AFFORDABLE INFECTIOUS DISEASE BIOSENSORS FOR FINANCIALLY SUSTAINABLE HEALTHCARE: A CONCEPTUAL FRAMEWORK INTEGRATING GREEN FINANCE READINESS AND AI-BASED DECISION SUPPORT

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

Infectious diseases continue to place a major clinical and financial burden on healthcare systems, particularly in low-resource settings where access to timely and affordable diagnosis remains limited. Conventional diagnostic methods such as polymerase chain reaction, enzyme-linked immunosorbent assay, microbial culture, and centralized laboratory testing are accurate but often expensive, time-consuming, infrastructure-dependent, and difficult to implement in rural and underserved areas. Delayed diagnosis can increase disease transmission, hospitalization, treatment costs, and pressure on public health systems. In this context, affordable infectious disease biosensors offer a promising pathway for rapid, low-cost, decentralized, and point-of-care diagnosis. This article develops a conceptual framework explaining how affordable biosensor-based diagnostic solutions can contribute to financially sustainable healthcare. The framework is built around six readiness dimensions: technological readiness, financial readiness, environmental readiness, digital readiness, governance and compliance readiness, and supply-chain readiness. It also proposes the use of a Green Finance Readiness Index to assess whether biosensor-based healthcare innovations are suitable for sustainable financing, ESG investment, and large-scale implementation. In addition, the article highlights the role of artificial intelligence-enabled decision support in interpreting biosensor signals, classifying diagnostic results, reducing human error, improving prediction accuracy, and supporting real-time disease surveillance. The article argues that biosensor-based diagnostics can reduce diagnostic delays, lower healthcare expenditure, minimize hospitalization, improve healthcare accessibility, strengthen outbreak surveillance, and support universal health coverage. By integrating green finance readiness and AI-enabled decision support, affordable infectious disease biosensors can be positioned as clinically useful, economically viable, environmentally sustainable, and socially accessible healthcare innovations. Future research should empirically validate the proposed framework using real patient samples, clinical testing, healthcare cost data, AI-based biosensor signal datasets, regulatory assessment, and field-level implementation studies.

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Keywords

Infectious disease biosensors; financial sustainability; point-of-care diagnostics; green finance readiness; artificial intelligence; healthcare innovation; sustainable healthcare.