work and social networks and the number of initial cases have been calibrated to match the basic reproduction number and the reported fatality curves. Parametric studies were conducted to observe the effect of social distancing, work closure, testing and quarantine of the family and colleagues of positively tested individuals.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>It is observed that estimates of the number of initial cases in Italy compared to Turkey and Germany are higher. Turkey will probably experience about 30% less number of fatalities than Germany due its smaller elderly population. If social distancing and work contacts are limited to 25% of daily routines, Germany and Turkey may limit the number of fatalities to a few thousands as the reproduction number decreases to about 1.3 from 2.8. Random testing may reduce the number of fatalities by 10% upon testing least 5/1000 of the population. Quarantining of family and workmates of positively tested individuals may reduce the total number of fatalities by about 50%.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>The fatality rate of Covid-19 is estimated to be about 1.5% based on the simulation results. This may further be reduced by limiting the number of non-family contacts to two, conducting tests more than 0.5% of the population and immediate quarantine of the contacts for positively tested individuals.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32794459</PMID><DateCompleted><Year>2020</Year><Month>08</Month><Day>28</Day></DateCompleted><DateRevised><Year>2020</Year><Month>08</Month><Day>28</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1972-2680</ISSN><JournalIssue CitedMedium="Internet"><Volume>14</Volume><Issue>7</Issue><PubDate><Year>2020</Year><Month>Jul</Month><Day>31</Day></PubDate></JournalIssue><Title>Journal of infection in developing countries</Title><ISOAbbreviation>J Infect Dev Ctries</ISOAbbreviation></Journal><ArticleTitle>Transmission dynamics of Covid-19 in Italy, Germany and Turkey considering social distancing, testing and quarantine.</ArticleTitle><Pagination><MedlinePgn>713-720</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.3855/jidc.12844</ELocationID><Abstract><AbstractText Label="INTRODUCTION" NlmCategory="BACKGROUND">There are significant differences in the active cases and fatality rates of Covid-19 for different European countries.</AbstractText><AbstractText Label="METHODOLOGY" NlmCategory="METHODS">The present study employs Monte Carlo based transmission growth simulations for Italy, Germany and Turkey. The probabilities of transmission at home, work and social networks and the number of initial cases have been calibrated to match the basic reproduction number and the reported fatality curves. Parametric studies were conducted to observe the effect of social distancing, work closure, testing and quarantine of the family and colleagues of positively tested individuals.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">It is observed that estimates of the number of initial cases in Italy compared to Turkey and Germany are higher. Turkey will probably experience about 30% less number of fatalities than Germany due its smaller elderly population. If social distancing and work contacts are limited to 25% of daily routines, Germany and Turkey may limit the number of fatalities to a few thousands as the reproduction number decreases to about 1.3 from 2.8. Random testing may reduce the number of fatalities by 10% upon testing least 5/1000 of the population. Quarantining of family and workmates of positively tested individuals may reduce the total number of fatalities by about 50%.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">The fatality rate of Covid-19 is estimated to be about 1.5% based on the simulation results. This may further be reduced by limiting the number of non-family contacts to two, conducting tests more than 0.5% of the population and immediate quarantine of the contacts for positively tested individuals.</AbstractText><CopyrightInformation>Copyright (c) 2020 Serdar Gul, Kagan Tuncay, Baris Binici, Beyazit Bestami Aydin.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Gul</LastName><ForeName>Serdar</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Department of Infectious Diseases and Clinical Microbiology, Kirikkale University, Kirikkale, Turkey. serdarguul@yahoo.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tuncay</LastName><ForeName>Kagan</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>Faculty of Engineering, Middle East Technical University, Ankara, Turkey. tuncay@metu.edu.tr.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Binici</LastName><ForeName>Baris</ForeName><Initials>B</Initials><AffiliationInfo><Affiliation>Faculty of Engineering, Middle East Technical University, Ankara, Turkey. binici@metu.edu.tr.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Aydin</LastName><ForeName>Beyazit Bestami</ForeName><Initials>BB</Initials><AffiliationInfo><Affiliation>Faculty of Engineering, Middle East Technical University, Ankara, Turkey. beyazit@metu.edu.tr.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>07</Month><Day>31</Day></ArticleDate></Article><MedlineJournalInfo><Country>Italy</Country><MedlineTA>J Infect Dev Ctries</MedlineTA><NlmUniqueID>101305410</NlmUniqueID><ISSNLinking>1972-2680</ISSNLinking></MedlineJournalInfo><SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName><SupplMeshName Type="Protocol" UI="C000657964">COVID-19 diagnostic testing</SupplMeshName></SupplMeshList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017677" MajorTopicYN="N">Age Distribution</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D050936" MajorTopicYN="N">Basic Reproduction Number</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002648" MajorTopicYN="N">Child</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D019411" MajorTopicYN="N">Clinical Laboratory Techniques</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName><QualifierName UI="Q000175" MajorTopicYN="N">diagnosis</QualifierName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000401" MajorTopicYN="N">mortality</QualifierName><QualifierName UI="Q000635" MajorTopicYN="Y">transmission</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005191" MajorTopicYN="N">Family Characteristics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005858" MajorTopicYN="N" Type="Geographic">Germany</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007558" MajorTopicYN="N" Type="Geographic">Italy</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D009010" MajorTopicYN="N">Monte Carlo Method</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName><QualifierName UI="Q000175" MajorTopicYN="N">diagnosis</QualifierName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000401" MajorTopicYN="N">mortality</QualifierName><QualifierName UI="Q000635" MajorTopicYN="Y">transmission</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011790" MajorTopicYN="Y">Quarantine</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012934" MajorTopicYN="N">Social Isolation</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D060756" MajorTopicYN="N">Social Networking</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014421" MajorTopicYN="N" Type="Geographic">Turkey</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">COVID-19</Keyword><Keyword MajorTopicYN="N">Germany</Keyword><Keyword MajorTopicYN="N">Italy</Keyword><Keyword MajorTopicYN="N">Turkey</Keyword><Keyword MajorTopicYN="N">social distancing</Keyword><Keyword MajorTopicYN="N">transmission</Keyword></KeywordList><CoiStatement>No Conflict of Interest is declared</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>04</Month><Day>18</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>06</Month><Day>30</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>8</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>8</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>8</Month><Day>29</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32794459</ArticleId><ArticleId IdType="doi">10.3855/jidc.12844</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Turquie</li></country></list><tree><country name="Turquie"><noRegion><name sortKey="Gul, Serdar" sort="Gul, Serdar" uniqKey="Gul S" first="Serdar" last="Gul">Serdar Gul</name></noRegion><name sortKey="Aydin, Beyazit Bestami" sort="Aydin, Beyazit Bestami" uniqKey="Aydin B" first="Beyazit Bestami" last="Aydin">Beyazit Bestami Aydin</name><name sortKey="Binici, Baris" sort="Binici, Baris" uniqKey="Binici B" first="Baris" last="Binici">Baris Binici</name><name sortKey="Tuncay, Kagan" sort="Tuncay, Kagan" uniqKey="Tuncay K" first="Kagan" last="Tuncay">Kagan Tuncay</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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