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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.
Afiliación
  • Ledien J; School of Life Sciences, University of Sussex, Falmer, Brighton BN1 9RH, UK.
  • Cucunubá ZM; Departamento de Epidemiología Clínica y Bioestadística, Facultad de Medicina, Universidad Pontificia Javeriana, 110231 Bogotá, Colombia.
  • Parra-Henao G; Centro de Investigación en Salud para el Trópico, Universidad Cooperativa de Colombia, 470002, Santa Marta, Colombia.
  • Rodríguez-Monguí E; National Institute of Health, 111321 Bogotá, Colombia.
  • Dobson AP; Departamento de Epidemiología Clínica y Bioestadística, Facultad de Medicina, Universidad Pontificia Javeriana, 110231 Bogotá, Colombia.
  • Adamo SB; Independent consultant to the Neglected, Tropical and Vector Borne Diseases Program, Pan American Health Organization (PAHO), Colombia.
  • Castellanos LG; Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.
  • Basáñez MG; Center for International Earth Science Information Network (CIESIN), Columbia Climate School, Columbia University, New York, NY 10025, USA.
  • Nouvellet P; Department of Communicable Diseases and Environmental Determinants of Health, Pan American Health Organization (PAHO), Washington, DC 20037, USA.
Philos Trans R Soc Lond B Biol Sci ; 378(1887): 20220278, 2023 10 09.
Article en En | MEDLINE | ID: mdl-37598701
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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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Envejecimiento / Enfermedad de Chagas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: America do sul / Colombia Idioma: En Revista: Philos Trans R Soc Lond B Biol Sci Año: 2023 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Envejecimiento / Enfermedad de Chagas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: America do sul / Colombia Idioma: En Revista: Philos Trans R Soc Lond B Biol Sci Año: 2023 Tipo del documento: Article