Direction of Enhancing Epidemic Intelligence From Open Source (EIOS) For Localized COVID-19 Management in Malaysia

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. Thus, this paper aims to refine the geographic scope in Malaysia to enable more targeted and efficient public health responses. The proposed EIOS system will also support filtering data by date, case numbers, death counts, and data sources, offering a more detailed and customizable view of the pandemic's progression. The outcome of this research will provide an enhancement and valuable insights into the local spread and control of infectious diseases for public health professionals in Malaysia, allowing better resource allocation and preparedness and ultimately reducing the overall impact of future outbreaks. This enhancement aims to facilitate lockdowns and other public health measures within smaller, more precisely defined areas by enabling more detailed geographic tracking.