Evidence map›Paper›PMID 29573157›Full record

ArticleInfluenza and other respiratory viruses2018

Dynamics of influenza in tropical Africa: Temperature, humidity, and co-circulating (sub)types.

Wan Yang, Matthew J Cummings, Barnabas Bakamutumaho, John Kayiwa, Nicholas Owor, Barbara Namagambo, Timothy Byaruhanga, Julius J Lutwama, Max R O'Donnell, Jeffrey Shaman

Abstract read
In one paragraph

Article in Influenza and other respiratory viruses, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Observational
  5. Article
  6. Article
  7. Short-term impact of ambient temperature on the incidence of influenza in Wuhan, China.Environmental science and pollution research international · 2022
    Article
  8. Associations between Temperature and Influenza Activity: A National Time Series Study in China.International journal of environmental research and public health · 2021
    Article
  9. Article
  10. Observational
  11. Article
  12. Article
  13. Review
  14. Observational
  15. Transmission-dynamics models for the SARS Coronavirus-2.American journal of human biology : the official journal of the Human Biology Council · 2020
    Review
  16. Article
  17. Review
  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

10 authors.

Wan YangDepartment of Environmental Health Sciences, Columbia University, New York, NY, USA.ORCID 0000-0002-7555-9728
Matthew J CummingsDivision of Pulmonary, Allergy, and Critical Care Medicine, Columbia University, New York, NY, USA.
Barnabas BakamutumahoNational Influenza Center, Uganda Virus Research Institute, Entebbe, Uganda.
John KayiwaNational Influenza Center, Uganda Virus Research Institute, Entebbe, Uganda.
Nicholas OworNational Influenza Center, Uganda Virus Research Institute, Entebbe, Uganda.
Barbara NamagamboNational Influenza Center, Uganda Virus Research Institute, Entebbe, Uganda.
Timothy ByaruhangaNational Influenza Center, Uganda Virus Research Institute, Entebbe, Uganda.
Julius J LutwamaNational Influenza Center, Uganda Virus Research Institute, Entebbe, Uganda.
Max R O'DonnellDivision of Pulmonary, Allergy, and Critical Care Medicine, Columbia University, New York, NY, USA.
Jeffrey ShamanDepartment of Environmental Health Sciences, Columbia University, New York, NY, USA.

Funding

True Metal fac coreP30ES009089 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MATTHEW S PERZANOWSKI · 1998 to 2026
$44.7M
Clinical and Translational Science AwardUL1TR000040 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2012 to 2015
$26.2M
Development and Dissemination of Operational Real-Time Respiratory Virus ForecastU01GM110748 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHAMAN, JEFFREY L · 2014 to 2018
$2.6M
Influenza Outbreak Prediction: Applying Data Assimilation Methodology to Make...R01GM100467 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHAMAN, JEFFREY L · 2011 to 2015
$1.4M
Biomarker for XDR-TB Treatment Response and Drug Resistance in HIV Endemic AreaK23AI098479 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI O'DONNELL, MAX · 2012 to 2016
$669k
NCATS NIH HHS UL1 TR000040NIAID NIH HHS K23 AI098479NIEHS NIH HHS P30 ES009089NIGMS NIH HHS R01 GM100467NIGMS NIH HHS U01 GM110748
6 · The paper itself

Abstract

backgroundThe association of influenza with meteorological variables in tropical climates remains controversial. Here, we investigate the impact of weather conditions on influenza in the tropics and factors that may contribute to this uncertainty.

methodsWe computed the monthly viral positive rate for each of the 3 circulating influenza (sub)types (ie, A/H1N1, A/H3N2, and B) among patients presenting with influenza-like illness (ILI) or severe acute respiratory infections (SARI) in 2 Ugandan cities (Entebbe and Kampala). Using this measure as a proxy for influenza activity, we applied regression models to examine the impact of temperature, relative humidity, absolute humidity, and precipitation, as well as interactions among the 3 influenza viruses on the epidemic dynamics of each influenza (sub)type. A full analysis including all 4 weather variables was done for Entebbe during 2007-2015, and a partial analysis including only temperature and precipitation was done for both cities during 2008-2014.

resultsFor Entebbe, the associations with weather variables differed by influenza (sub)type; with adjustment for viral interactions, the models showed that precipitation and temperature were negatively correlated with A/H1N1 activity, but not for A/H3N2 or B. A mutually negative association between A/H3N2 and B activity was identified in both Entebbe and Kampala.

conclusionOur findings suggest that key interactions exist among influenza (sub)types at the population level in the tropics and that such interactions can modify the association of influenza activity with weather variables. Studies of the relationship between influenza and weather conditions should therefore determine and account for co-circulating influenza (sub)types.

Indexed as

Influenza A Virus, H1N1 SubtypeInfluenza A Virus, H3N2 SubtypeInfluenza B virusWeatherHumansHumidityInfluenza, HumanTemperatureUgandaAfricahumidityinfluenzaintertypic interactionstemperaturetropical climateUganda

Identifiers

PMID29573157
PMCPMC6005592

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.