Towards fast quantum cascade laser spectrometers for high-throughput and cost-effective disease surveillance

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