1. What kind of data analytics is this?

 

The kind of data analytics that the HIDE system uses is LAMP methods (Logic, Analytics, Measure, and Process). This is because Malaysia's Health Minister has introduced a LAMP Analytics policy. In terms of effects, efficacy, and performance, LOGIC aids HIDE in facilitating more targeted and proactive acts in the future. They discovered that only 0.2 percent of MySejahtera premises account for roughly 90% of COVID-19 transmissions in Malaysia. These findings aid relevant authorities in better allocating compliance resources, reducing the need for blanket interventions to combat the COVID-19 pandemic—analytics and Measures aid in discovering answers in results, focusing on statistics and analysis design. The Crisis Preparedness and Response Centre (CPRC), a unit under the Ministry of Health that includes officers from different Ministries and Government agencies, established and manages the HIDE system. This is consistent with the whole-of-government approach to managing the pandemic while minimising work and income losses. HIDE (Hotspot Identification for Dynamic Engagement) is a Big Data Analytics and AI framework that uses machine learning to predict the MySejahtera locations at risk of being COVID-19 hotspots over seven days. To make these forecasts, the framework uses MySejahtera check-ins and other current healthcare databases. In Process, using the data obtained from the HIDE method, the minister can process actionable insights and establish strategies for making successful decisions. Based on backward and forward contact tracing using MySejahtera check-in data, the HIDE System assists in identifying a significant number of individuals who may have been exposed to COVID-positive individuals who have visited the premises and are listed on the HIDE system. Early intervention efforts may aid in reducing transmission and preventing cluster formation.