Evidence map›Paper›PMID 25695520›Full record

ArticleeLife2015

Effectiveness of traveller screening for emerging pathogens is shaped by epidemiology and natural history of infection.

Katelyn M Gostic, Adam J Kucharski, James O Lloyd-Smith

Abstract read
In one paragraph

Article in eLife, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Review
  6. Observational
  7. Article
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  9. Review
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  15. Strategies for radiology departments in handling the COVID-19 pandemic.Diagnostic and interventional radiology (Ankara, Turkey) · 2020
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  18. Challenges of SARS-CoV-2 and lessons learnt from SARS in Guangdong Province, China.Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology · 2020
    Article
  19. The 2019 coronavirus: Learning curves, lessons, and the weakest link.International journal of clinical practice · 2020
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Katelyn M GosticDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, United States.
Adam J KucharskiCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Tropical Hygiene and Medicine, London, United Kingdom.
James O Lloyd-SmithDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, United States.

Funding

Systems in Integrative BiologyT32GM008185 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CHOU, TOM · 1987 to 2022
$4.6M
Medical Research Council MR/K021524/1NIGMS NIH HHS T32 GM008185NIGMS NIH HHS T32-GM008185
6 · The paper itself

Abstract

During outbreaks of high-consequence pathogens, airport screening programs have been deployed to curtail geographic spread of infection. The effectiveness of screening depends on several factors, including pathogen natural history and epidemiology, human behavior, and characteristics of the source epidemic. We developed a mathematical model to understand how these factors combine to influence screening outcomes. We analyzed screening programs for six emerging pathogens in the early and late stages of an epidemic. We show that the effectiveness of different screening tools depends strongly on pathogen natural history and epidemiological features, as well as human factors in implementation and compliance. For pathogens with longer incubation periods, exposure risk detection dominates in growing epidemics, while fever becomes a better target in stable or declining epidemics. For pathogens with short incubation, fever screening drives detection in any epidemic stage. However, even in the most optimistic scenario arrival screening will miss the majority of cases.

Indexed as

TravelDisease OutbreaksHumansModels, Theoreticalecologyemerging diseasesentry screeningepidemiologyfever screeningglobal healthincubation periodpathogen natural historyviruses

Identifiers

PMID25695520
PMCPMC4337724

What OpenQuestion holds

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LicenceCC BY
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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.