Towards Fast Quantum Cascade Laser Spectrometers for High-Throughput and Cost-Effective Disease Surveillance

Abstract

Fourier transform infrared (FTIR) spectroscopy, coupled with machine learning (ML) analysis can be used for disease monitoring with high speed and accuracy, including the classification of mosquito samples by species, age and malaria detection. However, current FTIR instruments use low-brightness thermal light sources to generate infrared light, which limits their ability to measure complex biological samples, especially where high spatial resolution is necessary, such as for specific mosquito tissues. Moreover, these systems lack portability, which is essential for field applications. To overcome these issues, spectrometers using quantum cascade lasers (QCLs) have become an attractive alternative for building fast, and portable systems due to their high electrical-to-optical efficiency, small size, and potential for low-cost. Here, we present a QCL-based spectrometer prototype designed for large scale, low-cost, environmental field-based disease surveillance.