Evidence map›Paper›PMID 28002419›Full record

ArticlePloS one2016

Seasonality of Influenza and Respiratory Syncytial Viruses and the Effect of Climate Factors in Subtropical-Tropical Asia Using Influenza-Like Illness Surveillance Data, 2010 -2012.

Taro Kamigaki, Liling Chaw, Alvin G Tan, Raita Tamaki, Portia P Alday, Jenaline B Javier, Remigio M Olveda, Hitoshi Oshitani, Veronica L Tallo

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

22 citing papers in PubMed, 43 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Viral Respiratory Pathogens and Lung Injury.Clinical microbiology reviews · 2021
    Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. 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

9 authors at 3 institutions in 2 countries.

Taro KamigakiDepartment of Virology, Tohoku University Graduate School of Medicine, Sendai, Japan.
Liling ChawDepartment of Virology, Tohoku University Graduate School of Medicine, Sendai, Japan.
Alvin G TanDepartment of Epidemiology and Biostatistics, Research Institute for Tropical Medicine, Department of Health, Manila, Philippines.
Raita TamakiDepartment of Virology, Tohoku University Graduate School of Medicine, Sendai, Japan.
Portia P AldayDepartment of Epidemiology and Biostatistics, Research Institute for Tropical Medicine, Department of Health, Manila, Philippines.
Jenaline B JavierDepartment of Epidemiology and Biostatistics, Research Institute for Tropical Medicine, Department of Health, Manila, Philippines.
Remigio M OlvedaResearch Institute for Tropical Medicine, Department of Health, Manila, Philippines.
Hitoshi OshitaniDepartment of Virology, Tohoku University Graduate School of Medicine, Sendai, Japan.
Veronica L TalloDepartment of Epidemiology and Biostatistics, Research Institute for Tropical Medicine, Department of Health, Manila, Philippines.
Tohoku University · JPDepartment of Health · PHResearch Institute for Tropical Medicine · PH

Funding

NCIRD CDC HHS U51 IP000335
6 · The paper itself

Abstract

introductionThe seasonality of influenza and respiratory syncytial virus (RSV) is well known, and many analyses have been conducted in temperate countries; however, this is still not well understood in tropical countries. Previous studies suggest that climate factors are involved in the seasonality of these viruses. However, the extent of the effect of each climate variable is yet to be defined. MATERIALS AND

methodsWe investigated the pattern of seasonality and the effect of climate variables on influenza and RSV at three sites of different latitudes: the Eastern Visayas region and Baguio City in the Philippines, and Okinawa Prefecture in Japan. Wavelet analysis and the dynamic linear regression model were applied. Climate variables used in the analysis included mean temperature, relative and specific humidity, precipitation, and number of rainy days. The Akaike Information Criterion estimated in each model was used to test the improvement of fit in comparison with the baseline model.

resultsAt all three study sites, annual seasonal peaks were observed in influenza A and RSV; peaks were unclear for influenza B. Ranges of climate variables at the two Philippine sites were narrower and mean variables were significantly different among the three sites. Whereas all climate variables except the number of rainy days improved model fit to the local trend model, their contributions were modest. Mean temperature and specific humidity were positively associated with influenza and RSV at the Philippine sites and negatively associated with influenza A in Okinawa. Precipitation also improved model fit for influenza and RSV at both Philippine sites, except for the influenza A model in the Eastern Visayas.

conclusionsAnnual seasonal peaks were observed for influenza A and RSV but were less clear for influenza B at all three study sites. Including additional data from subsequent more years would help to ascertain these findings. Annual amplitude and variation in climate variables are more important than their absolute values for determining their effect on the seasonality of influenza and RSV.

Indexed as

Tropical ClimateHumansHumidityInfluenza, HumanJapanLinear ModelsPhilippinesRainRespiratory Syncytial Virus InfectionsRisk FactorsSeasonsTemperatureWavelet Analysis

Identifiers

PMID28002419
PMCPMC5176282
OpenAlexW2570210796

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.