_____________________________________________________________________________________________________ *Corresponding author: E-mail: SaraeeD@cardiff.ac.uk; Journal of Advances in Medicine and Medical Research 33(5): 8-21, 2021; Article no.JAMMR.65476 ISSN: 2456-8899 (Past name: British Journal of Medicine and Medical Research, Past ISSN: 2231-0614, NLM ID: 101570965) Literature Review on Epidemiological Modelling, Spatial Modelling and Artificial Intelligence for COVID-19 Danial Saraee 1* and Charith Silva 2 1 School of Medicine, UHW Main Building, Heath Park, University of Cardiff, England. 2 School of Science, Engineering and Environment, University of Salford, England. Authors’ contributions This work was carried out in collaboration among both authors. Author DS designed the study, performed the data collection, analysis, interpretation and wrote the first draft of the manuscript. Author CS contributed on data analysis and interpretation. Author DS managed the literature searches. Both authors read and approved the final manuscript. Article Information DOI: 10.9734/JAMMR/2021/v33i530841 Editor(s): (1) Dr. Rameshwari Thakur, Muzaffarnagar Medical College, India. (2) Dr. Emin Umit Bagriacik, Gazi University, Turkey. (3) Dr. Syed Faisal Zaidi , King Saud bin Abdulaziz University for Health Sciences, Kingdom of Saudi Arabia. Reviewers: (1) Zakir Hussain, FELTP,Pakistan. (2) Jean Pierre NAMAHORO, China University of Geosciences, China. (3) R Kesavan, University of Jaffna, Sri Lanka. Complete Peer review History: http://www.sdiarticle4.com/review-history/65476 Received 25 January 2021 Accepted 07 March 2021 Published 16 March 2021 ABSTRACT Introduction: Following the outbreak of Coronavirus (COVID-19) in Wuhan, China in December 2019, the World Health Organisation (WHO) has declared this infectious disease as a pandemic. Unlike previous infectious outbreaks such as Severe Acute Respiratory Syndrome (SARS) and Middle Eastern Respiratory syndrome (MERS), the high transmission rate of COVID-19 has resulted in worldwide spread. The countries with the highest recorded incidence and mortality rates are the US and UK. Rationale/Objective: This review will compare studies that have used epidemiological models for disease forecasting and other models that have identified sociodemographic factors associated with COVID-19. We will evaluate several models, from basic equation-based mathematical models to more advanced machine-learning ones. Our expectation is that by identifying high impact models used by policy makers and discussing their limitations, we can identify possible areas for future research. Review Article