Evidence map›Paper›PMID 30383419›Full record

ArticleAmerican journal of public health2018

Tuberculosis Incidence Among Populations at High Risk in California, Florida, New York, and Texas, 2011-2015.

Sarah T Cherng, Sourya Shrestha, Sue Reynolds, Andrew N Hill, Suzanne M Marks, Jane Kelly, David W Dowdy

Abstract read
In one paragraph

Article in American journal of public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Model-based Cost-effectiveness of State-level Latent Tuberculosis Interventions in California, Florida, New York, and Texas.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021
    Article
  3. Article
  4. Article
  5. Article
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

7 authors.

Sarah T CherngSarah T. Cherng, Sourya Shrestha, and David W. Dowdy are with the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. Sue Reynolds, Andrew N. Hill, and Suzanne M. Marks are with the Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA. Jane Kelly is with the Georgia Department of Public Health, Atlanta.
Sourya ShresthaSarah T. Cherng, Sourya Shrestha, and David W. Dowdy are with the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. Sue Reynolds, Andrew N. Hill, and Suzanne M. Marks are with the Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA. Jane Kelly is with the Georgia Department of Public Health, Atlanta.
Sue ReynoldsSarah T. Cherng, Sourya Shrestha, and David W. Dowdy are with the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. Sue Reynolds, Andrew N. Hill, and Suzanne M. Marks are with the Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA. Jane Kelly is with the Georgia Department of Public Health, Atlanta.
Andrew N HillSarah T. Cherng, Sourya Shrestha, and David W. Dowdy are with the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. Sue Reynolds, Andrew N. Hill, and Suzanne M. Marks are with the Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA. Jane Kelly is with the Georgia Department of Public Health, Atlanta.
Suzanne M MarksSarah T. Cherng, Sourya Shrestha, and David W. Dowdy are with the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. Sue Reynolds, Andrew N. Hill, and Suzanne M. Marks are with the Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA. Jane Kelly is with the Georgia Department of Public Health, Atlanta.
Jane KellySarah T. Cherng, Sourya Shrestha, and David W. Dowdy are with the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. Sue Reynolds, Andrew N. Hill, and Suzanne M. Marks are with the Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA. Jane Kelly is with the Georgia Department of Public Health, Atlanta.
David W DowdySarah T. Cherng, Sourya Shrestha, and David W. Dowdy are with the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. Sue Reynolds, Andrew N. Hill, and Suzanne M. Marks are with the Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA. Jane Kelly is with the Georgia Department of Public Health, Atlanta.

Funding

Virology and Molecular Biomarkers CoreP30AI050409 · NIAID · EMORY UNIVERSITY · PI Carlos del Rio · 2002 to 2026
$74.0M
Methods and Data CoreR24HD042828 · NICHD · UNIVERSITY OF WASHINGTON · PI TOLNAY, STEWART E · 2002 to 2016
$9.3M
Statistical Methods for Network EpidemiologyR01HD068395 · NICHD · UNIVERSITY OF WASHINGTON · PI MORRIS, WANDA MARTINA · 2011 to 2015
$3.0M
ENHANCING MODELS OF HIV, VIRAL HEPATITIS, STIs, AND TUBERCULOSIS TO INFORM AND IMPROVE PUBLIC HEALTH IMPACTU38PS004646 · PS · EMORY UNIVERSITY · PI SULLIVAN, PATRICK · 2014 to 2015
$2.9M
Using Sexual Network Transmission Models to Explain HIV Disparities Between BlackR21HD075662 · NICHD · UNIVERSITY OF WASHINGTON · PI GOODREAU, STEVEN M. · 2013 to 2014
$418k
NCHHSTP CDC HHS U38 PS004646NIAID NIH HHS P30 AI050409NICHD NIH HHS R01 HD068395NICHD NIH HHS R21 HD075662NICHD NIH HHS R24 HD042828
6 · The paper itself

Abstract

objectivesTo illustrate the magnitude of between-state heterogeneities in tuberculosis (TB) incidence among US populations at high risk for TB that may help guide state-specific strategies for TB elimination.

methodsWe used data from the National Tuberculosis Surveillance System and other public sources from 2011 to 2015 to calculate TB incidence in every US state among people who were non-US-born, had diabetes, or were HIV-positive, homeless, or incarcerated. We then estimated the proportion of TB cases that reflected the difference between each state's reported risk factor-specific TB incidence and the lowest incidence achieved among 4 states (California, Florida, New York, Texas). We reported these differences for the 4 states and also calculated and aggregated across all 50 states to quantify the total percentage of TB cases nationally that reflected between-state differences in risk factor-specific TB incidence.

resultsOn average, 24% of recent TB incidence among high-risk US populations reflected heterogeneity at the state level. The populations that accounted for the greatest percentage of heterogeneity-reflective cases were non-US-born individuals (51%) and patients with diabetes (24%).

conclusionsState-level differences in TB incidence among key populations provide clues for targeting state-level interventions.

Indexed as

HumansIncidencePublic Health SurveillanceRetrospective StudiesRisk FactorsTuberculosisUnited States

Identifiers

PMID30383419
PMCPMC6215364

What OpenQuestion holds

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Registered trials

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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.