Alicia Alva

Alicia Katherine Alva Mantari (born 1977, Lima) is a Peruvian specialist in biomedical informatics and telemedicine. She holds a master's degree with focus on global health and has been actively involved in telemedicine projects since 2008, leading tele-diagnosis systems projects for diseases such as tuberculosis and melanoma.

For ten years, she was a member of the Bioinformatics and Molecular Biology Laboratory at Cayetano Heredia University (Universidad Peruana Cayetano Heredia; UPCH) . and studies on heavy metal contamination. Her contributions have supported the growth of telemedicine in Peru, improving access to healthcare for those in hard-to-reach regions.

Biography

Early years and education Alicia Alva studied in Alcides Spelucín Vega School in Callao, where she participated in mathematics competitions and developed an interest in science. Later on, she studied mathematics at the National University of Engineering (Universidad Nacional de Ingeniería; UNI), where she developed analytical and computational thinking.

In 2024, she participated in the creation of Yanadevn, an early dengue diagnostic system developed by researchers at the University of Sciences and Humanities in collaboration with UPCH and regional hospitals. The device uses CRISPR/Cas13 technology to detect the presence of dengue RNA in blood. Research and publications She co-authored the study "Implementation of a telediagnostic system for tuberculosis and determination of multi-drug resistance based on the MODS method in Trujillo, Peru". It focused on developing a remote diagnostic system for tuberculosis and multidrug resistance (MDR) using the MODS method. It optimized an image recognition algorithm to detect Mycobacterium tuberculosis in digital MODS culture images from the CENEX-Trujillo laboratory. Awards and recognitions She won the "Special Projects: COVID-19 Response" 2020 competition by Concytec for the SAMAYCOV project, a device designed to assess COVID-19 risk related to lung damage. She won the II National Innotec Competition 2010, for the development of a tele-diagnosis system for multidrug-resistant tuberculosis (TB-MDR), capable of providing results in less than 15 seconds.