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From serological surveys to disease burden: a modelling pipeline for Chagas disease

In 2012, the World Health Organization (WHO) set the elimination of Chagas disease intradomiciliary vectorial transmission as a goal by 2020. After a decade, some progress has been made, but the new 2021–2030 WHO roadmap has set even more ambitious targets. Innovative and robust modelling methods ar...

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Autores principales: Ledien, Julia, Cucunubá, Zulma M., Parra-Henao, Gabriel, Rodríguez-Monguí, Eliana, Dobson, Andrew P., Adamo, Susana B., Castellanos, Luis Gerardo, Basáñez, María-Gloria, Nouvellet, Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440172/
https://www.ncbi.nlm.nih.gov/pubmed/37598701
http://dx.doi.org/10.1098/rstb.2022.0278
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author Ledien, Julia
Cucunubá, Zulma M.
Parra-Henao, Gabriel
Rodríguez-Monguí, Eliana
Dobson, Andrew P.
Adamo, Susana B.
Castellanos, Luis Gerardo
Basáñez, María-Gloria
Nouvellet, Pierre
author_facet Ledien, Julia
Cucunubá, Zulma M.
Parra-Henao, Gabriel
Rodríguez-Monguí, Eliana
Dobson, Andrew P.
Adamo, Susana B.
Castellanos, Luis Gerardo
Basáñez, María-Gloria
Nouvellet, Pierre
author_sort Ledien, Julia
collection PubMed
description In 2012, the World Health Organization (WHO) set the elimination of Chagas disease intradomiciliary vectorial transmission as a goal by 2020. After a decade, some progress has been made, but the new 2021–2030 WHO roadmap has set even more ambitious targets. Innovative and robust modelling methods are required to monitor progress towards these goals. We present a modelling pipeline using local seroprevalence data to obtain national disease burden estimates by disease stage. Firstly, local seroprevalence information is used to estimate spatio-temporal trends in the Force-of-Infection (FoI). FoI estimates are then used to predict such trends across larger and fine-scale geographical areas. Finally, predicted FoI values are used to estimate disease burden based on a disease progression model. Using Colombia as a case study, we estimated that the number of infected people would reach 506 000 (95% credible interval (CrI) = 395 000–648 000) in 2020 with a 1.0% (95%CrI = 0.8–1.3%) prevalence in the general population and 2400 (95%CrI = 1900–3400) deaths (approx. 0.5% of those infected). The interplay between a decrease in infection exposure (FoI and relative proportion of acute cases) was overcompensated by a large increase in population size and gradual population ageing, leading to an increase in the absolute number of Chagas disease cases over time. This article is part of the theme issue ‘Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs’.
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spelling pubmed-104401722023-08-21 From serological surveys to disease burden: a modelling pipeline for Chagas disease Ledien, Julia Cucunubá, Zulma M. Parra-Henao, Gabriel Rodríguez-Monguí, Eliana Dobson, Andrew P. Adamo, Susana B. Castellanos, Luis Gerardo Basáñez, María-Gloria Nouvellet, Pierre Philos Trans R Soc Lond B Biol Sci Articles In 2012, the World Health Organization (WHO) set the elimination of Chagas disease intradomiciliary vectorial transmission as a goal by 2020. After a decade, some progress has been made, but the new 2021–2030 WHO roadmap has set even more ambitious targets. Innovative and robust modelling methods are required to monitor progress towards these goals. We present a modelling pipeline using local seroprevalence data to obtain national disease burden estimates by disease stage. Firstly, local seroprevalence information is used to estimate spatio-temporal trends in the Force-of-Infection (FoI). FoI estimates are then used to predict such trends across larger and fine-scale geographical areas. Finally, predicted FoI values are used to estimate disease burden based on a disease progression model. Using Colombia as a case study, we estimated that the number of infected people would reach 506 000 (95% credible interval (CrI) = 395 000–648 000) in 2020 with a 1.0% (95%CrI = 0.8–1.3%) prevalence in the general population and 2400 (95%CrI = 1900–3400) deaths (approx. 0.5% of those infected). The interplay between a decrease in infection exposure (FoI and relative proportion of acute cases) was overcompensated by a large increase in population size and gradual population ageing, leading to an increase in the absolute number of Chagas disease cases over time. This article is part of the theme issue ‘Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs’. The Royal Society 2023-10-09 2023-08-21 /pmc/articles/PMC10440172/ /pubmed/37598701 http://dx.doi.org/10.1098/rstb.2022.0278 Text en This article is ©2023 https://royals-ociety.org/-/media/journals/author/Licence-to-Publish-20062019-final.pdfhttps://royalsociety.org/journals/ethics-policies/data-sharing-mining/Pan American Health Organization, Regional Office for the Americas of the World Health Organization. This is an open access article distributed under the terms of the Creative Commons Attribution IGO License (http://creativecommons.org/licenses/by/3.0/igo/legalcode (https://creativecommons.org/licenses/by/3.0/igo/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Ledien, Julia
Cucunubá, Zulma M.
Parra-Henao, Gabriel
Rodríguez-Monguí, Eliana
Dobson, Andrew P.
Adamo, Susana B.
Castellanos, Luis Gerardo
Basáñez, María-Gloria
Nouvellet, Pierre
From serological surveys to disease burden: a modelling pipeline for Chagas disease
title From serological surveys to disease burden: a modelling pipeline for Chagas disease
title_full From serological surveys to disease burden: a modelling pipeline for Chagas disease
title_fullStr From serological surveys to disease burden: a modelling pipeline for Chagas disease
title_full_unstemmed From serological surveys to disease burden: a modelling pipeline for Chagas disease
title_short From serological surveys to disease burden: a modelling pipeline for Chagas disease
title_sort from serological surveys to disease burden: a modelling pipeline for chagas disease
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440172/
https://www.ncbi.nlm.nih.gov/pubmed/37598701
http://dx.doi.org/10.1098/rstb.2022.0278
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