Outbreak Anticipation System – JPS
Lever
Use of data, telehealth and new technologies
Grant type
Model Development
Beneficiary population
Residents of the nine capital cities of the Northeast region.
Developed by the Oswaldo Cruz Foundation (Fiocruz), with support from the Molecular Biology Institute of Paraná (IBMP), the *Sistema de Antecipação de Surtos* – AESOP (Outbreak Anticipation System) uses artificial intelligence to identify respiratory syndrome outbreaks early and support faster, more targeted healthcare system responses.
The platform analyzes Primary Health Care (PHC) data and complementary information—such as over-the-counter medication sales and socioeconomic and bioclimatic indicators—to generate geographically localized alerts. The solution strengthens health surveillance and enables the mapping of areas with a higher risk of outbreak dissemination.
In 2025, anomaly detection algorithms for PHC appointments were developed and validated. The system was also made available to teams from the Ministry of Health’s Secretariat of Health and Environmental Surveillance, as well as the state and municipal Health Secretariats of Amazonas and Bahia. By the end of the year, AESOP was already issuing weekly alerts to 2,243 municipalities in the North and Northeast regions.
The initiative seeks to validate a platform for predicting new pandemic outbreaks (Alert-Early System of Outbreaks with Pandemic Potential / AESOP), based on artificial intelligence. The system monitors data from Primary Health Care (PHC) and other sources such as: the number of health visits related to specific symptoms, hospital admissions, pharmacy purchases of medications, and the circulation of rumors on social media and in news outlets.
progress in the development of the Real-Time Monitoring System and anomaly detection algorithms (based on PHC data, medication sales and machine learning models)
levels of management gained access to the system: the Ministry of Health, state health departments, and municipal health departments.