1. Improvement of diagnostic strategies, access to health care, and treatment
2. Assessment of myocardial inflammation as a surrogate marker of clinical response
3. Validation of biomarkers of cure in a cohort of patients

1. The use of digital health and AI tools on a large scale and implementation science methods may overcome the barriers to identifying and treating CD patients, improving the health care system, with potential impact on morbidity and mortality related to CD.
2. Treatment with benznidazole can improve myocardial inflammation in patients with CD at the early stage of heart disease measured with advanced cardiac imaging techniques (magnetic resonance T1 and T2 mapping, PET-Scan), and also that plasma biomarkers will associate with improvement of myocardial inflammation.
3. Establishing a prospective cohort of well-characterized patients with CD treated with benznidazole, together with the data and samples collected will allow validating potential biomarker candidate.

The aims will be assessed using a variety of methods. First, a mixed methods project applying semi-structured interviews and develop focus groups (FG) with health care professionals (primary care physician, nurses, community health workers) from the three study cities. Additionally, a prospective, longitudinal, cohort of patients with CD will be treated and followed to assess the effect of benznidazole among inflammatory tissular foci on the myocardium and to assess a panel of biomarkers. For systemic correlates of inflammation during treatment, we will use omics strategies to identify markers of cardiac inflammation and response to treatment. Finally, a prospective cohort of treated patients will be established. Biomarkers that have presented a better correlation with the endpoint based on cardiac images will be selected to further validate in a subgroup of patients.

• Implementation Science – Intervention strategies were developed using the Behaviour Change Wheel (BCW) framework, emphasizing educational programmes, hands-on training, and infrastructural improvements to identify key barriers, including limited awareness of ChD among healthcare professionals, reliance on symptomatic diagnosis, environmental constraints, and inadequate public and professional engagement with ChD. This approach addresses healthcare workers’ challenges, fostering a more proactive and informed ChD management strategy.
• IA for Chagas detection – Creation and validation of an AI algorithm capable of suggesting infection of Chagas disease. The joining of AI-ECG and epidemiological risk factors analysis significantly improved the diagnostic discrimination and the individual risk reclassification compared with the epidemiological data alone.
• Develop a decision support system – A decision support system was developed as a mobile and computer application to assist in determining the most appropriate treatment for patients with Chagas disease.
• Use of advanced cardiovascular imaging to detect response to antiparasitic treatment – Application of new cardiac imaging techniques (CMR and PET-CT) in Chagas disease using miocardial inflammation as an outcome surrogate to identify biomarkers correlating with response to anti-parasitic treatment.
• Establishment of the largest Chagas cohort after treatment for Chagas disease – Establish a longitudinal, open, and multicenter cohort of patients with T. cruzi infection treated with (some?) anti-trypanocidal drug.
• Training people – Each center hosts its own postgraduate program, and the students are using SaMi-Trop data and samples for their theses, dissertations and other scientific documents.

• SickKids-Centre for Global Child Health Collaboration – We established a collaborative study with the SickKids-Centre for Global Child Health; Canada, to investigate the potential of autoantibodies against cardiac proteins as biomarkers for Chagas Cardiomyopathy and to assess the impact of benznidazole treatment on autoantibody levels to identify diagnostic and treatment-specific signatures for Chagas Cardiomyopathy.
• The McGill Institute Collaboration – We are establishing a group with researches of The McGill Institute, Canada, to collaborate in the CMR images review and interpretation. This collaboration opens good perspectives, given the outstanding expertise of these researches in advanced CMR techniques.
• Novartis and DNDi Collaboration – We established a collaborative study with Novartis and DNDi, that will fund a proteomics study utilizing samples and data from the SaMi-Trop cohort.
• UNIMONTES Clinical Trial Center – The UNIMONTES team successfully established a clinical trial center focused on ChD and it has already participated in four clinical trials.
• Triatochat Project – Samitrop supported the formation of a Chagas association in Montes Claros, named Triatochat Project that aims to strengthen health education, support entomological surveillance of Chagas disease, and bring science closer to the community.