Evidence map›Paper›PMID 35597716›Full record

ReviewTrends in microbiology2022

Connecting the dots: understanding how human mobility shapes TB epidemics.

Tyler S Brown, D Ashley Robinson, Caroline O Buckee, Barun Mathema

Open access · greenAbstract readReview
In one paragraph

Review in Trends in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.7field-weighted citation impact, top 14% 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

14 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Genomic epidemiology ofMicrobial genomics · 2026
    Article
  3. Transmission of bedaquiline-resistant Mycobacterium tuberculosis in KwaZulu-Natal, South Africa.American journal of respiratory and critical care medicine · 2026
    Article
  4. Article
  5. First insights into the genetic composition ofJournal of clinical tuberculosis and other mycobacterial diseases · 2025
    Article
  6. Article
  7. Article
  8. Mobility patterns, activity locations, and TB in Nairobi, Kenya.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2025
    Article
  9. Article
  10. Article
  11. One Half of the Pair: Prioritizing Tuberculosis Transmitters for Early Detection.American journal of respiratory and critical care medicine · 2024
    Article
  12. Article
  13. Article
  14. Spatial scale of tuberculosis transmission in Lima, Peru.Proceedings of the National Academy of Sciences of the United States of America · 2022
    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 at 3 institutions in 1 country.

Tyler S BrownCenter for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Infectious Diseases Division, Massachusetts General Hospital, Boston, MA, USA.
D Ashley RobinsonDepartment of Microbiology and Immunology, University of Mississippi Medical Center, Jackson, MS, USA.
Caroline O BuckeeCenter for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Barun MathemaDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA. Electronic address: bm2055@cumc.columbia.edu.
Center for Disease Dynamics, Economics & Policy · USColumbia University Irving Medical Center · USUniversity of Mississippi Medical Center · US

Funding

INFECTIOUS DISEASE AND BASIC MICROBIOLOGICAL MECHANISMST32AI007061 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI Marcia B Goldberg · 1985 to 2026
$12.1M
Geographic origins and dispersal of drug-resistant M. tuberculosis in South Africa: Advancing strategies for early detectionK08AI166125 · NIAID · UNIVERSITY OF COLORADO DENVER · PI BROWN, TYLER STEVEN · 2022 to 2025
$780k
NIAID NIH HHS K08 AI166125NIAID NIH HHS T32 AI007061
6 · The paper itself

Abstract

Tuberculosis (TB) remains a leading infectious cause of death worldwide. Reducing TB infections and TB-related deaths rests ultimately on stopping forward transmission from infectious to susceptible individuals. Critical to this effort is understanding how human host mobility shapes the transmission and dispersal of new or existing strains of Mycobacterium tuberculosis (Mtb). Important questions remain unanswered. What kinds of mobility, over what temporal and spatial scales, facilitate TB transmission? How do human mobility patterns influence the dispersal of novel Mtb strains, including emergent drug-resistant strains? This review summarizes the current state of knowledge on mobility and TB epidemic dynamics, using examples from three topic areas, including inference of genetic and spatial clustering of infections, delineating source-sink dynamics, and mapping the dispersal of novel TB strains, to examine scientific questions and methodological issues within this topic. We also review new data sources for measuring human mobility, including mobile phone-associated movement data, and discuss important limitations on their use in TB epidemiology.

Indexed as

EpidemicsMycobacterium tuberculosisTuberculosisAntitubercular AgentsHumansAntitubercular Agents

Identifiers

PMID35597716
PMCPMC10068677
OpenAlexW4280542207

What OpenQuestion holds

Textmetadata
LicenceTDM
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.