Evidence map›Paper›PMID 31059505›Full record

ArticlePLoS neglected tropical diseases2019

Seasonal patterns of dengue fever in rural Ecuador: 2009-2016.

Rachel Sippy, Diego Herrera, David Gaus, Ronald E Gangnon, Jonathan A Patz, Jorge E Osorio

Open access · goldAbstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
6.2field-weighted citation impact, top 4% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Dengue, chikungunya, and Zika virus infections in Latin America and the Caribbean: a systematic review.Revista panamericana de salud publica = Pan American journal of public health · 2023
    Review
  8. Review
  9. Article
  10. Epidemiology of dengue fever in Guatemala.PLoS neglected tropical diseases · 2020
    Article
  11. 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

6 authors at 1 institution in 1 country.

Rachel SippyDepartment of Population Health Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.ORCID 0000-0003-3617-2093
Diego HerreraSalud y Desarrollo Andino, Pedro Vicente Maldonado, Pichincha, Ecuador.
David GausSalud y Desarrollo Andino, Pedro Vicente Maldonado, Pichincha, Ecuador.
Ronald E GangnonDepartment of Population Health Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Jonathan A PatzDepartment of Population Health Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Jorge E OsorioDepartment of Pathobiological Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.ORCID 0000-0002-7474-6150
University of Wisconsin–Madison · US

Funding

Research Training in Complementary and Alternative MedicineT32AT006956 · NCCIH · UNIVERSITY OF WISCONSIN-MADISON · PI BARRETT, BRUCE P · 2011 to 2017
$1.5M
NCCIH NIH HHS T32 AT006956
6 · The paper itself

Abstract

Season is a major determinant of infectious disease rates, including arboviruses spread by mosquitoes, such as dengue, chikungunya, and Zika. Seasonal patterns of disease are driven by a combination of climatic or environmental factors, such as temperature or rainfall, and human behavioral time trends, such as school year schedules, holidays, and weekday-weekend patterns. These factors affect both disease rates and healthcare-seeking behavior. Seasonality of dengue fever has been studied in the context of climatic factors, but short- and long-term time trends are less well-understood. With 2009-2016 medical record data from patients diagnosed with dengue fever at two hospitals in rural Ecuador, we used Poisson generalized linear modeling to determine short- and long-term seasonal patterns of dengue fever, as well as the effect of day of the week and public holidays. In a subset analysis, we determined the impact of school schedules on school-aged children. With a separate model, we examined the effect of climate on diagnosis patterns. In the first model, the most important predictors of dengue fever were annual sinusoidal fluctuations in disease, long-term trends (as represented by a spline for the full study duration), day of the week, and hospital. Seasonal trends showed single peaks in case diagnoses, during mid-March. Compared to the average of all days, cases were more likely to be diagnosed on Tuesdays (risk ratio (RR): 1.26, 95% confidence interval (CI) 1.05-1.51) and Thursdays (RR: 1.25, 95% CI 1.02-1.53), and less likely to be diagnosed on Saturdays (RR: 0.81, 95% CI 0.65-1.01) and Sundays (RR: 0.74, 95% CI 0.58-0.95). Public holidays were not significant predictors of dengue fever diagnoses, except for an increase in diagnoses on the day after Christmas (RR: 2.77, 95% CI 1.46-5.24). School schedules did not impact dengue diagnoses in school-aged children. In the climate model, important climate variables included the monthly total precipitation, an interaction between total precipitation and monthly absolute minimum temperature, an interaction between total precipitation and monthly precipitation days, and a three-way interaction between minimum temperature, total precipitation, and precipitation days. This is the first report of long-term dengue fever seasonality in Ecuador, one of few reports from rural patients, and one of very few studies utilizing daily disease reports. These results can inform local disease prevention efforts, public health planning, as well as global and regional models of dengue fever trends.

Indexed as

AdolescentChildChild, PreschoolDengueEcuadorFemaleHumansMaleRisk FactorsRural PopulationSeasons

Identifiers

PMID31059505
PMCPMC6522062
OpenAlexW2898416139

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.