Malaria is a significant health threat worldwide, especially in tropical and subtropical areas, where delayed or inaccurate diagnoses lead to persistent transmission or increased fatality rates. A rapid, precise, and label-free detection method is therefore crucial for timely intervention. This study proposes a highly sensitive Surface Plasmon Resonance (SPR) biosensor, whose performance was evaluated numerically for the early and precise detection of malaria infection. The sensor employs a multilayer architecture consisting of \(N-FK51A\) / \(TiO_2\) /Ag/ \(SiO_2\) /Blue Phosphorous (BP), engineered to enhance plasmonic excitation, light confinement, and analyte interaction. Numerical simulations based on the Transfer Matrix Method (TMM), supported by Finite Element Method (FEM) verification, were conducted to evaluate its optical response and sensing performance. The optimized configuration achieved a maximum angular sensitivity of 502.2857 deg./RIU, FWHM of 3.138, figure of merit (FOM) of 562.79 \(\hbox {RIU}^{-1}\) , signal-to-noise ratio (SNR) of 1.12, detection accuracy (DA) of 0.46 \(\hbox {deg}^{-1}\) , and a quality factor (QF) of 160.06 \(\hbox {RIU}^{-1}\) . The BP layer demonstrated superior plasmon-analyte coupling compared to other 2D materials, significantly improving resonance sharpness and detection accuracy. A comparison analysis employing TMM and FEM validates the model’s accuracy and reliability. The proposed sensor demonstrates significantly higher sensitivity and reliability when compared to previously reported SPR sensors. The findings indicate that the sensor configuration presents a viable approach for next-generation, label-free, and non-invasive biosensing for rapid malaria diagnosis.
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