Evidence map›Paper›PMID 33825903›Full record

ArticleJournal of medical entomology2021

Environmental Correlates of Lyme Disease Emergence in Southwest Virginia, 2005-2014.

Paul M Lantos, Jean Tsao, Mark Janko, Ali Arab, Michael E von Fricken, Paul G Auwaerter, Lise E Nigrovic, Vance Fowler, Felicia Ruffin, David Gaines and 2 more

Abstract read
In one paragraph

Article in Journal of medical entomology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  6. Review
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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

12 authors.

Paul M LantosDepartments of Medicine, Pediatrics, Community and Family Medicine, and Global Health, Duke University, Durham, NC.ORCID 0000-0003-2339-1481
Jean TsaoDepartment of Fisheries and Wildlife, Michigan State University, Lansing, MI.ORCID 0000-0001-6641-7931
Mark JankoInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA.
Ali ArabDepartment of Mathematics and Statistics, Georgetown University, Washington, DC.
Michael E von FrickenDepartment of Global and Community Health, George Mason University, Fairfax, VA.ORCID 0000-0003-2938-4549
Paul G AuwaerterDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD.
Lise E NigrovicDepartment of Emergency Medicine, Boston Children's Hospital, Boston, MA.
Vance FowlerDepartment of Medicine, Duke University, Durham, NC.
Felicia RuffinDepartment of Medicine, Duke University, Durham, NC.
David GainesOffice of Epidemiology, Virginia Department of Health, Richmond, VA.
James BroyhillOffice of Epidemiology, Virginia Department of Health, Richmond, VA.
Jennifer SwensonNicholas School of the Environment, Duke University, Durham, NC.

Funding

Duke CTSA (Composite)KL2TR001115 · NCATS · DUKE UNIVERSITY · PI BOULWARE, LEIGH E, KRAFT, MONICA · 2013 to 2017
$5.1M
NCATS NIH HHS KL2 TR001115
6 · The paper itself

Abstract

Lyme disease is the most common tick-borne disease in North America. Though human infection is mostly transmitted in a limited geography, the range has expanded in recent years. One notable area of recent expansion is in the mountainous region of southwestern Virginia. The ecological factors that facilitate or constrain the range of human Lyme disease in this region remain uncertain. To evaluate this further, we obtained ecological data, including remotely sensed data on forest structure and vegetation, weather data, and elevation. These data were aggregated within the census block groups of a 9,153 km2 area around the cities of Blacksburg and Roanoke, VA, an area with heterogeneous Lyme disease transmission. In this geographic area, 755 individuals were reported to have Lyme disease in the 10 yr from 2006 to 2015, and these cases were aggregated by block group. A zero-inflated negative binomial model was used to evaluate which environmental variables influenced the abundance of Lyme disease cases. Higher elevation and higher vegetation density had the greatest effect size on the abundance of Lyme disease. Measures of forest edge, forest integrity, temperature, and humidity were not associated with Lyme disease cases. Future southward expansion of Lyme disease into the southeastern states may be most likely in ecologically similar mountainous areas.

Indexed as

EnvironmentCommunicable Diseases, EmergingCross-Sectional StudiesHumansLyme DiseaseRetrospective StudiesVirginiaBayesian statisticsepidemiologygeographic information systemLyme diseaseremote sensing

Identifiers

PMID33825903
PMCPMC8285012

What OpenQuestion holds

Textmetadata
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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.