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Mycetoma is a neglected tropical disease characterised by chronic, destructive infections of subcutaneous tissues, predominantly affecting populations in endemic regions with limited healthcare resources. Delayed diagnosis, limited treatment options, and restricted access to specialised healthcare contribute to substantial morbidity, disability, and socioeconomic burden. Digital technologies offer promising opportunities to address these challenges and improve mycetoma care. Artificial intelligence (AI) can support early detection and diagnostic accuracy through the analysis of clinical images, radiological findings, and patient data. Telemedicine can facilitate remote specialist consultations and follow-up, particularly in rural and underserved communities, while electronic health records enable systematic data collection, disease surveillance, and monitoring of treatment outcomes. Mobile health applications can improve patient education, symptom monitoring, and treatment adherence, whereas computational drug discovery may accelerate the identification of potential therapeutic agents. Furthermore, digital platforms can strengthen international research collaborations, knowledge exchange, and capacity building. However, implementing these technologies in endemic regions faces significant barriers, including inadequate digital infrastructure, limited internet connectivity, insufficient digital literacy, data privacy concerns, and ethical challenges related to informed consent, data ownership, and algorithmic decision-making. Addressing these barriers requires investment in infrastructure, appropriate regulatory frameworks, stakeholder collaboration, and context-specific capacity-building initiatives. Integrating digital health solutions into national healthcare strategies could support sustainable and equitable improvements in mycetoma management. This review highlights the potential applications, opportunities, and challenges of digital technologies in mycetoma care and emphasises the need for inclusive, locally adapted approaches to enhance early diagnosis, treatment outcomes, research, and health equity in endemic communities.
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Zamel et al. (2026) studied this question.
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