Peru: AI-Powered Cough Monitoring for Early Respiratory Infection Detection
Photo Credit: Feepik
Overview
Respiratory infections spread fastest where they are hardest to detect inside households, long before a clinic visit. In Peru, where contagious diseases like tuberculosis continue to burden communities, the gap between first symptom and formal diagnosis creates windows for transmission that weaken even well-resourced health systems.
This project deploys an AI-based cough-monitoring tool to support early screening and detection of contagious respiratory infections at the household level. By analysing longitudinal cough data from patients and their close contacts, the system builds a continuous picture of infection risk enabling timely alerts before disease spreads further. The approach is designed with equity in mind, exploring how scalable, low-barrier surveillance tools can reach populations that conventional health infrastructure routinely misses.
The implications extend beyond individual households. Stronger early-warning capacity at the community level means better outbreak preparedness across the Peruvian health system.