Advancing Localized Public Health Surveillance in Malaysia by Enhancing EIOS with Google COVID-19 Data Integration

Epidemic intelligence has evolved from traditional manual reporting and field investigation methods to dynamic, real-time surveillance, driven by the 21st-century surge in digital data sources. Infectious diseases pose a significant global health threat, with traditional surveillance methods often facing delays in detecting and responding due to reliance on structured clinical data. The Covid-19 pandemic has emphasized the need for precise and actionable data to inform public health decisions. The current categorization of the Epidemic Intelligence from Open Sources (EIOS) system by country limits its ability to precisely track and monitor infectious diseases at more localized levels. This study focuses on enhancing the EIOS system by improving geographic data specifically for Malaysia. Currently, the EIOS platform, which incorporates data sources from Johns Hopkins University (JHU), the World Health Organization (WHO), and the Worldometers (WOM), provides country-level data that limits the effectiveness of localized interventions. This enhancement involves integrating state-level data in Malaysia from the Google Covid-19 Open Data Repository, which collects data automatically from authoritative sources, volunteers and contributors into the EIOS system. This paper presents the focus in Malaysia for better precision and effectiveness, in public health interventions. The suggested EIOS system will assist in sorting data based on dates,cases numbers,fatalities and data origins resultng in a more intricate and adaptable depiction of the pandemics advancement. The results of this study will offer insights and improvements for public health experts in Malaysia regarding the management and containment of infectious diseases at a local level.It will help optimize resource distribution and readiness efforts to mitigate the effects of outbreaks effectively.This improvement is intended to support targeted lockdowns and other public health interventions, in geographic areas with greater precision by enhancing geographical tracking capabilities.