Evidence map›Paper›PMID 31781687›Full record

ArticleGates open research2019

Insights from quantitative and mathematical modelling on the proposed WHO 2030 goals for Chagas disease.

Collaborating Group on Chagas Disease Modelling

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
1.0field-weighted citation impact, top 23% 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, 9 citations in OpenAlex.

  1. Using Passive Surveillance to Maintain Elimination as a Public Health Problem for Neglected Tropical Diseases: A Model-Based Exploration.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
    Article
  2. Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions?Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
    Article
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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

1 author at 1 institution in 1 country.

Collaborating Group on Chagas Disease Modelling
Imperial College London · GB

Funding

An immune system for the city: a new paradigm for control of urban disease vectorsR01AI146129 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI LEVY, MICHAEL Z, PAZ-SOLDAN, VALERIE ANDREA · 2019 to 2023
$3.3M
Disrupting Vector-borne Disease Transmission in Complex Urban EnvironmentsR01AI101229 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI LEVY, MICHAEL Z · 2013 to 2017
$3.1M
Improving participation in vector control campaigns R01HD075869 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI BUTTENHEIM, ALISON MEREDITH, LEVY, MICHAEL Z · 2014 to 2018
$2.6M
Medical Research Council MR/R015600/1Medical Research Council MR/R024855/1NIAID NIH HHS R01 AI101229NIAID NIH HHS R01 AI146129NICHD NIH HHS R01 HD075869
6 · The paper itself

Abstract

Chagas disease (CD) persists as one of the neglected tropical diseases (NTDs) with a particularly large impact in the Americas. The World Health Organization (WHO) recently proposed goals for CD elimination as a public health problem to be reached by 2030 by means of achieving intradomiciliary transmission interruption (IDTI), blood transfusion and transplant transmission interruption, diagnostic and treatment scaling-up and prevention and control of congenital transmission. The NTD Modelling Consortium has developed mathematical models to study

Indexed as

Chagas diseaseElimination as a public health problemintradomiciliary transmission interruptionNTD Modelling Consortiumtrypanocidal treatmentWHO guidelines

Identifiers

PMID31781687
PMCPMC6856696
OpenAlexW3000310527

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.