Evidence map›Paper›PMID 31886455›Full record

ArticleGates open research2019

Insights from quantitative and mathematical modelling on the proposed 2030 goals for Yaws.

Louise Dyson, Eric Q Mooring, Alex Holmes, Michael J Tildesley, Michael Marks

Open access · goldAbstract read
In one paragraph

Article in Gates open research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-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

7 citing papers in PubMed, 17 citations in OpenAlex.

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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

5 authors at 3 institutions in 2 countries.

Louise DysonMathematics Institute, University of Warwick, Coventry, CV4 7AL, UK.ORCID https://orcid.org/0000-0001-9788-4858
Eric Q MooringDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Alex HolmesMathematics Institute, University of Warwick, Coventry, CV4 7AL, UK.
Michael J TildesleyMathematics Institute, University of Warwick, Coventry, CV4 7AL, UK.
Michael MarksClinical Research Department, Faculty of Infectious & Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.ORCID https://orcid.org/0000-0002-7585-4743
University of Warwick · GBHarvard University · USLondon School of Hygiene & Tropical Medicine · GB

Funding

Epidemiology of Infectious Diseases and BiodefenseT32AI007535 · NIAID · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI GRAD, YONATAN H, MURRAY, MEGAN B · 1998 to 2025
$4.8M
NIAID NIH HHS T32 AI007535
6 · The paper itself

Abstract

The World Health Organization is currently developing 2030 goals for neglected tropical diseases (NTDs). In these, yaws has been targeted for eradication by 2030, with 50% of member states certified free of yaws transmission by 2023. Here we summarise the yaws modelling literature and discuss the proposed goal and strategy. The current Morges strategy involves rounds of Total Community Treatment (TCT), in which all members of the community are treated, and Total Targeted Treatment (TTT), treating active cases and their contacts. However, modelling and empirical work suggest that latent infections are often not found in the same household as active cases, reducing the utility of household-based contact tracing for a TTT strategy. Economic modelling has also discovered uncertainty in the cost of eradication, requiring further data to give greater information. We also note the need for improved active surveillance in previously endemic countries, in order to plan future intervention efforts and ensure global eradication.

Indexed as

modellingneglected tropical diseasesyaws

Identifiers

PMID31886455
PMCPMC6913063
OpenAlexW2980346201

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.