Evidence map›Paper›PMID 37610812›Full record

ArticleJMIR public health and surveillance2023

Improving Surveillance of Human Tick-Borne Disease Risks: Spatial Analysis Using Multimodal Databases.

Sarah P Maxwell, Chris Brooks, Dohyeong Kim, Connie L McNeely, Seonga Cho, Kevin C Thomas

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.1field-weighted citation impact, top 9% of its field
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

10 citing papers in PubMed, 11 citations in OpenAlex.

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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

6 authors at 4 institutions in 1 country.

Sarah P MaxwellSchool of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, TX, United States.ORCID 0000-0003-2452-6114
Chris BrooksLaboratory for Human Neurobiology, Boston University School of Medicine, Boston, MA, United States.ORCID 0000-0002-9511-5390
Dohyeong KimSchool of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, TX, United States.ORCID 0000-0002-1428-1451
Connie L McNeelySchar School of Policy and Government, George Mason University, Fairfax, VA, United States.ORCID 0000-0002-4292-8195
Seonga ChoDepartment of Geography, University of California, Santa Barbara, Santa Barbara, CA, United States.ORCID 0000-0003-4626-2957
Kevin C ThomasLaboratory for Human Neurobiology, Boston University School of Medicine, Boston, MA, United States.ORCID 0000-0003-3463-5832
Boston University · USThe University of Texas at Dallas · USGeorge Mason University · USUniversity of California, Santa Barbara · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe extent of tick-borne disease (TBD) risk in the United States is generally unknown. Active surveillance using entomological measures, such as presence and density of infected nymphal Ixodes scapularis ticks, have served as indicators for assessing human risk, but results have been inconsistent and passive surveillance via public health systems suggests TBDs are underreported.

objectiveResearch using various data sources and collection methods (eg, Google Trends, apps, and tick bite encounters [TBEs] reports) has shown promise for assessing human TBD risk. In that vein, and engaging a One Health perspective, this study used multimodal databases, geographically overlaying patient survey data on TBEs and concomitant reports of TBDs with data drawn from other sources, such as canine serological reports, to glean insights and to determine and assess the use of various indicators as proxies for human TBD risk.

methodsThis study used a mixed methods research strategy, relying on triangulation techniques and drawing on multiple data sources to provide insights into various aspects of human disease risk from TBEs and TBDs in the United States. A web-based survey was conducted over a 15-month period beginning in December 2020 to collect data on TBEs. To maximize the value of the covariate data, related analyses included TBE reports that occurred in the United States between January 1, 2000, and March 31, 2021. TBEs among patients diagnosed with Lyme disease were analyzed at the county level and compared to I scapularis and I pacificus tick presence, human cases identified by the Centers for Disease Control and Prevention (CDC), and canine serological data. Spatial analyses employed multilayer thematic mapping and other techniques.

resultsAfter cleaning, survey results showed a total of 249 (75.7%) TBEs spread across 148 respondents (61.9% of all respondents, 81.7% of TBE-positive respondents); 144 (4.7%) counties in 30 states (60%) remained eligible for analysis, with an average of 1.68 (SD 1.00) and median of 1 (IQR 1) TBEs per respondent. Analysis revealed significant spatial matching at the county level among patient survey reports of TBEs and disease risk indicators from the CDC and other official sources. Thematic mapping results included one-for-one county-level matching of reported TBEs with at least 1 designated source of human disease risk (ie, positive canine serological tests, CDC-reported Lyme disease, or known tick presence).

conclusionsUse of triangulation methods to integrate patient data on TBE recall with established canine serological reports, tick presence, and official human TBD information offers more granular, county-level information regarding TBD risk to inform clinicians and public health officials. Such data may supplement public health sources to offer improved surveillance and provide bases for developing robust proxies for TBD risk among humans.

Indexed as

Lyme DiseaseTick-Borne DiseasesAnimalsCenters for Disease Control and Prevention, U.S.Databases, FactualDogsHumansSpatial AnalysisUnited StatesentomologicalentomologyLyme diseaseOne Health modelriskspatialsurveillancethematic mappingticktick bite encountertick-borne disease surveillancetriangulationvector

Identifiers

PMID37610812
PMCPMC10483298
OpenAlexW4382278293

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.