Evidence map›Paper›PMID 29618375›Full record

ArticleParasites & vectors2018

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

Israel Ukawuba, Jeffrey Shaman

Abstract read
In one paragraph

Article in Parasites & vectors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Environmental Determinants ofThe American journal of tropical medicine and hygiene · 2020
    Article
  11. Review
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

2 authors.

Israel UkawubaMailman School of Public Health, Columbia University, 722 W 168th, New York, NY, 10032, USA. iu2140@columbia.edu.
Jeffrey ShamanMailman School of Public Health, Columbia University, 722 W 168th, New York, NY, 10032, USA.

Funding

True Metal fac coreP30ES009089 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Ami R Zota · 1998 to 2026
$44.7M
Development and Dissemination of Operational Real-Time Respiratory Virus ForecastU01GM110748 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHAMAN, JEFFREY L · 2014 to 2018
$2.6M
Interdisciplinary Training in Climate and HealthT32ES023770 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHAMAN, JEFFREY L · 2014 to 2019
$1.5M
Influenza Outbreak Prediction: Applying Data Assimilation Methodology to Make...R01GM100467 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHAMAN, JEFFREY L · 2011 to 2015
$1.4M
NIEHS NIH HHS ES009089NIEHS NIH HHS P30 ES009089NIEHS NIH HHS T32 ES023770NIGMS NIH HHS R01 GM100467NIGMS NIH HHS U01 GM110748NIH HHS GM100467NIH HHS GM110748
6 · The paper itself

Abstract

backgroundThe 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.

methodsWe 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.

resultsFindings 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.

conclusionsThe 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.

Indexed as

Meteorological ConceptsHumansModels, StatisticalRisk AssessmentTexasWest Nile FeverHumidityHydrologySoil moistureSpringSummerTemperatureTexasWest Nile virus

Identifiers

PMID29618375
PMCPMC5885460

What OpenQuestion holds

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LicenceCC BY
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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.