Evidence map›Paper›PMID 29082351›Full record

ArticleThe Lancet. Public health2017

Current and future trends in tuberculosis incidence in New York City: a dynamic modelling analysis.

Anthony T Fojo, Natalie L Stennis, Andrew S Azman, Emily A Kendall, Sourya Shrestha, Shama D Ahuja, David W Dowdy

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Lancet. Public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Epidemiologic and clinical characteristics ofFrontiers in cellular and infection microbiology · 2026
    Article
  2. Article
  3. Comparative Modeling of Tuberculosis Epidemiology and Policy Outcomes in California.American journal of respiratory and critical care medicine · 2020
    Article
  4. Use of Modeling to Inform Tuberculosis Elimination Strategies.American journal of respiratory and critical care medicine · 2020
    Article
  5. Estimated Impact of World Health Organization Latent Tuberculosis Screening Guidelines in a Region With a Low Tuberculosis Incidence: Retrospective Cohort Study.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2019
    Article
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Anthony T FojoDivision of General Internal Medicine, Johns Hopkins University School of Medicine, 2024 Monument St., Baltimore, MD, USA 21205.
Natalie L StennisBureau of Tuberculosis Control, New York City Department of Health and Mental Hygiene, 42-09 28th St, 21st floor, Long Island City, NY, USA 11101.
Andrew S AzmanDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St. Room E6531, Baltimore, MD, USA 21205.
Emily A KendallDivision of Infectious Diseases, Johns Hopkins University School of Medicine, PCTB Suite 211, 725 N. Wolfe St., Baltimore, MD, USA 21205.
Sourya ShresthaDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St. Room E6531, Baltimore, MD, USA 21205.
Shama D AhujaBureau of Tuberculosis Control, New York City Department of Health and Mental Hygiene, 42-09 28th St, 21st floor, Long Island City, NY, USA 11101.
David W DowdyDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St. Room E6531, Baltimore, MD, USA 21205.

Funding

Translational modeling of individual- and population-level outcomes of novel tuberculosis drug regimensK08AI127908 · NIAID · JOHNS HOPKINS UNIVERSITY · PI KENDALL, EMILY A · 2017 to 2021
$879k
NIAID NIH HHS K08 AI127908
6 · The paper itself

Abstract

backgroundAfter steady decline since the 1990s, tuberculosis (TB) incidence in New York City (NYC) and the United States (US) has flattened. The reasons for this trend and the implications for the future trajectory of TB in the US remain unclear.

methodsWe developed a compartmental model of TB in NYC, parameterized with detailed epidemiological data. We ran the model under five alternative scenarios representing different explanations for recent declines in TB incidence. We evaluated each scenario's relative likelihood by comparing its output to available data. We used the most likely scenarios to explore drivers of TB incidence and predict future trajectories of the TB epidemic in NYC.

findingsDemographic changes and declining TB transmission alone were insufficient to explain recent trends in NYC TB incidence. Only scenarios that assumed contemporary changes in TB dynamics among the foreign-born - a declining rate of reactivation or a decrease in imported subclinical TB - could accurately describe the trajectory of TB incidence since 2007. In those scenarios, the projected decline in TB incidence from 2015 to 2025 varied from minimal [2·0%/year (95% credible interval 0·4-3·5%)] to similar to 2005 to 2009 trends [4·4%/year (2·5-6·4%)]. The primary factor differentiating optimistic from pessimistic projections was the degree to which improvements in TB dynamics among the foreign-born continued into the coming decade.

interpretationFurther progress against TB in NYC requires additional focus on the foreign-born population. Absent additional intervention in this group, TB incidence may not decline further.

Indexed as

Health ResourcesHumansMathematical ModelNew York CityTuberculosisUnited States

Identifiers

PMID29082351
PMCPMC5659270

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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.