CovidSeniorV1, Main, Exploration, bibRecord, 000021

COVID-19 mortality among migrants living in Italy.

Identifieur interne : 000021 ( Main/Exploration ); précédent : 000020; suivant : 000022

COVID-19 mortality among migrants living in Italy.

Auteurs : Marco Canevelli [Italie] ; Luigi Palmieri [Italie] ; Valeria Raparelli [Italie] ; Ornella Punzo [Italie] ; Chiara Donfrancesco [Italie] ; Cinzia Lo Noce [Italie] ; Nicola Vanacore [Italie] ; Silvio Brusaferro ; Graziano Onder [Italie]

Source :

Annali dell'Istituto superiore di sanita [ 2384-8553 ]

RBID : pubmed:32959804

Descripteurs français

KwdFr :
- Adulte (MeSH), Adulte d'âge moyen (MeSH), Albanie (ethnologie), Archives administratives hospitalières (MeSH), Betacoronavirus (MeSH), Broncho-pneumopathie chronique obstructive (épidémiologie), Cause de décès (MeSH), Comorbidité (MeSH), Diabète de type 2 (épidémiologie), Effet du travailleur en bonne santé (MeSH), Femelle (MeSH), France (ethnologie), Humains (MeSH), Infections à coronavirus (mortalité), Insuffisance rénale chronique (épidémiologie), Italie (épidémiologie), Maladies cardiovasculaires (épidémiologie), Mortalité (ethnologie), Mâle (MeSH), Obésité (épidémiologie), Pandémies (MeSH), Pneumopathie virale (mortalité), Population de passage et migrants (statistiques et données numériques), Répartition par âge (MeSH), Sujet âgé (MeSH), Sujet âgé de 80 ans ou plus (MeSH), Tumeurs (épidémiologie).
MESH :
- ethnologie : Albanie, France, Mortalité.
- mortalité : Infections à coronavirus, Pneumopathie virale.
- statistiques et données numériques : Population de passage et migrants.
- épidémiologie : Broncho-pneumopathie chronique obstructive, Diabète de type 2, Insuffisance rénale chronique, Italie, Maladies cardiovasculaires, Obésité, Tumeurs.
- Adulte, Adulte d'âge moyen, Archives administratives hospitalières, Betacoronavirus, Cause de décès, Comorbidité, Effet du travailleur en bonne santé, Femelle, Humains, Mâle, Pandémies, Répartition par âge, Sujet âgé, Sujet âgé de 80 ans ou plus.
Wicri :
- geographic : Italie.

English descriptors

KwdEn :
- Adult (MeSH), Age Distribution (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Albania (ethnology), Betacoronavirus (MeSH), Cardiovascular Diseases (epidemiology), Cause of Death (MeSH), Comorbidity (MeSH), Coronavirus Infections (mortality), Diabetes Mellitus, Type 2 (epidemiology), Female (MeSH), France (ethnology), Healthy Worker Effect (MeSH), Hospital Records (MeSH), Humans (MeSH), Italy (epidemiology), Male (MeSH), Middle Aged (MeSH), Mortality (ethnology), Neoplasms (epidemiology), Obesity (epidemiology), Pandemics (MeSH), Pneumonia, Viral (mortality), Pulmonary Disease, Chronic Obstructive (epidemiology), Renal Insufficiency, Chronic (epidemiology), Transients and Migrants (statistics & numerical data).
MESH :
- geographic , epidemiology : Italy.
- geographic , ethnology : Albania, France.
- epidemiology : Cardiovascular Diseases, Diabetes Mellitus, Type 2, Neoplasms, Obesity, Pulmonary Disease, Chronic Obstructive, Renal Insufficiency, Chronic.
- ethnology : Mortality.
- mortality : Coronavirus Infections, Pneumonia, Viral.
- statistics & numerical data : Transients and Migrants.
- Adult, Age Distribution, Aged, Aged, 80 and over, Betacoronavirus, Cause of Death, Comorbidity, Female, Healthy Worker Effect, Hospital Records, Humans, Male, Middle Aged, Pandemics.

Abstract

We aimed to compare COVID-19-specific and all-cause mortality rates among natives and migrants in Italy and to investigate the clinical characteristics of individuals dying with COVID-19 by native/migrant status. The mortality rates and detailed clinical characteristics of natives and migrants dying with COVID-19 were explored by considering the medical charts of a representative sample of patients deceased in Italian hospitals (n = 2,687) between February 21st and April 29th, 2020. The migrant or native status was assigned based on the individual's country of birth. The expected all-cause mortality among natives and migrants living in Italy was derived by the last available (2018) dataset provided by the Italian National Institute of Statistics. Overall, 68 individuals with a migration background were identified. The proportions of natives and migrants among the COVID-19-related deaths (97.5% and 2.5%, respectively) were similar to the relative all-cause mortality rates estimated in Italy in 2018 (97.4% and 2.6%, respectively). The clinical phenotype of migrants dying with COVID-19 was similar to that of natives except for the younger age at death. International migrants living in Italy do not have a mortality advantage for COVID-19 and are exposed to the risk of poor outcomes as their native counterparts.

DOI: 10.4415/ANN_20_03_16
PubMed: 32959804

Affiliations:

Links toward previous steps (curation, corpus...)

to stream Main, to step Corpus: 000141
to stream Main, to step Curation: 000141

Le document en format XML

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<author><name sortKey="Donfrancesco, Chiara" sort="Donfrancesco, Chiara" uniqKey="Donfrancesco C" first="Chiara" last="Donfrancesco">Chiara Donfrancesco</name>
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<author><name sortKey="Vanacore, Nicola" sort="Vanacore, Nicola" uniqKey="Vanacore N" first="Nicola" last="Vanacore">Nicola Vanacore</name>
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<author><name sortKey="Brusaferro, Silvio" sort="Brusaferro, Silvio" uniqKey="Brusaferro S" first="Silvio" last="Brusaferro">Silvio Brusaferro</name>
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<author><name sortKey="Onder, Graziano" sort="Onder, Graziano" uniqKey="Onder G" first="Graziano" last="Onder">Graziano Onder</name>
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<sourceDesc><biblStruct><analytic><title xml:lang="en">COVID-19 mortality among migrants living in Italy.</title>
<author><name sortKey="Canevelli, Marco" sort="Canevelli, Marco" uniqKey="Canevelli M" first="Marco" last="Canevelli">Marco Canevelli</name>
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<author><name sortKey="Palmieri, Luigi" sort="Palmieri, Luigi" uniqKey="Palmieri L" first="Luigi" last="Palmieri">Luigi Palmieri</name>
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<author><name sortKey="Punzo, Ornella" sort="Punzo, Ornella" uniqKey="Punzo O" first="Ornella" last="Punzo">Ornella Punzo</name>
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<country xml:lang="fr">Italie</country>
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<author><name sortKey="Donfrancesco, Chiara" sort="Donfrancesco, Chiara" uniqKey="Donfrancesco C" first="Chiara" last="Donfrancesco">Chiara Donfrancesco</name>
<affiliation wicri:level="3"><nlm:affiliation>Dipartimento Malattie Cardiovascolari, Endocrino-Metaboliche e Invecchiamento, Istituto Superiore di Sanità, Rome, Italy.</nlm:affiliation>
<country xml:lang="fr">Italie</country>
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<author><name sortKey="Lo Noce, Cinzia" sort="Lo Noce, Cinzia" uniqKey="Lo Noce C" first="Cinzia" last="Lo Noce">Cinzia Lo Noce</name>
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<country xml:lang="fr">Italie</country>
<wicri:regionArea>Dipartimento Malattie Cardiovascolari, Endocrino-Metaboliche e Invecchiamento, Istituto Superiore di Sanità, Rome</wicri:regionArea>
<placeName><settlement type="city">Rome</settlement>
<region nuts="2">Latium</region>
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<author><name sortKey="Vanacore, Nicola" sort="Vanacore, Nicola" uniqKey="Vanacore N" first="Nicola" last="Vanacore">Nicola Vanacore</name>
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<country xml:lang="fr">Italie</country>
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<author><name sortKey="Brusaferro, Silvio" sort="Brusaferro, Silvio" uniqKey="Brusaferro S" first="Silvio" last="Brusaferro">Silvio Brusaferro</name>
<affiliation><nlm:affiliation>President, Istituto Superiore di Sanità, Rome, Italy *The members of the Italian National Institute of Health COVID-19 Mortality Group are listed before the References.</nlm:affiliation>
<wicri:noCountry code="subField">Italy *The members of the Italian National Institute of Health COVID-19 Mortality Group are listed before the References</wicri:noCountry>
</affiliation>
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<author><name sortKey="Onder, Graziano" sort="Onder, Graziano" uniqKey="Onder G" first="Graziano" last="Onder">Graziano Onder</name>
<affiliation wicri:level="3"><nlm:affiliation>Dipartimento Malattie Cardiovascolari, Endocrino-Metaboliche e Invecchiamento, Istituto Superiore di Sanità, Rome, Italy.</nlm:affiliation>
<country xml:lang="fr">Italie</country>
<wicri:regionArea>Dipartimento Malattie Cardiovascolari, Endocrino-Metaboliche e Invecchiamento, Istituto Superiore di Sanità, Rome</wicri:regionArea>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult (MeSH)</term>
<term>Age Distribution (MeSH)</term>
<term>Aged (MeSH)</term>
<term>Aged, 80 and over (MeSH)</term>
<term>Albania (ethnology)</term>
<term>Betacoronavirus (MeSH)</term>
<term>Cardiovascular Diseases (epidemiology)</term>
<term>Cause of Death (MeSH)</term>
<term>Comorbidity (MeSH)</term>
<term>Coronavirus Infections (mortality)</term>
<term>Diabetes Mellitus, Type 2 (epidemiology)</term>
<term>Female (MeSH)</term>
<term>France (ethnology)</term>
<term>Healthy Worker Effect (MeSH)</term>
<term>Hospital Records (MeSH)</term>
<term>Humans (MeSH)</term>
<term>Italy (epidemiology)</term>
<term>Male (MeSH)</term>
<term>Middle Aged (MeSH)</term>
<term>Mortality (ethnology)</term>
<term>Neoplasms (epidemiology)</term>
<term>Obesity (epidemiology)</term>
<term>Pandemics (MeSH)</term>
<term>Pneumonia, Viral (mortality)</term>
<term>Pulmonary Disease, Chronic Obstructive (epidemiology)</term>
<term>Renal Insufficiency, Chronic (epidemiology)</term>
<term>Transients and Migrants (statistics & numerical data)</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Adulte (MeSH)</term>
<term>Adulte d'âge moyen (MeSH)</term>
<term>Albanie (ethnologie)</term>
<term>Archives administratives hospitalières (MeSH)</term>
<term>Betacoronavirus (MeSH)</term>
<term>Broncho-pneumopathie chronique obstructive (épidémiologie)</term>
<term>Cause de décès (MeSH)</term>
<term>Comorbidité (MeSH)</term>
<term>Diabète de type 2 (épidémiologie)</term>
<term>Effet du travailleur en bonne santé (MeSH)</term>
<term>Femelle (MeSH)</term>
<term>France (ethnologie)</term>
<term>Humains (MeSH)</term>
<term>Infections à coronavirus (mortalité)</term>
<term>Insuffisance rénale chronique (épidémiologie)</term>
<term>Italie (épidémiologie)</term>
<term>Maladies cardiovasculaires (épidémiologie)</term>
<term>Mortalité (ethnologie)</term>
<term>Mâle (MeSH)</term>
<term>Obésité (épidémiologie)</term>
<term>Pandémies (MeSH)</term>
<term>Pneumopathie virale (mortalité)</term>
<term>Population de passage et migrants (statistiques et données numériques)</term>
<term>Répartition par âge (MeSH)</term>
<term>Sujet âgé (MeSH)</term>
<term>Sujet âgé de 80 ans ou plus (MeSH)</term>
<term>Tumeurs (épidémiologie)</term>
</keywords>
<keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Italy</term>
</keywords>
<keywords scheme="MESH" type="geographic" qualifier="ethnology" xml:lang="en"><term>Albania</term>
<term>France</term>
</keywords>
<keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Cardiovascular Diseases</term>
<term>Diabetes Mellitus, Type 2</term>
<term>Neoplasms</term>
<term>Obesity</term>
<term>Pulmonary Disease, Chronic Obstructive</term>
<term>Renal Insufficiency, Chronic</term>
</keywords>
<keywords scheme="MESH" qualifier="ethnologie" xml:lang="fr"><term>Albanie</term>
<term>France</term>
<term>Mortalité</term>
</keywords>
<keywords scheme="MESH" qualifier="ethnology" xml:lang="en"><term>Mortality</term>
</keywords>
<keywords scheme="MESH" qualifier="mortality" xml:lang="en"><term>Coronavirus Infections</term>
<term>Pneumonia, Viral</term>
</keywords>
<keywords scheme="MESH" qualifier="mortalité" xml:lang="fr"><term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
</keywords>
<keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Transients and Migrants</term>
</keywords>
<keywords scheme="MESH" qualifier="statistiques et données numériques" xml:lang="fr"><term>Population de passage et migrants</term>
</keywords>
<keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Broncho-pneumopathie chronique obstructive</term>
<term>Diabète de type 2</term>
<term>Insuffisance rénale chronique</term>
<term>Italie</term>
<term>Maladies cardiovasculaires</term>
<term>Obésité</term>
<term>Tumeurs</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Adult</term>
<term>Age Distribution</term>
<term>Aged</term>
<term>Aged, 80 and over</term>
<term>Betacoronavirus</term>
<term>Cause of Death</term>
<term>Comorbidity</term>
<term>Female</term>
<term>Healthy Worker Effect</term>
<term>Hospital Records</term>
<term>Humans</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Pandemics</term>
</keywords>
<keywords scheme="MESH" xml:lang="fr"><term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Archives administratives hospitalières</term>
<term>Betacoronavirus</term>
<term>Cause de décès</term>
<term>Comorbidité</term>
<term>Effet du travailleur en bonne santé</term>
<term>Femelle</term>
<term>Humains</term>
<term>Mâle</term>
<term>Pandémies</term>
<term>Répartition par âge</term>
<term>Sujet âgé</term>
<term>Sujet âgé de 80 ans ou plus</term>
</keywords>
<keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Italie</term>
</keywords>
</textClass>
</profileDesc>
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<front><div type="abstract" xml:lang="en">We aimed to compare COVID-19-specific and all-cause mortality rates among natives and migrants in Italy and to investigate the clinical characteristics of individuals dying with COVID-19 by native/migrant status. The mortality rates and detailed clinical characteristics of natives and migrants dying with COVID-19 were explored by considering the medical charts of a representative sample of patients deceased in Italian hospitals (n = 2,687) between February 21st and April 29th, 2020. The migrant or native status was assigned based on the individual's country of birth. The expected all-cause mortality among natives and migrants living in Italy was derived by the last available (2018) dataset provided by the Italian National Institute of Statistics. Overall, 68 individuals with a migration background were identified. The proportions of natives and migrants among the COVID-19-related deaths (97.5% and 2.5%, respectively) were similar to the relative all-cause mortality rates estimated in Italy in 2018 (97.4% and 2.6%, respectively). The clinical phenotype of migrants dying with COVID-19 was similar to that of natives except for the younger age at death. International migrants living in Italy do not have a mortality advantage for COVID-19 and are exposed to the risk of poor outcomes as their native counterparts.</div>
</front>
</TEI>
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<DateCompleted><Year>2020</Year>
<Month>10</Month>
<Day>02</Day>
</DateCompleted>
<DateRevised><Year>2020</Year>
<Month>10</Month>
<Day>02</Day>
</DateRevised>
<Article PubModel="Print"><Journal><ISSN IssnType="Electronic">2384-8553</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>56</Volume>
<Issue>3</Issue>
<PubDate><MedlineDate>2020 Jul-Sep</MedlineDate>
</PubDate>
</JournalIssue>
<Title>Annali dell'Istituto superiore di sanita</Title>
<ISOAbbreviation>Ann Ist Super Sanita</ISOAbbreviation>
</Journal>
<ArticleTitle>COVID-19 mortality among migrants living in Italy.</ArticleTitle>
<Pagination><MedlinePgn>373-377</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.4415/ANN_20_03_16</ELocationID>
<Abstract><AbstractText>We aimed to compare COVID-19-specific and all-cause mortality rates among natives and migrants in Italy and to investigate the clinical characteristics of individuals dying with COVID-19 by native/migrant status. The mortality rates and detailed clinical characteristics of natives and migrants dying with COVID-19 were explored by considering the medical charts of a representative sample of patients deceased in Italian hospitals (n = 2,687) between February 21st and April 29th, 2020. The migrant or native status was assigned based on the individual's country of birth. The expected all-cause mortality among natives and migrants living in Italy was derived by the last available (2018) dataset provided by the Italian National Institute of Statistics. Overall, 68 individuals with a migration background were identified. The proportions of natives and migrants among the COVID-19-related deaths (97.5% and 2.5%, respectively) were similar to the relative all-cause mortality rates estimated in Italy in 2018 (97.4% and 2.6%, respectively). The clinical phenotype of migrants dying with COVID-19 was similar to that of natives except for the younger age at death. International migrants living in Italy do not have a mortality advantage for COVID-19 and are exposed to the risk of poor outcomes as their native counterparts.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Canevelli</LastName>
<ForeName>Marco</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>Centro Nazionale per la Prevenzione delle Malattie e la Promozione della Salute, Istituto Superiore di Sanità, Rome, Italy - Dipartimento di Neuroscienze Umane, Sapienza Università di Roma, Rome, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Palmieri</LastName>
<ForeName>Luigi</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>Dipartimento Malattie Cardiovascolari, Endocrino-Metaboliche e Invecchiamento, Istituto Superiore di Sanità, Rome, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Raparelli</LastName>
<ForeName>Valeria</ForeName>
<Initials>V</Initials>
<AffiliationInfo><Affiliation>Dipartimento di Medicina Sperimentale, Sapienza Università di Roma, Rome, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Punzo</LastName>
<ForeName>Ornella</ForeName>
<Initials>O</Initials>
<AffiliationInfo><Affiliation>Dipartimento di Malattie Infettive, Istituto Superiore di Sanità, Rome, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Donfrancesco</LastName>
<ForeName>Chiara</ForeName>
<Initials>C</Initials>
<AffiliationInfo><Affiliation>Dipartimento Malattie Cardiovascolari, Endocrino-Metaboliche e Invecchiamento, Istituto Superiore di Sanità, Rome, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Lo Noce</LastName>
<ForeName>Cinzia</ForeName>
<Initials>C</Initials>
<AffiliationInfo><Affiliation>Dipartimento Malattie Cardiovascolari, Endocrino-Metaboliche e Invecchiamento, Istituto Superiore di Sanità, Rome, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Vanacore</LastName>
<ForeName>Nicola</ForeName>
<Initials>N</Initials>
<AffiliationInfo><Affiliation>Centro Nazionale per la Prevenzione delle Malattie e la Promozione della Salute, Istituto Superiore di Sanità, Rome, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Brusaferro</LastName>
<ForeName>Silvio</ForeName>
<Initials>S</Initials>
<AffiliationInfo><Affiliation>President, Istituto Superiore di Sanità, Rome, Italy *The members of the Italian National Institute of Health COVID-19 Mortality Group are listed before the References.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Onder</LastName>
<ForeName>Graziano</ForeName>
<Initials>G</Initials>
<AffiliationInfo><Affiliation>Dipartimento Malattie Cardiovascolari, Endocrino-Metaboliche e Invecchiamento, Istituto Superiore di Sanità, Rome, Italy.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><CollectiveName>Italian National Institute of Health COVID-19 Mortality Group</CollectiveName>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
</Article>
<MedlineJournalInfo><Country>Italy</Country>
<MedlineTA>Ann Ist Super Sanita</MedlineTA>
<NlmUniqueID>7502520</NlmUniqueID>
<ISSNLinking>0021-2571</ISSNLinking>
</MedlineJournalInfo>
<SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName>
<SupplMeshName Type="Organism" UI="C000656484">severe acute respiratory syndrome coronavirus 2</SupplMeshName>
</SupplMeshList>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList><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="D000369" MajorTopicYN="N">Aged, 80 and over</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000415" MajorTopicYN="N" Type="Geographic">Albania</DescriptorName>
<QualifierName UI="Q000208" MajorTopicYN="N">ethnology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000073640" MajorTopicYN="Y">Betacoronavirus</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D002318" MajorTopicYN="N">Cardiovascular Diseases</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D002423" MajorTopicYN="N">Cause of Death</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D015897" MajorTopicYN="N">Comorbidity</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName>
<QualifierName UI="Q000401" MajorTopicYN="Y">mortality</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D003924" MajorTopicYN="N">Diabetes Mellitus, Type 2</DescriptorName>
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<MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName>
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<MeshHeading><DescriptorName UI="D006753" MajorTopicYN="N">Hospital Records</DescriptorName>
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<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>
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<MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName>
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<MeshHeading><DescriptorName UI="D009026" MajorTopicYN="N">Mortality</DescriptorName>
<QualifierName UI="Q000208" MajorTopicYN="N">ethnology</QualifierName>
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<MeshHeading><DescriptorName UI="D009369" MajorTopicYN="N">Neoplasms</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D009765" MajorTopicYN="N">Obesity</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D058873" MajorTopicYN="Y">Pandemics</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName>
<QualifierName UI="Q000401" MajorTopicYN="Y">mortality</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D029424" MajorTopicYN="N">Pulmonary Disease, Chronic Obstructive</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
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<MeshHeading><DescriptorName UI="D051436" MajorTopicYN="N">Renal Insufficiency, Chronic</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
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<MeshHeading><DescriptorName UI="D014171" MajorTopicYN="N">Transients and Migrants</DescriptorName>
<QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName>
</MeshHeading>
</MeshHeadingList>
<InvestigatorList><Investigator ValidYN="Y"><LastName>Palmieri</LastName>
<ForeName>Luigi</ForeName>
<Initials>L</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Bertinato</LastName>
<ForeName>Luigi</ForeName>
<Initials>L</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Brambilla</LastName>
<ForeName>Gianfranco</ForeName>
<Initials>G</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Calcagnini</LastName>
<ForeName>Giovanni</ForeName>
<Initials>G</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Canevelli</LastName>
<ForeName>Marco</ForeName>
<Initials>M</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Censi</LastName>
<ForeName>Federica</ForeName>
<Initials>F</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Colaizzo</LastName>
<ForeName>Elisa</ForeName>
<Initials>E</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Donfrancesco</LastName>
<ForeName>Chiara</ForeName>
<Initials>C</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Facchiano</LastName>
<ForeName>Francesco</ForeName>
<Initials>F</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Floridia</LastName>
<ForeName>Marco</ForeName>
<Initials>M</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Giuliano</LastName>
<ForeName>Marina</ForeName>
<Initials>M</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Grisetti</LastName>
<ForeName>Tiziana</ForeName>
<Initials>T</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Kodra</LastName>
<ForeName>Yllka</ForeName>
<Initials>Y</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Langer</LastName>
<ForeName>Martin</ForeName>
<Initials>M</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Lega</LastName>
<ForeName>Ilaria</ForeName>
<Initials>I</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Lo Noce</LastName>
<ForeName>Cinzia</ForeName>
<Initials>C</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Malchiodi Albedi</LastName>
<ForeName>Fiorella</ForeName>
<Initials>F</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Manno</LastName>
<ForeName>Valerio</ForeName>
<Initials>V</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Mattei</LastName>
<ForeName>Eugenio</ForeName>
<Initials>E</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Meli</LastName>
<ForeName>Paola</ForeName>
<Initials>P</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Minelli</LastName>
<ForeName>Giada</ForeName>
<Initials>G</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Nebuloni</LastName>
<ForeName>Manuela</ForeName>
<Initials>M</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Nisticò</LastName>
<ForeName>Lorenza</ForeName>
<Initials>L</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Nonis</LastName>
<ForeName>Marino</ForeName>
<Initials>M</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Onder</LastName>
<ForeName>Graziano</ForeName>
<Initials>G</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Palmisano</LastName>
<ForeName>Lucia</ForeName>
<Initials>L</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Petrosillo</LastName>
<ForeName>Nicola</ForeName>
<Initials>N</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Pricci</LastName>
<ForeName>Flavia</ForeName>
<Initials>F</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Punzo</LastName>
<ForeName>Ornella</ForeName>
<Initials>O</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Raparelli</LastName>
<ForeName>Valeria</ForeName>
<Initials>V</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Salerno</LastName>
<ForeName>Paolo</ForeName>
<Initials>P</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Tamburo De Bella</LastName>
<ForeName>Manuela</ForeName>
<Initials>M</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Taruscio</LastName>
<ForeName>Domenica</ForeName>
<Initials>D</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Tiple</LastName>
<ForeName>Dorina</ForeName>
<Initials>D</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Unim</LastName>
<ForeName>Brigid</ForeName>
<Initials>B</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Vaianella</LastName>
<ForeName>Luana</ForeName>
<Initials>L</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Vanacore</LastName>
<ForeName>Nicola</ForeName>
<Initials>N</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Vichi</LastName>
<ForeName>Monica</ForeName>
<Initials>M</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Rocco Villani</LastName>
<ForeName>Emanuele</ForeName>
<Initials>E</Initials>
</Investigator>
<Investigator ValidYN="Y"><LastName>Zona</LastName>
<ForeName>Amerigo</ForeName>
<Initials>A</Initials>
</Investigator>
</InvestigatorList>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2020</Year>
<Month>9</Month>
<Day>22</Day>
<Hour>8</Hour>
<Minute>40</Minute>
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<PubMedPubDate PubStatus="pubmed"><Year>2020</Year>
<Month>9</Month>
<Day>23</Day>
<Hour>6</Hour>
<Minute>0</Minute>
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<PubMedPubDate PubStatus="medline"><Year>2020</Year>
<Month>10</Month>
<Day>3</Day>
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<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">32959804</ArticleId>
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<affiliations><list><country><li>Italie</li>
</country>
<region><li>Latium</li>
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<tree><noCountry><name sortKey="Brusaferro, Silvio" sort="Brusaferro, Silvio" uniqKey="Brusaferro S" first="Silvio" last="Brusaferro">Silvio Brusaferro</name>
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<country name="Italie"><region name="Latium"><name sortKey="Canevelli, Marco" sort="Canevelli, Marco" uniqKey="Canevelli M" first="Marco" last="Canevelli">Marco Canevelli</name>
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<name sortKey="Donfrancesco, Chiara" sort="Donfrancesco, Chiara" uniqKey="Donfrancesco C" first="Chiara" last="Donfrancesco">Chiara Donfrancesco</name>
<name sortKey="Lo Noce, Cinzia" sort="Lo Noce, Cinzia" uniqKey="Lo Noce C" first="Cinzia" last="Lo Noce">Cinzia Lo Noce</name>
<name sortKey="Onder, Graziano" sort="Onder, Graziano" uniqKey="Onder G" first="Graziano" last="Onder">Graziano Onder</name>
<name sortKey="Palmieri, Luigi" sort="Palmieri, Luigi" uniqKey="Palmieri L" first="Luigi" last="Palmieri">Luigi Palmieri</name>
<name sortKey="Punzo, Ornella" sort="Punzo, Ornella" uniqKey="Punzo O" first="Ornella" last="Punzo">Ornella Punzo</name>
<name sortKey="Raparelli, Valeria" sort="Raparelli, Valeria" uniqKey="Raparelli V" first="Valeria" last="Raparelli">Valeria Raparelli</name>
<name sortKey="Vanacore, Nicola" sort="Vanacore, Nicola" uniqKey="Vanacore N" first="Nicola" last="Vanacore">Nicola Vanacore</name>
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	Serveur d'exploration sur la COVID chez les séniors
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COVID-19 mortality among migrants living in Italy.

COVID-19 mortality among migrants living in Italy.

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