Intelligent Early Warning and Response System Based on Health System Routine Data and Environment Data to Improve National Health Resilience

Artificial intelligence (AI) has the potential to revolutionize pandemic preparedness. It can be used to analyze various data sources to identify patterns and anomalies that may indicate the presence of a new infectious disease. Our proposed research is using AI techniques to help with predicting outbreaks, contact tracing, resource allocation, monitoring compliance, and modeling the spread of the pathogen using social interaction and mobility data. Social interaction and mobility data are data from social media, public transportation, and mobile phone usage that record anonymous mobility data such as Google Community Mobility Data and Apple Mobility Data. However, our research does not limit itself to social interaction and mobility data utilization. Indonesia’s Ministry of Health also has various information systems that collect infectious disease-related cases, such as the EWARS application and PeduliLindung which collect citizen mobility data during pandemics.