Covid-19 Decision Making Intelligence during Disasters Management

Autor: Anita Ismail, Rosmah Mat Isa, Farah Laili Muda @ Ismail, Ainulashikin Marzuki, Nurzi Juana Mohd Zaizi, Nur Fatin Nabila Mohd Rafei Heng, null Sakinah Ahmad
Rok vydání: 2021
Zdroj: Ulum Islamiyyah. 33:41-49
ISSN: 2289-4799
1675-5936
DOI: 10.33102/uij.vol33nos4.433
Popis: As the coronavirus (COVID-19) spreads from China to neighbouring areas and beyond, increased national and international efforts are underway to contain the epidemic. Humanity is increasingly confronted with a diverse array of man-made and natural disasters. While emergency circumstances cannot be avoided, they may be managed more efficiently. Effective emergency management requires thorough planning, informed reaction, and well-coordinated actions throughout the emergency management life cycle. According to the literature, data-driven emergency management information systems that are well-integrated help in disaster management operations. Recent advances in molecular and computational techniques, as well as in information and communication technologies (ICTs), artificial intelligence (AI), and Big Data, can assist in managing the massive, unprecedented amount of data generated by public health surveillance, real-time epidemic outbreak monitoring, trend nowcasting/forecasting, routine situation briefing and updating from governmental institutions and organisms, and health facility utilisation. This study could be tailored to assist organisations in adapting to their new normal.
Databáze: OpenAIRE