Evidence map›Paper›PMID 22687530›Full record

ArticleEpidemiology and infection2013

Meteorological conditions and incidence of Legionnaires' disease in Glasgow, Scotland: application of statistical modelling.

C E Dunn, B Rowlingson, R S Bhopal, P Diggle

Abstract read
In one paragraph

Article in Epidemiology and infection, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Legionella pneumophila Risk from Cooling Tower Systems in China.Applied and environmental microbiology · 2022
    Article
  5. Article
  6. The Impact of Storms onFrontiers in microbiology · 2020
    Article
  7. Article
  8. Article
  9. Article
  10. Legionnaire's disease, weather and climate.Bulletin of the World Health Organization · 2015
    Article
  11. Article
  12. Article
  13. 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

4 authors.

C E DunnDepartment of Geography, Durham University, Durham, UK. C.E.Dunn@durham.ac.uk
B Rowlingson
R S Bhopal
P Diggle

Funding

Medical Research Council G0902153
6 · The paper itself

Abstract

This study investigated the relationships between Legionnaires' disease (LD) incidence and weather in Glasgow, UK, by using advanced statistical methods. Using daily meteorological data and 78 LD cases with known exact date of onset, we fitted a series of Poisson log-linear regression models with explanatory variables for air temperature, relative humidity, wind speed and year, and sine-cosine terms for within-year seasonal variation. Our initial model showed an association between LD incidence and 2-day lagged humidity (positive, P = 0·0236) and wind speed (negative, P = 0·033). However, after adjusting for year-by-year and seasonal variation in cases there were no significant associations with weather. We also used normal linear models to assess the importance of short-term, unseasonable weather values. The most significant association was between LD incidence and air temperature residual lagged by 1 day prior to onset (P = 0·0014). The contextual role of unseasonably high air temperatures is worthy of further investigation. Our methods and results have further advanced understanding of the role which weather plays in risk of LD infection.

Indexed as

Linear ModelsWeatherAdultAgedAged, 80 and overFemaleHumansHumidityIncidenceLegionnaires' DiseaseMaleMiddle AgedScotlandSeasonsTemperatureWind

Identifiers

PMID22687530
PMCPMC9151842

What OpenQuestion holds

Textmetadata
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.