Evidence map›Paper›PMID 19943935›Full record

ArticleInternational journal of health geographics2009

Risk factors for human infection with West Nile Virus in Connecticut: a multi-year analysis.

Ann Liu, Vivian Lee, Deron Galusha, Martin D Slade, Maria Diuk-Wasser, Theodore Andreadis, Matthew Scotch, Peter M Rabinowitz

Abstract read
In one paragraph

Article in International journal of health geographics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–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

27 citing papers in PubMed.

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  17. Climate change impacts on West Nile virus transmission in a global context.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2015
    Review
  18. Environmental predictors of West Nile fever risk in Europe.International journal of health geographics · 2014
    Article
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  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

8 authors.

Ann LiuYale Center for Medical Informatics, Yale University School of Medicine, New Haven, CT, USA. aliu@jhsph.edu
Vivian Lee
Deron Galusha
Martin D Slade
Maria Diuk-Wasser
Theodore Andreadis
Matthew Scotch
Peter M Rabinowitz

Funding

Informatics for zoonotic disease surveillance: combining animal and human dataK99LM009825 · NLM · YALE UNIVERSITY · PI SCOTCH, MATTHEW · 2008 to 2010
$230k
NLM NIH HHS K99 LM009825
6 · The paper itself

Abstract

backgroundThe optimal method for early prediction of human West Nile virus (WNV) infection risk remains controversial. We analyzed the predictive utility of risk factor data for human WNV over a six-year period in Connecticut. RESULTS AND DISCUSSION: Using only environmental variables or animal sentinel data was less predictive than a model that considered all variables. In the final parsimonious model, population density, growing degree-days, temperature, WNV positive mosquitoes, dead birds and WNV positive birds were significant predictors of human infection risk, with an ROC value of 0.75.

conclusionA real-time model using climate, land use, and animal surveillance data to predict WNV risk appears feasible. The dynamic patterns of WNV infection suggest a need to periodically refine such prediction systems.

methodsUsing multiple logistic regression, the 30-day risk of human WNV infection by town was modeled using environmental variables as well as mosquito and wild bird surveillance.

Indexed as

Population DensityWest Nile virusAgricultureClimateConnecticutFemaleHumansLogistic ModelsMaleModels, TheoreticalReproducibility of ResultsRisk AssessmentRisk FactorsWest Nile Fever

Identifiers

PMID19943935
PMCPMC2788533

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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.