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Association of spring-summer hydrology and meteorology with human West Nile virus infection in West Texas, USA, 2002–2016

Overview of attention for article published in Parasites & Vectors, April 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

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1 news outlet
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3 X users

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36 Mendeley
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Title
Association of spring-summer hydrology and meteorology with human West Nile virus infection in West Texas, USA, 2002–2016
Published in
Parasites & Vectors, April 2018
DOI 10.1186/s13071-018-2781-0
Pubmed ID
Authors

Israel Ukawuba, Jeffrey Shaman

Abstract

The emergence of West Nile virus (WNV) in the Western Hemisphere has motivated research into the processes contributing to the incidence and persistence of the disease in the region. Meteorology and hydrology are fundamental determinants of vector-borne disease transmission dynamics of a region. The availability of water influences the population dynamics of vector and host, while temperature impacts vector growth rates, feeding habits, and disease transmission potential. Characterization of the temporal pattern of environmental factors influencing WNV risk is crucial to broaden our understanding of local transmission dynamics and to inform efforts of control and surveillance. We used hydrologic, meteorological and WNV data from west Texas (2002-2016) to analyze the relationship between environmental conditions and annual human WNV infection. A Bayesian model averaging framework was used to evaluate the association of monthly environmental conditions with WNV infection. Findings indicate that wet conditions in the spring combined with dry and cool conditions in the summer are associated with increased annual WNV cases. Bayesian multi-model inference reveals monthly means of soil moisture, specific humidity and temperature to be the most important variables among predictors tested. Environmental conditions in March, June, July and August were the leading predictors in the best-fitting models. The results significantly link soil moisture and temperature in the spring and summer to WNV transmission risk. Wet spring in association with dry and cool summer was the temporal pattern best-describing WNV, regardless of year. Our findings also highlight that soil moisture may be a stronger predictor of annual WNV transmission than rainfall.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 19%
Student > Ph. D. Student 6 17%
Student > Master 5 14%
Student > Bachelor 2 6%
Student > Doctoral Student 1 3%
Other 2 6%
Unknown 13 36%
Readers by discipline Count As %
Environmental Science 7 19%
Agricultural and Biological Sciences 3 8%
Nursing and Health Professions 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Biochemistry, Genetics and Molecular Biology 1 3%
Other 6 17%
Unknown 16 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 June 2018.
All research outputs
#4,160,353
of 23,041,514 outputs
Outputs from Parasites & Vectors
#915
of 5,509 outputs
Outputs of similar age
#82,455
of 329,124 outputs
Outputs of similar age from Parasites & Vectors
#40
of 187 outputs
Altmetric has tracked 23,041,514 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,509 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has done well, scoring higher than 83% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,124 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 187 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.