The Covid-19 or Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2) virus causes ongoing global pandemic impacting human causalitiesand economicrecession. OnMarch 11th, 2020, the World HealthOrganization (WHO) declared fromepidemicto bea global pandemic. This virus is very infectious fromhuman to human through airborne and aerosols that are mostly spread by coughs and sneezes. The infected people commonly get symptoms of fever, respiratory illness, diarrhea, and pneumonia, however, around half of the infected people do not feel any symptoms. Despite having no signs ofillness, the SARS-Cov-2 virus in these people remainsactive and transmits to other people. Moreover, due to virus mutation, three new Covid-19 strains have recently been found in United Kingdom, United States and South Africa that are ten times more contagious than the initial virus strain. All these accumulated developments of Covid-19 virus have caused 103 million coronavirus cases with 2,22 million people deaths by January 30th, 2021. Alargeimplication ofthis global pandemicturns to be much less businessactivities dueto lockdown or large-scalesocial distancing restrictions. This research focuses on the characterizations of Covid-19 virus transmissions and mitigation efforts by using advanced information technologies that comprises five research work packages or research objectives. The first task aims at characterizing the Covid-19 epidemiology using mathematical modelling methods of infectious disease, namely SIR, MSIR, SEIS, and/or SEIR compartmental methods as well as the techniques permitting for a mixed modelling of the efficacy of the available Covid-19 vaccines and herd immunity. Secondly, this research will contribute on detecting Covid-19 virus spread behavior similarity with spatio-temporalepidemiologicalcharacteristics usingAI and machine learning techniques, such as self-organizing features map (SOFM), convolutional deep neural network (CDNN), chaos theory (CT), and othercomputational intelligence techniques. The third research work package has a main task on predicting the Covid-19 epidemiological growth or reproduction numbers using advanced data-driven modelling and time series prediction techniques that can simulate the dynamical characteristics of Covid-19 transmission under various mitigation controls. Subsequently, the research on building an automated face recognition to prevent Covid-19 transmissions in work and public places will be carried out by checking the conformance towards the standard safety and health protocols against Covid-19 virus transmission. Lastly, the fifth research work package aims at developing immersive dashboard and intelligent data analytics for more interactive and detailed analysis of the Covid-19 transmission behaviors and advanced modelling results in provisioning more reliable and accurate Covid-19 decision supportsystem. The latter research objective will be one of the main research project deliverables, which provide immersive dashboard and intelligent data analytics for Covid-19 decision support system. This integrated and comprehensive system will consist of the modelling results from the first until fourth research work packages and observation data, which allows for more

Covid-19, Global Pandemic, Virus Transmission Protocols

• Samuel Mahatmaputra Tedjojuwono, S.Kom., M.Info.Tech

• Dr. Michael Baskara Laksana Adi Siek, S.Si., S.Kom., M.Sc.