Evidence map›Paper›PMID 36078811›Full record

ArticleInternational journal of environmental research and public health2022

Risk Factors Associated with Passengers with Imported Dengue Fever at International Airports in Taiwan.

Ying-Yun Wang, Pei-Kwei Tsay

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 84% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 1 institution in 1 country.

Ying-Yun WangGraduate Institute of Clinical Medical Sciences, Chang Gung University, Taoyuan 333, Taiwan.
Pei-Kwei TsayDepartment of Public Health and Center of Biostatistics, College of Medicine, Chang Gung University, Taoyuan 333, Taiwan.ORCID 0000-0003-1749-1419
Chang Gung University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dengue fever (DF) is a mosquito-borne disease prevalent in the tropics (e.g., sub-Saharan Africa, Asia, and Central and South America) and a common cause of febrile illness in travelers. The high incidence of imported DF in Taiwan has led to a domestic outbreak. This study explored the risk factors associated with individuals given diagnoses of imported DF at international airports in Taiwan. The results may serve as a reference for DF prevention. In this retrospective study, data from the symptom notification system database of the Taiwan Centers for Disease Control (TCDC) were used. These data concerned travelers who returned to Taiwan from DF-endemic areas with suspected DF symptoms. The epidemiological characteristics of the cases were analyzed, and 28 variables related to DF infection were included in the multivariate logistic regression analysis. In 2018-2019, there were 8656 cases (451 positive and 8205 negative cases). The results revealed DF symptoms and a 16-30-day stay in endemic areas to be independent risk factors and the presence of three respiratory symptoms and <10 days of short-term travel to be protective factors. These results may enable the accurate assessment of symptoms in travelers with DF as well as the risk factors associated with imported DF, lowering the risk of indigenous DF outbreaks caused by imported DF.

Indexed as

AirportsDengueAnimalsHumansRetrospective StudiesRisk FactorsTaiwanTravelimported dengue feverquarantinerisk factor

Identifiers

PMID36078811
PMCPMC9517761
OpenAlexW4294739979

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.