From serological surveys to disease burden: a modelling pipeline for Chagas disease.
Chagas disease
Force-of-Infection
Random Forest
burden of disease
infectious diseases
modelling
Journal
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
ISSN: 1471-2970
Titre abrégé: Philos Trans R Soc Lond B Biol Sci
Pays: England
ID NLM: 7503623
Informations de publication
Date de publication:
09 10 2023
09 10 2023
Historique:
medline:
22
8
2023
pubmed:
21
8
2023
entrez:
20
8
2023
Statut:
ppublish
Résumé
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'.
Identifiants
pubmed: 37598701
doi: 10.1098/rstb.2022.0278
pmc: PMC10440172
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
20220278Subventions
Organisme : World Health Organization
ID : 001
Pays : International
Organisme : Medical Research Council
ID : MR/R015600/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R024855/1
Pays : United Kingdom
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