Evidence map›Paper›PMID 23552375›Full record

ArticleAnnals of internal medicine2013

GeoSentinel surveillance of illness in returned travelers, 2007-2011.

Karin Leder, Joseph Torresi, Michael D Libman, Jakob P Cramer, Francesco Castelli, Patricia Schlagenhauf, Annelies Wilder-Smith, Mary E Wilson, Jay S Keystone, Eli Schwartz and 8 more

Open access · greenAbstract read
In one paragraph

Article in Annals of internal medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 190 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
190citing papers in PubMed, 5 pooled it
53.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

190 citing papers in PubMed, 5 syntheses or guidelines pooled it, 481 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  4. Pooled it
  5. Pooled it
  6. Trial
  7. Article
  8. Review
  9. Article
  10. Increase in imported mupirocin-resistantNew microbes and new infections · 2026
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
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  18. Cutaneous larva migrans in Canadian travellers returning from the Caribbean: A 10-year surveillance analysis from CanTravNet.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2025
    Article
  19. Article
  20. Fascioliasis acquired in Central Asia.Journal of travel medicine · 2025
    Article

130 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors at 6 institutions in 7 countries.

Karin LederVictorian Infectious Disease Service, Royal Melbourne Hospital, Monash University, Austin Hospital, Melbourne University. karin.leder@monash.edu
Joseph Torresi
Michael D Libman
Jakob P Cramer
Francesco Castelli
Patricia Schlagenhauf
Annelies Wilder-Smith
Mary E Wilson
Jay S Keystone
Eli Schwartz
Elizabeth D Barnett
Frank von Sonnenburg
John S Brownstein
Allen C Cheng
Mark J Sotir
Douglas H Esposito
David O Freedman
GeoSentinel Surveillance Network
Heidelberg University · DEUniversity Hospital Heidelberg · DEUniversity Medical Center Hamburg-Eppendorf · DEAustin Hospital · AUToronto General Hospital · CAUniversität Hamburg · DE

Funding

The Global Surveillance Network of ISTM and CDCU50CI000359 · CI · INTERNATIONAL SOCIETY OF TRAVEL MEDICINE · PI FREEDMAN, DAVID O · 2006 to 2010
$3.2M
Intramural CDC HHS CC999999Medical Research Council G0701652NCPDCID CDC HHS 5U50CI000359NCPDCID CDC HHS U50 CI000359
6 · The paper itself

Abstract

backgroundInternational travel continues to increase, particularly to Asia and Africa. Clinicians are increasingly likely to be consulted for advice before travel or by ill returned travelers.

objectiveTo describe typical diseases in returned travelers according to region, travel reason, and patient demographic characteristics; describe the pattern of low-frequency travel-associated diseases; and refine key messages for care before and after travel.

designDescriptive, using GeoSentinel records.

setting53 tropical or travel disease units in 24 countries. PATIENTS: 42 173 ill returned travelers seen between 2007 and 2011. MEASUREMENTS: Frequencies of demographic characteristics, regions visited, and illnesses reported.

resultsAsia (32.6%) and sub-Saharan Africa (26.7%) were the most common regions where illnesses were acquired. Three quarters of travel-related illness was due to gastrointestinal (34.0%), febrile (23.3%), and dermatologic (19.5%) diseases. Only 40.5% of all ill travelers reported pretravel medical visits. The relative frequency of many diseases varied with both travel destination and reason for travel, with travelers visiting friends and relatives in their country of origin having both a disproportionately high burden of serious febrile illness and very low rates of advice before travel (18.3%). Life-threatening diseases, such as Plasmodium falciparum malaria, melioidosis, and African trypanosomiasis, were reported. LIMITATIONS: Sentinel surveillance data collected by specialist clinics do not reflect healthy returning travelers or those with mild or self-limited illness. Data cannot be used to infer quantitative risk for illness.

conclusionMany illnesses may have been preventable with appropriate advice, chemoprophylaxis, or vaccination. Clinicians can use these 5-year GeoSentinel data to help tailor more efficient pretravel preparation strategies and evaluate possible differential diagnoses of ill returned travelers according to destination and reason for travel. PRIMARY FUNDING SOURCE: Centers for Disease Control and Prevention.

Indexed as

Sentinel SurveillanceTravelAdolescentAdultAfrica South of the SaharaAgedAged, 80 and overAsiaCaribbean RegionChildChild, PreschoolFeverGastrointestinal DiseasesHumansInfantInfections

Identifiers

PMID23552375
PMCPMC4629801
OpenAlexW2108375849

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.