Evidence map›Paper›PMID 29147578›Full record

ArticleBMJ global health2017

Modelling historical changes in the force-of-infection of Chagas disease to inform control and elimination programmes: application in Colombia.

Zulma M Cucunubá, Pierre Nouvellet, Lesong Conteh, Mauricio Javier Vera, Victor Manuel Angulo, Juan Carlos Dib, Gabriel Jaime Parra-Henao, María Gloria Basáñez

Abstract read
In one paragraph

Article in BMJ global health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
–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

27 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
  6. The epidemiology of Chagas disease in the Americas.Lancet regional health. Americas · 2024
    Review
  7. The Hidden Hand of Asymptomatic Infection Hinders Control of Neglected Tropical Diseases: A Modeling Analysis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
    Article
  8. Review
  9. From serological surveys to disease burden: a modelling pipeline for Chagas disease.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
  10. Article
  11. Review
  12. Observational
  13. Article
  14. Genetic Instability among Hitnü People Living in Colombian Crude-Oil Exploitation Areas.International journal of environmental research and public health · 2022
    Article
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  16. Review
  17. 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

8 authors.

Zulma M CucunubáDepartment of Infectious Disease Epidemiology, Faculty of Medicine (St Mary's campus), Imperial College London, London, UK.ORCID 0000-0002-8165-3198
Pierre NouvelletDepartment of Infectious Disease Epidemiology, Faculty of Medicine (St Mary's campus), Imperial College London, London, UK.
Lesong ContehDepartment of Infectious Disease Epidemiology, Faculty of Medicine (St Mary's campus), Imperial College London, London, UK.
Mauricio Javier VeraGrupo de Enfermedades Endemo-Epidémicas, Subdirección Enfermedades Transmisibles, Ministerio de Salud y Protección Social, Bogotá, Colombia.
Victor Manuel AnguloCentro de Investigaciones en Enfermedades Tropicales (CINTROP), Universidad Industrial de Santander, Piedecuesta, Colombia.
Juan Carlos DibFundación Salud para el Trópico, SantaMarta, Colombia.
Gabriel Jaime Parra-HenaoInstituto Colombiano de Medicina Tropical, Universidad CES, Santa Martha, Colombia.
María Gloria BasáñezDepartment of Infectious Disease Epidemiology, Faculty of Medicine (St Mary's campus), Imperial College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWHO's 2020 milestones for Chagas disease include having all endemic Latin American countries certified with no intradomiciliary

methodsFocusing on Colombia, all the available age-structured serological surveys (undertaken between 1995 and 2014) were searched and compiled. A total of 109 serosurveys were found, comprising 83 742 individuals from rural (indigenous and non-indigenous) and urban settings in 14 (out of 32) administrative units (departments). Estimates of the force-of-infection (FoI) were obtained by fitting and comparing three catalytic models using Bayesian methods to reconstruct temporal and spatial patterns over the course of three decades (between 1984 and 2014).

resultsSignificant downward changes in the FoI were identified over the course of the three decades, and in some specific locations the predicted current seroprevalence in children aged 0-5 years is <1%. However, pronounced heterogeneity exists within departments, especially between indigenous, rural and urban settings, with the former exhibiting the highest FoI (up to 66 new infections/1000 people susceptible/year). The FoI in most of the indigenous settings remain unchanged during the three decades investigated. Current prevalence in adults in these 15 departments varies between 10% and 90% depending on the dynamics of historical exposure.

conclusionsAssessing progress towards the control of Chagas disease requires quantifying the impact of historical exposure on current age-specific prevalence at subnational level. In Colombia, despite the evident progress, there is a marked heterogeneity indicating that in some areas the vector control interventions have not been effective, hindering the possibility of achieving interruption by 2020. A substantial burden of chronic cases remains even in locations where serological criteria for transmission interruption may have been achieved, therefore still demanding diagnosis and treatment interventions.

Indexed as

chagas diseasecontrol strategiescross-sectional surveymathematical modellingserology

Identifiers

PMID29147578
PMCPMC5680445

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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.