Evidence map›Paper›PMID 37611506›Full record

ArticleTicks and tick-borne diseases2023

Comparison of acarological risk metrics derived from active and passive surveillance and their concordance with tick-borne disease incidence.

Karen M Holcomb, Noelle Khalil, Duncan W Cozens, Jamie L Cantoni, Doug E Brackney, Megan A Linske, Scott C Williams, Goudarz Molaei, Rebecca J Eisen

Abstract read
In one paragraph

Article in Ticks and tick-borne diseases, 2023. 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. Epidemiological and Molecular Characteristics ofTransboundary and emerging diseases · 2024
    Article
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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

9 authors.

Karen M HolcombDivision of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, CO, United States. Electronic address: kholcomb@cdc.gov.
Noelle KhalilCenter for Vector Biology and Zoonotic Diseases, The Connecticut Agricultural Experiment Station, New Haven, CT, United States.
Duncan W CozensCenter for Vector Biology and Zoonotic Diseases, The Connecticut Agricultural Experiment Station, New Haven, CT, United States.
Jamie L CantoniCenter for Vector Biology and Zoonotic Diseases, The Connecticut Agricultural Experiment Station, New Haven, CT, United States.
Doug E BrackneyCenter for Vector Biology and Zoonotic Diseases, The Connecticut Agricultural Experiment Station, New Haven, CT, United States.
Megan A LinskeCenter for Vector Biology and Zoonotic Diseases, The Connecticut Agricultural Experiment Station, New Haven, CT, United States.
Scott C WilliamsCenter for Vector Biology and Zoonotic Diseases, The Connecticut Agricultural Experiment Station, New Haven, CT, United States.
Goudarz MolaeiCenter for Vector Biology and Zoonotic Diseases, The Connecticut Agricultural Experiment Station, New Haven, CT, United States; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, United States.
Rebecca J EisenDivision of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, CO, United States.

Funding

COLLABORATIVE INTERNATIONAL BIRTH DEFECTS SURVEILLANCE PROGRAMU50DD000524 · DD · INTERNATIONAL CENTRE ON BIRTH DEFECTS · PI MASTROIACOVO, PIERPAOLO · 2009 to 2013
$1.0M
Intramural CDC HHS CC999999NCBDD CDC HHS U50 DD000524NCEZID CDC HHS U01 CK000509
6 · The paper itself

Abstract

Tick-borne diseases continue to threaten human health across the United States. Both active and passive tick surveillance can complement human case surveillance, providing spatio-temporal information on when and where humans are at risk for encounters with ticks and tick-borne pathogens. However, little work has been done to assess the concordance of the acarological risk metrics from each surveillance method. We used data on Ixodes scapularis and its associated human pathogens from Connecticut (2019-2021) collected through active collections (drag sampling) or passive submissions from the public to compare county estimates of tick and pathogen presence, infection prevalence, and tick abundance by life stage. Between the surveillance strategies, we found complete agreement in estimates of tick and pathogen presence, high concordance in infection prevalence estimates for Anaplasma phagocytophilum, Borrelia burgdorferi sensu stricto, and Babesia microti, but no consistent relationships between actively and passively derived estimates of tick abundance or abundance of infected ticks by life stage. We also compared nymphal metrics (i.e., pathogen prevalence in nymphs, nymphal abundance, and abundance of infected nymphs) with reported incidence of Lyme disease, anaplasmosis, and babesiosis, but did not find any consistent relationships with any of these metrics. The small spatial and temporal scale for which we had consistently collected active and passive data limited our ability to find significant relationships. Findings are likely to differ if examined across a broader spatial or temporal coverage with greater variation in acarological and epidemiological outcomes. Our results indicate similar outcomes between some actively and passively derived tick surveillance metrics (tick and pathogen presence, pathogen prevalence), but comparisons were variable for abundance estimates.

Indexed as

Borrelia burgdorferiIxodesLyme DiseaseTick-Borne DiseasesAnimalsHumansIncidenceNymphUnited StatesActive surveillanceAnaplasmosisBabesiosisIxodes scapularisLyme diseasePassive surveillance

Identifiers

PMID37611506
PMCPMC10885130

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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.