AI-based Monitoring and Response System for Hospital Preparedness towards COVID-19 in Southeast Asia

TL;DR

This paper presents an AI-driven system using Twitter data to monitor hospital surge capacity and equipment shortages during COVID-19 in Southeast Asia, aiding resource allocation and preparedness.

Contribution

It introduces a novel approach leveraging social media data to estimate hospital burden and resource shortages in regions lacking comprehensive official data.

Findings

Accurately predicts hospital surge in Indian states

Demonstrates potential for real-time monitoring using Twitter data

Supports resource planning in Southeast Asian countries

Abstract

This research paper proposes a COVID-19 monitoring and response system to identify the surge in the volume of patients at hospitals and shortage of critical equipment like ventilators in South-east Asian countries, to understand the burden on health facilities. This can help authorities in these regions with resource planning measures to redirect resources to the regions identified by the model. Due to the lack of publicly available data on the influx of patients in hospitals, or the shortage of equipment, ICU units or hospital beds that regions in these countries might be facing, we leverage Twitter data for gleaning this information. The approach has yielded accurate results for states in India, and we are working on validating the model for the remaining countries so that it can serve as a reliable tool for authorities to monitor the burden on hospitals.