Evidence map›Paper›PMID 33874940›Full record

ArticleBMC medicine2021

The positive externalities of migrant-based TB control strategy in a Chinese urban population with internal migration: a transmission-dynamic modeling study.

Chongguang Yang, Jian Kang, Liping Lu, Xiaoqin Guo, Xin Shen, Ted Cohen, Nicolas A Menzies

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

4 citing papers in PubMed, 12 citations in OpenAlex.

  1. Quantifying the community transmission ofEmerging microbes & infections · 2026
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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

7 authors at 3 institutions in 2 countries.

Chongguang Yang *Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, CT, USA.
Jian Kang *Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Liping LuDepartment of Tuberculosis Control, Songjiang Center for Disease Control and Prevention, Shanghai, China.
Xiaoqin GuoDepartment of Tuberculosis Control, Songjiang Center for Disease Control and Prevention, Shanghai, China.
Xin Shen *Department of Tuberculosis Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China. shenxin@scdc.sh.cn.
Ted CohenDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, CT, USA.
Nicolas A Menzies *Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA. nmenzies@hsph.harvard.edu.
Harvard Global Health Institute · USYale University · USShanghai Municipal Center For Disease Control Prevention · CN

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
Institutional Career Development CoreKL2TR001862 · NCATS · YALE UNIVERSITY · PI CANTLEY, LLOYD G, EDELMAN, E. JENNIFER · 2016 to 2025
$12.2M
Optimal targeting for individual and population-level TB preventionR01AI146555 · NIAID · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI MENZIES, NICOLAS A · 2020 to 2024
$2.5M
NCATS NIH HHS KL2 TR001862NCATS NIH HHS UL1 TR001863NIAID NIH HHS R01 AI146555NIH HHS R01AI13058NIH HHS R01AI146555
6 · The paper itself

Abstract

backgroundLarge-scale rural-to-urban migration has changed the epidemiology of tuberculosis (TB) in large Chinese cities. We estimated the contribution of TB importation, reactivation of latent infection, and local transmission to new TB cases in Shanghai, and compared the potential impact of intervention options.

methodsWe developed a transmission dynamic model of TB for Songjiang District, Shanghai, which has experienced high migration over the past 25 years. We calibrated the model to local demographic data, TB notifications, and molecular epidemiologic studies. We estimated epidemiological drivers as well as future outcomes of current TB policies and compared this base-case scenario with scenarios describing additional targeted interventions focusing on migrants or vulnerable residents.

resultsThe model captured key demographic and epidemiological features of TB among migrant and resident populations in Songjiang District, Shanghai. Between 2020 and 2035, we estimate that over 60% of TB cases will occur among migrants and that approximately 43% of these cases will result from recent infection. While TB incidence will decline under current policies, we estimate that additional interventions-including active screening and preventive treatment for migrants-could reduce TB incidence by an additional 20% by 2035.

conclusionsMigrant-focused TB interventions could produce meaningful health benefits for migrants, as well as for young residents who receive indirect protection as a result of reduced TB transmission in Shanghai. Further studies to measure cost-effectiveness are needed to evaluate the feasibility of these interventions in Shanghai and similar urban centers experiencing high migration volumes.

Indexed as

Transients and MigrantsTuberculosisChinaHumansIncidenceUrban PopulationChinaInternal migrationPublic health policyTransmission-dynamic modelingTuberculosis

Identifiers

PMID33874940
PMCPMC8055441
OpenAlexW3155362051

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.