Since early March 2020, solid lab has proactively contributed to data analytics, network science, risk management, and machine learning research for analysis, prediction, and exploration of COVID-19. In addition to our predictive dashboard that leverages data science to forecast the number of cases and provide a spatiotemporal visualization, we are actively working with network scientists, civil engineering, economists, and operational research collaborators on various aspects of COVID-19 related research. This page provides an overview of some parts of this research and the corresponding publications and findings:

 

1- Spatiotemporal predictive  dashboard to forecast and visualize COVID-19 cases using data analytics

[1] M. Hyman, A. Imteaj, & M. Hadi Amini, (2020). Data Analytics for COVID-19 Prediction; Available from: https://public.tableau.com/profile/solid.lab#!/vizhome/DataAnalyticsforCOVID-19Prediction/Covid-19Dashboard

[2] Meleik Hyman, Calvin Mark, Ahmed Imteaj, Hamed Ghiaie, Shabnam Rezapour, Arif M. Sadri, and M. Hadi Amin,. “Data analytics to evaluate the impact of infectious disease on economy: Case study of COVID-19 pandemic.” Patterns Journal (2021): 100315.

[3] Farid Ghareh Mohammadi, F. Shenavarmasouleh, M. Hadi Amini, and H.R. Arabnia, “Impact of Weather Conditions on the COVID-19 Pandemic in the United States: A Big Data Analytics Approach.” International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2020.

 

News Coverage: FIU News, FIU CEC, FIU CEC LinkedIn, FIU SCIS, FIU SCIS LinkedIn

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2- Economic Implications of COVID-19 (ongoing collaboration):

[4] M. Hadi Amini, M. Hyman, A. Imteaj, “Efficient Data Analytics For Interdependent Healthcare And Financial Networks: Tale Of Economic Shockwaves Caused By COVID-19”, INFORMS Annual Meeting 2020 session on Modeling Infection Propagation and Designing Surveillance Strategies.

 

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3- NSF-Sponsored Research Grant (ongoing project)

[5] Arif M. Sadri (PI), M. Hadi Amini (Co-PI), Understanding Community Response in the Emergence and Spread of Novel Coronavirus through Health Risk Communications in Socio-Technical Systems.

[6] Md Ashraf, Arif Mohaimin Sadri, and M. Hadi Amini, “Data-driven Inferences of Agency-level Risk and Response Communication on COVID-19 through Social Media based Interactions.” Journal of Emergency Management (2021). (Accepted for publication)

News Coverage: FIU News, FIU CEC,  FIU SCIS, FIU SCIS Twitter, FIU CEC LinkedIn