Evidence map›Paper›PMID 34433597›Full record

ArticleBMJ open2021

Impact of the gate-keeping policies of China's primary healthcare model on the future burden of tuberculosis in China: a protocol for a mathematical modelling study.

Xinyi You, Jing Gu, Dong Roman Xu, Shanshan Huang, Hao Xue, Chun Hao, Yunzhou Ruan, Sean Sylvia, Jing Liao, Yiyuan Cai and 5 more

Abstract read
In one paragraph

Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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

15 authors.

Xinyi You *Department of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Jing Gu *Department of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China.ORCID 0000-0001-5436-2339
Dong Roman XuACACIA Labs, Institute for Global Health and School of Health Management, Southern Medical University, Guangzhou, Guangdong, China.ORCID 0000-0001-7438-632X
Shanshan HuangCentre for Tuberculosis Control of Guangdong Province, Guangzhou, Guangdong, China.
Hao XueStanford Center on China's Economy and Institutions, Stanford University, Stanford, California, USA.
Chun HaoDepartment of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Yunzhou RuanDepartment of Tuberculosis Resistance Prevention and Control, Chinese Center for Disease Control and Prevention, Beijing, China.
Sean SylviaDepartment of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
Jing LiaoDepartment of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Yiyuan CaiDepartment of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Liping PengDepartment of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Xiaohui WangDepartment of Social Medicine and Health Management, School of Public Health, Lanzhou University, Lanzhou, Gansu, China.
Renzhong LiDepartment of Tuberculosis Resistance Prevention and Control, Chinese Center for Disease Control and Prevention, Beijing, China lijinghua3@mail.sysu.edu.cn Lirz@chinacdc.cn.
Jinghua LiDepartment of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China lijinghua3@mail.sysu.edu.cn Lirz@chinacdc.cn.ORCID 0000-0002-9571-7359
Yuantao HaoDepartment of Medical Statistics, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China.ORCID 0000-0001-8024-5312

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn the past three decades, China has made great strides in the prevention and treatment of tuberculosis (TB). However, the TB burden remains high. In 2019, China accounted for 8.4% of global incident cases of TB, the third highest in the world, with a higher prevalence in rural areas. The Healthy China 2030 highlights the gate-keeping role of primary healthcare (PHC). However, the impact of PHC reforms on the future TB burden is unclear. We propose to use mathematical models to project and evaluate the impacts of different gate-keeping policies. METHODS AND ANALYSIS: We will develop a deterministic, population-level, compartmental model to capture the dynamics of TB transmission within adult rural population. The model will incorporate seven main TB statuses, and each compartment will be subdivided by service providers. The parameters involving preference for healthcare seeking will be collected using discrete choice experiment (DCE) method. We will solve the deterministic model numerically over a 20-year (2021-2040) timeframe and predict the TB prevalence, incidence and cumulative new infections under the status quo or various policy scenarios. We will also conduct an analysis following standard protocols to calculate the average cost-effectiveness for each policy scenario relative to the status quo. A numerical calibration analysis against the available published TB prevalence data will be performed using a Bayesian approach. ETHICS AND DISSEMINATION: Most of the data or parameters in the model will be obtained based on secondary data (eg, published literature and an open-access data set). The DCE survey has been reviewed and approved by the Ethics Committee of the School of Public Health, Sun Yat-sen University. The approval number is SYSU [2019]140. Results of the study will be disseminated through peer-reviewed journals, media and conference presentations.

Indexed as

TuberculosisAdultBayes TheoremChinaHealth Care ReformHumansModels, TheoreticalPrimary Health Careepidemiologyhealth economicshealth policyprimary caretuberculosis

Identifiers

PMID34433597
PMCPMC8390147

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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.