Evidence map›Paper›PMID 33242759›Full record

ArticleEpidemics2020

High-resolution estimates of tuberculosis incidence among non-U.S.-born persons residing in the United States, 2000-2016.

Andrew N Hill, Ted Cohen, Joshua A Salomon, Nicolas A Menzies

Open access · goldAbstract read
In one paragraph

Article in Epidemics, 2020. 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
0.2field-weighted citation impact, top 38% 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

7 citing papers in PubMed, 16 citations in OpenAlex.

  1. Effects of the COVID-19 Pandemic on Tuberculosis Outcomes in the United States: A Bayesian Analysis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Trends, Mechanisms, and Racial/Ethnic Differences of Tuberculosis Incidence in the US-Born Population Aged 50 Years or Older in the United States.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022
    Article
  6. TB risk by time since U.S. entry among non-U.S.-born residents of Washington State, USA.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2021
    Article
  7. 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

4 authors at 4 institutions in 1 country.

Andrew N HillDivision of Tuberculosis Elimination, U.S. Centers for Disease Control and Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD and TB Prevention, Atlanta, GA 30329, USA. Electronic address: fyu7@cdc.gov.
Ted CohenDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Joshua A SalomonDepartment of Medicine, Stanford University, Stanford, CA, USA.
Nicolas A MenziesDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Centers for Disease Control and Prevention · USHarvard Global Health Institute · USStanford University · USYale University · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Economic Modeling for HIV, Viral Hepatitis, STD, TB and School HealthU38PS004644 · PS · HARVARD SCHOOL OF PUBLIC HEALTH · PI SALOMON, JOSHUA A · 2014 to 2015
$2.9M
Intramural CDC HHS CC999999NCATS NIH HHS UL1 TR001863NCHHSTP CDC HHS U38 PS004644
6 · The paper itself

Abstract

In the United States, new tuberculosis cases are increasingly concentrated within non-native-born populations. We estimated trends and differences in tuberculosis incidence rates for the non-U.S.-born population, at a resolution unobtainable from raw data. We obtained non-U.S.-born tuberculosis case reports for 2000-2016 from the National Tuberculosis Surveillance System, and population data from the American Community Survey and 2000 U.S. Census. We constructed generalized additive regression models to estimate incidence rates in terms of birth country, entry year, age at entry, and number of years since entry into the United States and described how these factors contribute to overall tuberculosis risk. Controlling for other factors, tuberculosis incidence rates were lower for more recent immigration cohorts, with an incidence risk ratio (IRR) of 10.2 (95 % confidence interval 7.0, 14.7) for the 1950 entry cohort compared to its 2016 counterpart. Greater years since entry and younger age at entry were associated with substantially lower incidence rates. IRRs for birth country varied between 8.86 (6.78, 11.52) for Somalia and 0.02 (0.01, 0.03) for Canada, compared to all non-U.S.-born residents in 2016. IRRs were positively correlated with WHO predicted incidence rate and negatively associated with wealth level for the birth country. Lower country wealth level was also associated with shallower declines in tuberculosis over time. Tuberculosis risks differ by several orders of magnitude within the non-U.S.-born population. A better understanding of these differences will allow more effective targeting of tuberculosis prevention efforts. The methods presented here may also be relevant for understanding tuberculosis trends in other high-income countries.

Indexed as

CanadaEmigrants and ImmigrantsEmigration and ImmigrationFemaleHumansIncidenceMaleMiddle AgedOdds RatioPopulation SurveillanceReceptor, InsulinSurveys and QuestionnairesTuberculosisUnited StatesYoung Adultinsulin receptor-related receptorReceptor, InsulinGeneralized additive modelsIncidence trendsTuberculosis

Identifiers

PMID33242759
PMCPMC7808561
OpenAlexW3101669818

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.