Practical diagnostic algorithms for Chagas disease: a focus on low resource settings

ABSTRACT

Introduction

Chagas disease, caused by parasite Trypanosoma cruzi, is the most important neglected tropical disease in the Americas. Two drugs are available for treatment, but access to them is challenging, in part due to complex diagnostic algorithms. These are stage-dependent, involve multiple tests, and are ill-adapted to the reality of vast areas where the disease is endemic. Molecular and serologic tools are used to detect acute and chronic infections, with the performance of the latter showing geographic differences. Breakthroughs in the development of new diagnostic tools include the validation of a loop-mediated isothermal amplification assay for acute infections (T. cruzi-LAMP), and the regional validation of several rapid diagnostic tests (RDTs) for chronic infection, which simplify testing in resource-limited settings. The literature search was carried out in the MEDLINE database until 1 August 2023.

Areas covered

This review outlines existing algorithms, and proposes new ones focused on point-of-care testing.

Expert opinion

Integrating point-of-care testing into existing diagnostic algorithms in certain endemic areas will increase access to timely diagnosis and treatment. However, additional research is needed to validate the use of these techniques across a wider geography, and to better understand the cost-effectiveness of their large-scale implementation.

KEYWORDS:

• Chagas disease
• Trypanosoma cruzi
• diagnosis
• ELISA
• RDTs
• PCR
• LAMP
• point-of-care

Article highlights

• Current diagnostic algorithms of T. cruzi infection are complex and dependent on the clinical stage, severely limiting access to treatment.

• Conventional molecular techniques, such as PCR/qPCR outperform parasitological methods for the diagnosis of acute and congenital infections. However, they are restricted to reference centers, or research settings, being unavailable in most endemic areas.

• The diagnosis of chronic infections relies on the use of repeated serologic assays, including ELISA, IIF, and/or IHA. While the algorithm for serological detection is remarkably sensitive, it is complex and entails long turnaround times, compromising the access of patients to treatment.

• The incorporation of recently developed point-of-care alternatives to conventional molecular (the LAMP) and serologic methods (the RDTs) into existing algorithms will increase access to timely diagnosis and treatment.

• Particularly, the use of LAMP would have a major impact facilitating the identification and timely treatment of congenital infections.

• The heterogenous immune response elicited by patients from different regions in the Americas to an equally diverse set of parasite antigens still limits the widespread use of RDTs.

• Diagnostic programs based on these techniques are necessary to evaluate the impact and cost of such strategy.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers in this manuscript have no relevant financial or other relationships to disclose.

Author contribution statement

All authors contributed to the first draft of the manuscript and further revision. N.M.-P., E.E., and J.C.G.-F created key figures and tables for the paper. All authors agreed on the final version of the manuscript.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/14787210.2023.2279110

Additional information

Funding

AGS and JAP would like to acknowledge the support of the GHIT Fund to the [G2020-203] ChagasLAMP project (https://www.ghitfund.org/investment/portfoliodetail/detail/184/en). The work of N.M.-P., J.C.G.-F., and J.G. was supported by the ISCIII project PI18/01054. Our work is also supported by CIBER - Consorcio Centro de. Investigación Biomédica en Red - (CB 2021), Instituto de Salud Carlos III, Ministerio de Ciencia e. Innovación and Unión Europea – NextGenerationEU. We also acknowledge the support from the grant [CEX2018-000806-S] funded by MCIN/AEI/10.13039/501100011033, and support from the Generalitat de Catalunya through the CERCA Program. J.C.G.-F. received support through a fellowship from “la Caixa” Foundation [ID 100010434, fellowship code: LCF/BQ/DI21/11860037]. We also acknowledge the Generalitat of Catalonia Universities and Research Department, Spain [AGAUR: 2021 SGR 01562].