Measuring dynamic social contacts in a rehabilitation hospital: effect of wards, patient and staff characteristics View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Audrey Duval, Thomas Obadia, Lucie Martinet, Pierre-Yves Boëlle, Eric Fleury, Didier Guillemot, Lulla Opatowski, Laura Temime,

ABSTRACT

Understanding transmission routes of hospital-acquired infections (HAI) is key to improve their control. In this context, describing and analyzing dynamic inter-individual contact patterns in hospitals is essential. In this study, we used wearable sensors to detect Close Proximity Interactions (CPIs) among patients and hospital staff in a 200-bed long-term care facility over 4 months. First, the dynamic CPI data was described in terms of contact frequency and duration per individual status or activity and per ward. Second, we investigated the individual factors associated with high contact frequency or duration using generalized linear mixed-effect models to account for inter-ward heterogeneity. Hospital porters and physicians had the highest daily number of distinct contacts, making them more likely to disseminate HAI among individuals. Conversely, contact duration was highest between patients, with potential implications in terms of HAI acquisition risk. Contact patterns differed among hospital wards, reflecting varying care patterns depending on reason for hospitalization, with more frequent contacts in neurologic wards and fewer, longer contacts in geriatric wards. This study is the first to report proximity-sensing data informing on inter-individual contacts in long-term care settings. Our results should help better understand HAI spread, parameterize future mathematical models, and propose efficient control strategies. More... »

PAGES

1686

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-018-20008-w

DOI

http://dx.doi.org/10.1038/s41598-018-20008-w

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100570980

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29374222


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1117", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Public Health and Health Services", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "name": [
            "Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (B2PHI), Inserm, UVSQ, Institut Pasteur, Universit\u00e9 Paris-Saclay, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Duval", 
        "givenName": "Audrey", 
        "id": "sg:person.016530015130.29", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016530015130.29"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institut Pasteur", 
          "id": "https://www.grid.ac/institutes/grid.428999.7", 
          "name": [
            "Institut Pasteur \u2013 Bioinformatics and Biostatistics Hub \u2013 C3BI, USR 3756 IP CNRS, Paris, France", 
            "Malaria Parasites & Hosts Unit, Department of Parasites & Insect Vectors, Institut Pasteur, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Obadia", 
        "givenName": "Thomas", 
        "id": "sg:person.0613066252.07", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0613066252.07"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "\u00c9cole Normale Sup\u00e9rieure de Lyon", 
          "id": "https://www.grid.ac/institutes/grid.15140.31", 
          "name": [
            "ENS de Lyon, DANTE/INRIA, LIP UMR CNRS 5668 Universit\u00e9 de Lyon, Lyon, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Martinet", 
        "givenName": "Lucie", 
        "id": "sg:person.015524121101.54", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015524121101.54"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Sorbonne University", 
          "id": "https://www.grid.ac/institutes/grid.462844.8", 
          "name": [
            "Sorbonne Universit\u00e9s, UPMC Univ Paris 06, UMR_S 1136, Institut Pierre Louis d\u2019Epid\u00e9miologie et de Sant\u00e9 Publique, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bo\u00eblle", 
        "givenName": "Pierre-Yves", 
        "id": "sg:person.01217105733.78", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01217105733.78"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "\u00c9cole Normale Sup\u00e9rieure de Lyon", 
          "id": "https://www.grid.ac/institutes/grid.15140.31", 
          "name": [
            "ENS de Lyon, Universit\u00e9 de Lyon, Laboratoire de l\u2019Informatique du Parall\u00e9lisme (UMR CNRS 5668- ENS de Lyon-UCB Lyon 1), IXXI Rh\u00f4ne Alpes Complex Systems Institute, Lyon, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fleury", 
        "givenName": "Eric", 
        "id": "sg:person.013601454301.39", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013601454301.39"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Versailles Saint-Quentin-en-Yvelines University", 
          "id": "https://www.grid.ac/institutes/grid.12832.3a", 
          "name": [
            "INSERM 1181 Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (B2PHI), Institut Pasteur, B2PHI Paris, France", 
            "Universit\u00e9 de Versailles Saint-Quentin, UMR 1181, B2PHI, Montigny-Le-Bretonneux, France", 
            "AP-HP, Raymond-Poincar\u00e9 Hospital, Garche, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Guillemot", 
        "givenName": "Didier", 
        "id": "sg:person.01265221133.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01265221133.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (B2PHI), Inserm, UVSQ, Institut Pasteur, Universit\u00e9 Paris-Saclay, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Opatowski", 
        "givenName": "Lulla", 
        "id": "sg:person.0652202333.32", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0652202333.32"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institut Pasteur", 
          "id": "https://www.grid.ac/institutes/grid.428999.7", 
          "name": [
            "Laboratoire MESuRS, Conservatoire national des Arts et M\u00e9tiers, Paris, France", 
            "Unit\u00e9 PACRI, Institut Pasteur, Conservatoire national des Arts et M\u00e9tiers, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Temime", 
        "givenName": "Laura", 
        "id": "sg:person.0770136252.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0770136252.45"
        ], 
        "type": "Person"
      }, 
      {}
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1073/pnas.0900974106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000151452"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pcbi.1004170", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000728436"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/infdis/jis542", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003128173"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/ice.2016.59", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003498666"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/mlr.0b013e3182836dc2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004641208"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/mlr.0b013e3182836dc2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004641208"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/ice.2015.89", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010626651"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1741-7015-9-87", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016144881", 
          "https://doi.org/10.1186/1741-7015-9-87"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0070854", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016577092"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0037893", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016988160"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.1009094108", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020444536"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/ice.2014.53", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022798089"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0087042", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025832843"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2334-13-185", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028759952", 
          "https://doi.org/10.1186/1471-2334-13-185"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2334-14-136", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032783055", 
          "https://doi.org/10.1186/1471-2334-14-136"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0073970", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034252344"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0107878", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039713470"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0107878", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039713470"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0017144", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047131764"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2334-13-294", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047261820", 
          "https://doi.org/10.1186/1471-2334-13-294"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pmed.0050074", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051930053"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep36301", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052028422", 
          "https://doi.org/10.1038/srep36301"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0950268812000842", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053749697"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "Understanding transmission routes of hospital-acquired infections (HAI) is key to improve their control. In this context, describing and analyzing dynamic inter-individual contact patterns in hospitals is essential. In this study, we used wearable sensors to detect Close Proximity Interactions (CPIs) among patients and hospital staff in a 200-bed long-term care facility over 4 months. First, the dynamic CPI data was described in terms of contact frequency and duration per individual status or activity and per ward. Second, we investigated the individual factors associated with high contact frequency or duration using generalized linear mixed-effect models to account for inter-ward heterogeneity. Hospital porters and physicians had the highest daily number of distinct contacts, making them more likely to disseminate HAI among individuals. Conversely, contact duration was highest between patients, with potential implications in terms of HAI acquisition risk. Contact patterns differed among hospital wards, reflecting varying care patterns depending on reason for hospitalization, with more frequent contacts in neurologic wards and fewer, longer contacts in geriatric wards. This study is the first to report proximity-sensing data informing on inter-individual contacts in long-term care settings. Our results should help better understand HAI spread, parameterize future mathematical models, and propose efficient control strategies.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/s41598-018-20008-w", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1045337", 
        "issn": [
          "2045-2322"
        ], 
        "name": "Scientific Reports", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "8"
      }
    ], 
    "name": "Measuring dynamic social contacts in a rehabilitation hospital: effect of wards, patient and staff characteristics", 
    "pagination": "1686", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "b575422c5530c5b5ca357518a08ee9fb0b0ac5fdcef28a2fc396233d2901a9b7"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "29374222"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101563288"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/s41598-018-20008-w"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1100570980"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/s41598-018-20008-w", 
      "https://app.dimensions.ai/details/publication/pub.1100570980"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T20:06", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8681_00000570.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://www.nature.com/articles/s41598-018-20008-w"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-20008-w'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-20008-w'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-20008-w'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-20008-w'


 

This table displays all metadata directly associated to this object as RDF triples.

206 TRIPLES      21 PREDICATES      50 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/s41598-018-20008-w schema:about anzsrc-for:11
2 anzsrc-for:1117
3 schema:author N808529cdea984842b87a2bb6a6be2d6a
4 schema:citation sg:pub.10.1038/srep36301
5 sg:pub.10.1186/1471-2334-13-185
6 sg:pub.10.1186/1471-2334-13-294
7 sg:pub.10.1186/1471-2334-14-136
8 sg:pub.10.1186/1741-7015-9-87
9 https://doi.org/10.1017/ice.2014.53
10 https://doi.org/10.1017/ice.2015.89
11 https://doi.org/10.1017/ice.2016.59
12 https://doi.org/10.1017/s0950268812000842
13 https://doi.org/10.1073/pnas.0900974106
14 https://doi.org/10.1073/pnas.1009094108
15 https://doi.org/10.1093/infdis/jis542
16 https://doi.org/10.1097/mlr.0b013e3182836dc2
17 https://doi.org/10.1371/journal.pcbi.1004170
18 https://doi.org/10.1371/journal.pmed.0050074
19 https://doi.org/10.1371/journal.pone.0017144
20 https://doi.org/10.1371/journal.pone.0037893
21 https://doi.org/10.1371/journal.pone.0070854
22 https://doi.org/10.1371/journal.pone.0073970
23 https://doi.org/10.1371/journal.pone.0087042
24 https://doi.org/10.1371/journal.pone.0107878
25 schema:datePublished 2018-12
26 schema:datePublishedReg 2018-12-01
27 schema:description Understanding transmission routes of hospital-acquired infections (HAI) is key to improve their control. In this context, describing and analyzing dynamic inter-individual contact patterns in hospitals is essential. In this study, we used wearable sensors to detect Close Proximity Interactions (CPIs) among patients and hospital staff in a 200-bed long-term care facility over 4 months. First, the dynamic CPI data was described in terms of contact frequency and duration per individual status or activity and per ward. Second, we investigated the individual factors associated with high contact frequency or duration using generalized linear mixed-effect models to account for inter-ward heterogeneity. Hospital porters and physicians had the highest daily number of distinct contacts, making them more likely to disseminate HAI among individuals. Conversely, contact duration was highest between patients, with potential implications in terms of HAI acquisition risk. Contact patterns differed among hospital wards, reflecting varying care patterns depending on reason for hospitalization, with more frequent contacts in neurologic wards and fewer, longer contacts in geriatric wards. This study is the first to report proximity-sensing data informing on inter-individual contacts in long-term care settings. Our results should help better understand HAI spread, parameterize future mathematical models, and propose efficient control strategies.
28 schema:genre research_article
29 schema:inLanguage en
30 schema:isAccessibleForFree true
31 schema:isPartOf N40a464d953af44b992dd1937e8d4ea27
32 Na6fe5e81516f44d4b33b97728af3585c
33 sg:journal.1045337
34 schema:name Measuring dynamic social contacts in a rehabilitation hospital: effect of wards, patient and staff characteristics
35 schema:pagination 1686
36 schema:productId N42b4711de655429cb74467683ebce6ac
37 Nd22ffe16193042b28b0f2339451b3de3
38 Ndf71b899f65e417c9c54b8d9210f5eae
39 Nf3e87276b5a64003864445231d385ff3
40 Nfaa53c7032614c3e994d9d0864fd965b
41 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100570980
42 https://doi.org/10.1038/s41598-018-20008-w
43 schema:sdDatePublished 2019-04-10T20:06
44 schema:sdLicense https://scigraph.springernature.com/explorer/license/
45 schema:sdPublisher N7a1857b005b34f91b2b7e2708630ba1b
46 schema:url https://www.nature.com/articles/s41598-018-20008-w
47 sgo:license sg:explorer/license/
48 sgo:sdDataset articles
49 rdf:type schema:ScholarlyArticle
50 N3c38588500ed46dca246f170cbe8c227 rdf:first sg:person.01217105733.78
51 rdf:rest N878671fe707a4255a059760a6ce1590e
52 N40a464d953af44b992dd1937e8d4ea27 schema:volumeNumber 8
53 rdf:type schema:PublicationVolume
54 N42b4711de655429cb74467683ebce6ac schema:name readcube_id
55 schema:value b575422c5530c5b5ca357518a08ee9fb0b0ac5fdcef28a2fc396233d2901a9b7
56 rdf:type schema:PropertyValue
57 N42da26a7934e4a7aac7014d91a93cefe rdf:first sg:person.015524121101.54
58 rdf:rest N3c38588500ed46dca246f170cbe8c227
59 N69bcaddc908f455f9f3336f75e558c5f rdf:first sg:person.0770136252.45
60 rdf:rest Ne1d535d37c3f4ce6ae2f901b98022438
61 N7a1857b005b34f91b2b7e2708630ba1b schema:name Springer Nature - SN SciGraph project
62 rdf:type schema:Organization
63 N808529cdea984842b87a2bb6a6be2d6a rdf:first sg:person.016530015130.29
64 rdf:rest N82dc05fc008943c6a2045120a52ba734
65 N82dc05fc008943c6a2045120a52ba734 rdf:first sg:person.0613066252.07
66 rdf:rest N42da26a7934e4a7aac7014d91a93cefe
67 N878671fe707a4255a059760a6ce1590e rdf:first sg:person.013601454301.39
68 rdf:rest Nfbc888c5a9f042bca68c3da79ff6c28b
69 N9e7a351e8ec342c797a558db9f728289 schema:name Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (B2PHI), Inserm, UVSQ, Institut Pasteur, Université Paris-Saclay, Paris, France
70 rdf:type schema:Organization
71 Na6fe5e81516f44d4b33b97728af3585c schema:issueNumber 1
72 rdf:type schema:PublicationIssue
73 Nb752b3e78f4d498a88a14f895d09b240 schema:name Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (B2PHI), Inserm, UVSQ, Institut Pasteur, Université Paris-Saclay, Paris, France
74 rdf:type schema:Organization
75 Nd22ffe16193042b28b0f2339451b3de3 schema:name dimensions_id
76 schema:value pub.1100570980
77 rdf:type schema:PropertyValue
78 Nd5fb0408d67d4c8dbc6bfe00cd3f05ec rdf:first sg:person.0652202333.32
79 rdf:rest N69bcaddc908f455f9f3336f75e558c5f
80 Ndf71b899f65e417c9c54b8d9210f5eae schema:name nlm_unique_id
81 schema:value 101563288
82 rdf:type schema:PropertyValue
83 Ne1d535d37c3f4ce6ae2f901b98022438 rdf:first N3a0ddb70725f4674add73dacd2cb45c6
84 rdf:rest rdf:nil
85 Nf3e87276b5a64003864445231d385ff3 schema:name doi
86 schema:value 10.1038/s41598-018-20008-w
87 rdf:type schema:PropertyValue
88 Nfaa53c7032614c3e994d9d0864fd965b schema:name pubmed_id
89 schema:value 29374222
90 rdf:type schema:PropertyValue
91 Nfbc888c5a9f042bca68c3da79ff6c28b rdf:first sg:person.01265221133.24
92 rdf:rest Nd5fb0408d67d4c8dbc6bfe00cd3f05ec
93 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
94 schema:name Medical and Health Sciences
95 rdf:type schema:DefinedTerm
96 anzsrc-for:1117 schema:inDefinedTermSet anzsrc-for:
97 schema:name Public Health and Health Services
98 rdf:type schema:DefinedTerm
99 sg:journal.1045337 schema:issn 2045-2322
100 schema:name Scientific Reports
101 rdf:type schema:Periodical
102 sg:person.01217105733.78 schema:affiliation https://www.grid.ac/institutes/grid.462844.8
103 schema:familyName Boëlle
104 schema:givenName Pierre-Yves
105 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01217105733.78
106 rdf:type schema:Person
107 sg:person.01265221133.24 schema:affiliation https://www.grid.ac/institutes/grid.12832.3a
108 schema:familyName Guillemot
109 schema:givenName Didier
110 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01265221133.24
111 rdf:type schema:Person
112 sg:person.013601454301.39 schema:affiliation https://www.grid.ac/institutes/grid.15140.31
113 schema:familyName Fleury
114 schema:givenName Eric
115 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013601454301.39
116 rdf:type schema:Person
117 sg:person.015524121101.54 schema:affiliation https://www.grid.ac/institutes/grid.15140.31
118 schema:familyName Martinet
119 schema:givenName Lucie
120 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015524121101.54
121 rdf:type schema:Person
122 sg:person.016530015130.29 schema:affiliation Nb752b3e78f4d498a88a14f895d09b240
123 schema:familyName Duval
124 schema:givenName Audrey
125 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016530015130.29
126 rdf:type schema:Person
127 sg:person.0613066252.07 schema:affiliation https://www.grid.ac/institutes/grid.428999.7
128 schema:familyName Obadia
129 schema:givenName Thomas
130 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0613066252.07
131 rdf:type schema:Person
132 sg:person.0652202333.32 schema:affiliation N9e7a351e8ec342c797a558db9f728289
133 schema:familyName Opatowski
134 schema:givenName Lulla
135 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0652202333.32
136 rdf:type schema:Person
137 sg:person.0770136252.45 schema:affiliation https://www.grid.ac/institutes/grid.428999.7
138 schema:familyName Temime
139 schema:givenName Laura
140 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0770136252.45
141 rdf:type schema:Person
142 sg:pub.10.1038/srep36301 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052028422
143 https://doi.org/10.1038/srep36301
144 rdf:type schema:CreativeWork
145 sg:pub.10.1186/1471-2334-13-185 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028759952
146 https://doi.org/10.1186/1471-2334-13-185
147 rdf:type schema:CreativeWork
148 sg:pub.10.1186/1471-2334-13-294 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047261820
149 https://doi.org/10.1186/1471-2334-13-294
150 rdf:type schema:CreativeWork
151 sg:pub.10.1186/1471-2334-14-136 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032783055
152 https://doi.org/10.1186/1471-2334-14-136
153 rdf:type schema:CreativeWork
154 sg:pub.10.1186/1741-7015-9-87 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016144881
155 https://doi.org/10.1186/1741-7015-9-87
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1017/ice.2014.53 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022798089
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1017/ice.2015.89 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010626651
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1017/ice.2016.59 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003498666
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1017/s0950268812000842 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053749697
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1073/pnas.0900974106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000151452
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1073/pnas.1009094108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020444536
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1093/infdis/jis542 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003128173
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1097/mlr.0b013e3182836dc2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004641208
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1371/journal.pcbi.1004170 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000728436
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1371/journal.pmed.0050074 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051930053
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1371/journal.pone.0017144 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047131764
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1371/journal.pone.0037893 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016988160
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1371/journal.pone.0070854 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016577092
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1371/journal.pone.0073970 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034252344
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1371/journal.pone.0087042 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025832843
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1371/journal.pone.0107878 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039713470
188 rdf:type schema:CreativeWork
189 https://www.grid.ac/institutes/grid.12832.3a schema:alternateName Versailles Saint-Quentin-en-Yvelines University
190 schema:name AP-HP, Raymond-Poincaré Hospital, Garche, France
191 INSERM 1181 Biostatistics, Biomathematics, Pharmacoepidemiology and Infectious Diseases (B2PHI), Institut Pasteur, B2PHI Paris, France
192 Université de Versailles Saint-Quentin, UMR 1181, B2PHI, Montigny-Le-Bretonneux, France
193 rdf:type schema:Organization
194 https://www.grid.ac/institutes/grid.15140.31 schema:alternateName École Normale Supérieure de Lyon
195 schema:name ENS de Lyon, DANTE/INRIA, LIP UMR CNRS 5668 Université de Lyon, Lyon, France
196 ENS de Lyon, Université de Lyon, Laboratoire de l’Informatique du Parallélisme (UMR CNRS 5668- ENS de Lyon-UCB Lyon 1), IXXI Rhône Alpes Complex Systems Institute, Lyon, France
197 rdf:type schema:Organization
198 https://www.grid.ac/institutes/grid.428999.7 schema:alternateName Institut Pasteur
199 schema:name Institut Pasteur – Bioinformatics and Biostatistics Hub – C3BI, USR 3756 IP CNRS, Paris, France
200 Laboratoire MESuRS, Conservatoire national des Arts et Métiers, Paris, France
201 Malaria Parasites & Hosts Unit, Department of Parasites & Insect Vectors, Institut Pasteur, Paris, France
202 Unité PACRI, Institut Pasteur, Conservatoire national des Arts et Métiers, Paris, France
203 rdf:type schema:Organization
204 https://www.grid.ac/institutes/grid.462844.8 schema:alternateName Sorbonne University
205 schema:name Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Institut Pierre Louis d’Epidémiologie et de Santé Publique, Paris, France
206 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...