Evidence map›Paper›PMID 29554086›Full record

ArticlePLoS neglected tropical diseases2018

Are the London Declaration's 2020 goals sufficient to control Chagas disease?: Modeling scenarios for the Yucatan Peninsula.

Bruce Y Lee, Sarah M Bartsch, Laura Skrip, Daniel L Hertenstein, Cameron M Avelis, Martial Ndeffo-Mbah, Carla Tilchin, Eric O Dumonteil, Alison Galvani

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Modeling the impact of xenointoxication in dogs to haltmedRxiv : the preprint server for health sciences · 2023
    Article
  7. Article
  8. Review
  9. Review
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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

9 authors.

Bruce Y LeePublic Health Computational and Operations Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.ORCID 0000-0003-2633-8651
Sarah M BartschPublic Health Computational and Operations Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
Laura SkripCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, United States of America.
Daniel L HertensteinPublic Health Computational and Operations Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
Cameron M AvelisPublic Health Computational and Operations Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.ORCID 0000-0001-9909-5246
Martial Ndeffo-MbahCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, United States of America.
Carla TilchinPublic Health Computational and Operations Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.ORCID 0000-0003-3220-377X
Eric O DumonteilDepartment of Tropical Medicine, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States of America.
Alison GalvaniCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, United States of America.

Funding

MULTILEVEL SYSTEMS-ORIENTED CHILDHOOD OBESITY STUDY IN CHINAU54HD070725 · NICHD · JOHNS HOPKINS UNIVERSITY · PI WANG, YOUFA · 2011 to 2016
$15.9M
MIDAS Informatics Services Group (ISG)U24GM110707 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ESPINO, JESSI U, WAGNER, MICHAEL MATTHEW · 2014 to 2018
$11.6M
Accelerating viral outbreak detection in US cities using mechanistic models, machine learning and diverse geospatial dataR01AI151176 · NIAID · YALE UNIVERSITY · PI GALVANI, ALISON P, MEYERS, LAUREN ANCEL · 2020 to 2024
$3.9M
Virtual Population Obesity Prevention (VPOP) Labs: Computational, Multi-Scale Models for Obesity SolutionsU01HD086861 · NICHD · JOHNS HOPKINS UNIVERSITY · PI LEE, BRUCE Y · 2015 to 2019
$2.8M
Evaluating the social influences that impact vaccination decisionsU01GM105627 · NIGMS · YALE UNIVERSITY · PI GALVANI, ALISON P · 2013 to 2017
$1.6M
AHRQ HHS R01 HS023317NIAID NIH HHS R01 AI151176NICHD NIH HHS U01 HD086861NICHD NIH HHS U54 HD070725NIGMS NIH HHS U01 GM105627NIGMS NIH HHS U24 GM110707NIH HHS U24GM110707NIH HHS U54HD070725
6 · The paper itself

Abstract

backgroundThe 2020 Sustainable Development goals call for 100% certified interruption or control of the three main forms of Chagas disease transmission in Latin America. However, how much will achieving these goals to varying degrees control Chagas disease; what is the potential impact of missing these goals and if they are achieved, what may be left?

methodsWe developed a compartmental simulation model that represents the triatomine, human host, and non-human host populations and vector-borne, congenital, and transfusional T. cruzi transmission between them in the domestic and peridomestic settings to evaluate the impact of limiting transmission in a 2,000 person virtual village in Yucatan, Mexico.

resultsInterruption of domestic vectorial transmission had the largest impact on T. cruzi transmission and prevalence in all populations. Most of the gains were achieved within the first few years. Controlling vectorial transmission resulted in a 46.1-83.0% relative reduction in the number of new acute Chagas cases for a 50-100% interruption in domestic vector-host contact. Only controlling congenital transmission led to a 2.4-8.1% (30-100% interruption) relative reduction in the total number of new acute cases and reducing only transfusional transmission led to a 0.1-0.3% (30-100% reduction). Stopping all three forms of transmission resulted in 0.5 total transmission events over five years (compared to 5.0 with no interruption); interrupting all forms by 30% resulted in 3.4 events over five years per 2,000 persons.

conclusionsWhile reducing domestic vectorial, congenital, and transfusional transmission can successfully reduce transmission to humans (up to 82% in one year), achieving the 2020 goals would still result in 0.5 new acute cases per 2,000 over five years. Even if the goals are missed, major gains can be achieved within the first few years. Interrupting transmission should be combined with other efforts such as a vaccine or improved access to care, especially for the population of already infected individuals.

Indexed as

Disease VectorsAnimalsAnimals, DomesticChagas DiseaseHumansMexicoModels, StatisticalTrypanosoma cruzi

Identifiers

PMID29554086
PMCPMC5875875

What OpenQuestion holds

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Registered trials

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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.