Evidence map›Paper›PMID 33556077›Full record

ArticlePLoS computational biology2021

Protective impacts of household-based tuberculosis contact tracing are robust across endemic incidence levels and community contact patterns.

Joshua Havumaki, Ted Cohen, Chengwei Zhai, Joel C Miller, Seth D Guikema, Marisa C Eisenberg, Jon Zelner

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 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
0.5field-weighted citation impact, top 42% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

7 authors at 3 institutions in 2 countries.

Joshua HavumakiDepartment of Epidemiology of Microbial Diseases, Yale University, New Haven, Connecticut, United States of America.ORCID 0000-0002-6749-1217
Ted CohenDepartment of Epidemiology of Microbial Diseases, Yale University, New Haven, Connecticut, United States of America.ORCID 0000-0002-8091-7198
Chengwei ZhaiDepartment of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0002-8508-9838
Joel C MillerSchool of Engineering and Mathematical Sciences, La Trobe University, Bundoora, Australia.ORCID 0000-0003-4426-0405
Seth D GuikemaDepartment of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan, United States of America.
Marisa C EisenbergDepartments of Epidemiology, Mathematics, Complex Systems, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0003-4221-830X
Jon ZelnerCenter for Social Epidemiology and Population Health, Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America.
University of Michigan · USYale University · USLa Trobe University · AU

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
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
Modeling the Effects of the Environment on Enteric Pathogen DynamicsU01GM110712 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI EISENBERG, JOSEPH N. S. · 2014 to 2018
$3.0M
Evaluating health and economic effects of targeted strategies in TB/HIVR01AI112438 · NIAID · YALE UNIVERSITY · PI COHEN, THEODORE H, SALOMON, JOSHUA A · 2014 to 2017
$2.4M
NCATS NIH HHS UL1 TR001863NIAID NIH HHS R01 AI112438NIAID NIH HHS R01 AI147854NIGMS NIH HHS U01 GM110712
6 · The paper itself

Abstract

There is an emerging consensus that achieving global tuberculosis control targets will require more proactive case finding approaches than are currently used in high-incidence settings. Household contact tracing (HHCT), for which households of newly diagnosed cases are actively screened for additional infected individuals is a potentially efficient approach to finding new cases of tuberculosis, however randomized trials assessing the population-level effects of such interventions in settings with sustained community transmission have shown mixed results. One potential explanation for this is that household transmission is responsible for a variable proportion of population-level tuberculosis burden between settings. For example, transmission is more likely to occur in households in settings with a lower tuberculosis burden and where individuals mix preferentially in local areas, compared with settings with higher disease burden and more dispersed mixing. To better understand the relationship between endemic incidence levels, social mixing, and the impact of HHCT, we developed a spatially explicit model of coupled household and community transmission. We found that the impact of HHCT was robust across settings of varied incidence and community contact patterns. In contrast, we found that the effects of community contact tracing interventions were sensitive to community contact patterns. Our results suggest that the protective benefits of HHCT are robust and the benefits of this intervention are likely to be maintained across epidemiological settings.

Indexed as

Contact TracingAlgorithmsComputer SimulationDisease ProgressionFamily CharacteristicsGlobal HealthHumansIncidenceProbabilityPublic Health InformaticsRandomized Controlled Trials as TopicRisk FactorsTuberculosis

Identifiers

PMID33556077
PMCPMC7895355
OpenAlexW3127426381

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.