Evidence map›Paper›PMID 31608405›Full record

ArticleJournal of travel medicine2019

Imported dengue in Spain: a nationwide analysis with predictive time series analyses.

Lidia Redondo-Bravo, Claudia Ruiz-Huerta, Diana Gomez-Barroso, María José Sierra-Moros, Agustín Benito, Zaida Herrador

Abstract read
In one paragraph

Article in Journal of travel medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

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

  1. Pooled it
  2. Article
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  5. Article
  6. Article
  7. Observational
  8. Dengue Epidemiology in Qatar from 2013-2021: A Retrospective Study.Tropical medicine and infectious disease · 2022
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. What Is the Impact of Lockdowns on Dengue?Current infectious disease reports · 2021
    Review
  15. Epidemiological and clinical analysis of the outbreak of dengue fever in Zhangshu City, Jiangxi Province, in 2019.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2021
    Article
  16. Article
  17. Article
  18. Review
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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

6 authors.

Lidia Redondo-BravoServicio de Medicina Preventiva, Hospital Universitario la Paz, Madrid, Spain.
Claudia Ruiz-HuertaServicio de Medicina Preventiva, Hospital Universitario de la Cruz Roja, Madrid, Spain.
Diana Gomez-BarrosoCentro Nacional de Epidemiología, Instituto de Salud Carlos III (ISCIII in Spanish), Madrid, Spain.
María José Sierra-MorosCentro de Coordinación de Alertas y Emergencias Sanitarias, Dirección General de Salud Pública, Calidad e Innovación, Ministerio de Sanidad, Consumo y Bienestar Social, Madrid, Spain.
Agustín BenitoCentro Nacional de Medicina Tropical, Instituto de Salud Carlos III (ISCIII in Spanish), Madrid, Spain.
Zaida HerradorCentro Nacional de Medicina Tropical, Instituto de Salud Carlos III (ISCIII in Spanish), Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOf febrile illnesses in Europe, dengue is second only to malaria as a cause of travellers being hospitalized. Local transmission has been reported in several European countries, including Spain. This study assesses the evolution of dengue-related admissions in Spain in terms of time, geographical distribution and individuals' common characteristics; it also creates a predictive model to evaluate the risk of local transmission.

methodsThis is a retrospective study using the Hospital Discharge Records Database from 1997 to 2016. We calculated hospitalization rates and described clinical characteristics. Spatial distribution and temporal behaviour were also assessed, and a predictive time series model was created to estimate expected cases in the near future. Figures for resident foreign population, Spanish residents' trips to endemic regions and the expansion of Aedes albopictus were also evaluated.

resultsA total of 588 dengue-related admissions were recorded: 49.6% were women, and the mean age was 34.3 years. One person died (0.2%), 82% presented with mild-to-moderate dengue and 7-8% with severe dengue. We observed a trend of steady and consistent increase in incidence (P < 0.05), in parallel with the increase in trips to dengue-endemic regions. Most admissions occurred during the summer, showing significant seasonality with 3-year peaks. We also found important regional differences. According to the predictive time series analysis, a continuing increase in imported dengue incidence can be expected in the near future, which, in the worst case scenario (upper 95% confidence interval), would mean an increase of 65% by 2025.

conclusionWe present a nationwide study based on hospital, immigration, travel and entomological data. The constant increase in dengue-related hospitalizations, in combination with wider vector distribution, could imply a higher risk of autochthonous dengue transmission in the years to come. Strengthening the human and vector surveillance systems is a necessity, as are improvements in control measures, in the education of the general public and in fostering their collaboration in order to reduce the impact of imported dengue and to prevent the occurrence of autochthonous cases.

Indexed as

AdolescentAdultAgedAnimalsChildChild, PreschoolCommunicable Diseases, ImportedDatabases, FactualDengueFemaleHospitalizationHumansIncidenceInfantInfant, NewbornLinear ModelsDengueepidemiologyhospitalizationimported diseasesSpain

Identifiers

PMID31608405
PMCPMC6927315

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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.