Evidence map›Paper›PMID 42147000›Full record

ArticleChina CDC weekly2026

China's TB Portfolio for Advancing the 2030 End TB Goals.

Shaojun Pei, Caihong Xu, Dongmei Hu, Yanlin Zhao

Abstract read
In one paragraph

Article in China CDC weekly, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Shaojun Pei *Department of Global Health, School of Public health, Peking University, Beijing, China.
Caihong Xu *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China.
Dongmei HuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China.
Yanlin ZhaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for Tuberculosis Control and Prevention, Chinese Centre for Disease Control and Prevention & Chinese Academy of Preventive Medicine, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global trajectory for tuberculosis (TB) elimination remains precarious, characterized by a recent but fragile and insufficient decline in its incidence by 2024, the first since the coronavirus disease 2019 (COVID-19) pandemic. Progress is severely hampered by the failure to meet the ambitious 2025 End TB targets and is further threatened by anticipated funding cuts, necessitating a translation of widely accepted concepts of "high-level multi-sectoral cooperation" and "strict accountability" to concrete solutions. In contrast, China has achieved remarkable progress, meeting its goal of a 20% reduction in TB incidence from 2015 to 2024, suggesting a transition toward a lower-incidence setting. This success reflects a deliberate, science-driven, and strategic transformation. In this Personal View, we describe China's clearly defined national and provincial TB incidence-reduction targets for 2025 and 2030, as well as its comprehensive TB control program spanning the full continuum of care. China's integrated strategy, combining political commitment, rigorous strategy, sustainable financing, empowering research and innovation, the zoonotic and anthroponotic TB approach, and strong accountability mechanisms, offers a blueprint for low- and middle-income countries. It outlines a specific implementation pathway to revitalize global efforts to combat TB and restore confidence in the feasibility of ending TB.

Indexed as

End TBTB Control StrategyZero-TB

Identifiers

PMID42147000
PMCPMC13171627

What OpenQuestion holds

Textmetadata
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.