Evidence map›Paper›PMID 23785416›Full record

ArticlePloS one2013

Predicting U.S. tuberculosis case counts through 2020.

Rachel S Y E L K Woodruff, Carla A Winston, Roque Miramontes

Abstract readHistorical Article
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

3 authors.

Rachel S Y E L K WoodruffCenters for Disease Control and Prevention, Atlanta, Georgia, United States of America. ryelkwoodruff@cdc.gov
Carla A Winston
Roque Miramontes

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In 2010, foreign-born persons accounted for 60% of all tuberculosis (TB) cases in the United States. Understanding which national groups make up the highest proportion of TB cases will assist TB control programs in concentrating limited resources where they can provide the greatest impact on preventing transmission of TB disease. The objective of our study was to predict through 2020 the numbers of U.S. TB cases among U.S.-born, foreign-born and foreign-born persons from selected countries of birth. TB case counts reported through the National Tuberculosis Surveillance System from 2000-2010 were log-transformed, and linear regression was performed to calculate predicted annual case counts and 95% prediction intervals for 2011-2020. Data were analyzed in 2011 before 2011 case counts were known. Decreases were predicted between 2010 observed and 2020 predicted counts for total TB cases (11,182 to 8,117 [95% prediction interval 7,262-9,073]) as well as TB cases among foreign-born persons from Mexico (1,541 to 1,420 [1,066-1,892]), the Philippines (740 to 724 [569-922]), India (578 to 553 [455-672]), Vietnam (532 to 429 [367-502]) and China (364 to 328 [249-433]). TB cases among persons who are U.S.-born and foreign-born were predicted to decline 47% (4,393 to 2,338 [2,113-2,586]) and 6% (6,720 to 6,343 [5,382-7,476]), respectively. Assuming rates of declines observed from 2000-2010 continue until 2020, a widening gap between the numbers of U.S.-born and foreign-born TB cases was predicted. TB case count predictions will help TB control programs identify needs for cultural competency, such as languages and interpreters needed for translating materials or engaging in appropriate community outreach.

Indexed as

Population SurveillanceHistory, 21st CenturyHumansTuberculosisUnited States

Identifiers

PMID23785416
PMCPMC3681901

What OpenQuestion holds

Textmetadata
LicenceCC0
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.