Evidence map›Paper›PMID 36964130›Full record

ArticleNature communications2023

Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics.

Peter J Dodd, Debebe Shaweno, Chu-Chang Ku, Philippe Glaziou, Carel Pretorius, Richard J Hayes, Peter MacPherson, Ted Cohen, Helen Ayles

Full text read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Literature Highlights.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2023
    Article
  10. Article
  11. Review
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

9 authors.

Peter J DoddSchool of Health and Related Research, University of Sheffield, Sheffield, UK. p.j.dodd@sheffield.ac.uk.ORCID 0000-0001-5825-9347
Debebe ShawenoSchool of Public Health, Infectious Disease Epidemiology, Imperial College London, London, UK.ORCID 0000-0001-9596-5443
Chu-Chang KuSchool of Public Health, Infectious Disease Epidemiology, Imperial College London, London, UK.
Philippe GlaziouGlobal TB Programme, World Health Organization, Geneva, Switzerland.
Carel PretoriusAvenir Health, Glastonbury, CT, USA.
Richard J HayesDepartment of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Peter MacPhersonSchool of Health & Wellbeing, University of Glasgow, Glasgow, UK.
Ted CohenDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.ORCID 0000-0002-8091-7198
Helen AylesClinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.

Funding

Transmission Aerobiology of M. tuberculosis: Genes and Metabolic Pathways That Sustain Mtb Across an Evolutionary BottleneckP01AI159402 · NIAID · WEILL MEDICAL COLL OF CORNELL UNIV · PI BOUROUIBA, LYDIA · 2021 to 2025
$15.8M
Integrating genomic and spatial approaches for targeted control of HIV-associated tuberculosis epidemicsR01AI147854 · NIAID · YALE UNIVERSITY · PI COHEN, THEODORE H, SALOMON, JOSHUA A · 2020 to 2023
$3.1M
Medical Research Council MR/P022081/1Medical Research Council MR/R010161/1NIAID NIH HHS P01 AI159402NIAID NIH HHS R01 AI147854Wellcome Trust 206575/Z/17/ZWorld Health Organization 001
6 · The paper itself

Abstract

Tuberculosis (TB) killed more people globally than any other single pathogen over the past decade. Where surveillance is weak, estimating TB burden estimates uses modeling. In many African countries, increases in HIV prevalence and antiretroviral therapy have driven dynamic TB epidemics, complicating estimation of burden, trends, and potential intervention impact. We therefore develop a novel age-structured TB transmission model incorporating evolving demographic, HIV and antiretroviral therapy effects, and calibrate to TB prevalence and notification data from 12 African countries. We use Bayesian methods to include uncertainty for all TB model parameters, and estimate age-specific annual risks of TB infection, finding up to 16.0%/year in adults, and the proportion of TB incidence from recent (re)infection, finding a mean across countries of 34%. Rapid reduction of the unacceptably high burden of TB in high HIV prevalence settings will require interventions addressing progression as well as transmission.

Indexed as

EpidemicsHIV InfectionsTuberculosisAdultBayes TheoremHumansIncidencePrevalence

Identifiers

PMID36964130
PMCPMC10037365

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read59
table measurements read1
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.