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

Abstract

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’.

Introduction to the special issue: challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs

“…The paper by Borlase et al in this volume discusses the challenges for determining the relationship between cumulative pathogen exposure and morbidity at the individual and population levels, drawing on case studies for trachoma, schistosomiasis and foodborne trematode infections, and explores potential frameworks for explicitly incorporating long-term morbidity into NTD transmission models [28]. These frameworks are crucial for quantifying burden of disease, and the paper by Ledien and colleagues presents a modelling pipeline from serological surveys to morbi-mortality models for Chagas disease (an IDM) to quantify disease burden in time and space [29].…”

“…For this issue, NTD modellers have contributed seven papers (50% of the contributions), including the potential of alternative treatment strategies for accelerating programmatic action towards attaining interruption of transmission [ 9 ]; the design of NTD impact surveys [ 12 ]; the usefulness of current and novel tools for diagnosis of helminthiases in areas ranging from low to high prevalence [ 17 ]; the feasibility and challenges posed by NTDs with long incubation periods and diagnostic delays [ 20 ]; the impact of human movement on reaching and sustaining elimination efforts [ 27 ]; the relationship between cumulative exposure to infection and development of severe morbidity [ 28 ], and the use of serological surveys and force-of-infection models linked to frameworks of disease progression for quantifying spatio-temporal patterns of disease burden accounting for uncertainty at all steps of the proposed pipeline [ 29 ]. The linkage between NTD models and data have certainly improved considerably over the past decade, but lessons learnt from model construction on what should be measured to better understand the impact of given control interventions on infection, transmission and morbidity have yet to filter through to the practical design of most monitoring and evaluation programmes.…”