A Simulation Model for Forecasting COVID-19 Pandemic Spread: Analytical Results Based on the Current Saudi COVID-19 Data
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Omar Cheikhrouhou | Ahmad B. A. Hassanat | Sami Mnasri | Ghada Awad Altarawneh | Ahmad S. Tarawneh | Khaled Alhazmi | Mohammed A. Aseeri | Malek Alrashidi | Khalid Almohammadi | Hani Almoamari | O. Cheikhrouhou | M. Aseeri | A. Tarawneh | G. Altarawneh | Sami Mnasri | Khalid Almohammadi | Khaled Alhazmi | Malek Alrashidi | Hani Almoamari | Ahmad Hassanat
[1] Wenlian Lu,et al. Prediction of the Epidemic of COVID-19 Based on Quarantined Surveillance in China , 2020, medRxiv.
[2] Bruce Y. Lee,et al. The Potential Health Care Costs And Resource Use Associated With COVID-19 In The United States. , 2020, Health affairs.
[3] Petrônio C. L. Silva,et al. COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions , 2020, Chaos, Solitons & Fractals.
[4] Yonghong Xiao,et al. Host and infectivity prediction of Wuhan 2019 novel coronavirus using deep learning algorithm , 2020, bioRxiv.
[5] T. Rhodes,et al. A model society: maths, models and expertise in viral outbreaks , 2020, Critical Public Health.
[6] M. Baseer,et al. Knowledge, Attitudes, and Practices Toward COVID-19 in a Saudi Arabian Population: A Cross-Sectional Study , 2020, Cureus.
[7] Mikhail Prokopenko,et al. Modelling transmission and control of the COVID-19 pandemic in Australia , 2020, Nature communications.
[8] H. Alwafi,et al. Epidemiology of COVID-19 in the Kingdom of Saudi Arabia: An Ecological Study , 2020, Frontiers in Public Health.
[9] Enrique Herrera-Viedma,et al. Composite Monte Carlo decision making under high uncertainty of novel coronavirus epidemic using hybridized deep learning and fuzzy rule induction☆ , 2020, Applied Soft Computing.
[10] Gary E. Weissman,et al. Locally Informed Simulation to Predict Hospital Capacity Needs During the COVID-19 Pandemic , 2020, Annals of Internal Medicine.
[12] Hongguang Sun,et al. COVID-19 infection and recovery in various countries: Modeling the dynamics and evaluating the non-pharmaceutical mitigation scenarios. , 2020, 2003.13901.
[13] F. Chou,et al. From biological safety to social safety: How Taiwan’s community centered prevention program controlled the COVID-19 outbreak , 2020, Journal of global health.
[14] Tianyi Li. Simulating the spread of epidemics in China on multi-layer transportation networks: Beyond COVID-19 in Wuhan , 2020, EPL (Europhysics Letters).
[15] D. Ivanov. Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case , 2020, Transportation Research Part E: Logistics and Transportation Review.
[16] Matjaž Perc,et al. Forecasting COVID-19 , 2020, Frontiers in Physics.
[17] Chanjuan Sun,et al. The efficacy of social distance and ventilation effectiveness in preventing COVID-19 transmission , 2020, Sustainable Cities and Society.
[18] Ying Wang,et al. COVID-19 infection: the perspectives on immune responses , 2020, Cell Death & Differentiation.
[19] D. Cummings,et al. Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictions , 2020, medRxiv.
[20] Estrada Mario Arturo Ruiz. The Monitoring of COVID-19 Infected Cases by Continent under the Application of MDNIDC-Mapping Simulator , 2020 .
[21] A. S. Abdel-Moneim,et al. Knowledge and awareness of Middle East respiratory syndrome coronavirus among Saudi and Non-Saudi Arabian pilgrims , 2017, International Journal of Health Sciences.
[22] Nils Jakob Johannesen,et al. Relative evaluation of regression tools for urban area electrical energy demand forecasting , 2019, Journal of Cleaner Production.
[23] J. Leskovec,et al. Large-scale physical activity data reveal worldwide activity inequality , 2017, Nature.
[24] Angus M. Brown. A step-by-step guide to non-linear regression analysis of experimental data using a Microsoft Excel spreadsheet , 2001, Comput. Methods Programs Biomed..
[25] Jing Zhao,et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia , 2020, The New England journal of medicine.
[26] G. Leung,et al. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study , 2020, The Lancet.
[27] L. Fang,et al. Epidemiological parameters of COVID-19 and its implication for infectivity among patients in China, 1 January to 11 February 2020 , 2020, Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin.
[28] X. Wan,et al. Seasonal variations in Nigeria: understanding COVID-19 transmission dynamics and immune responses , 2020 .
[29] COVID-19 Outbreak in Pakistan: Model-Driven Impact Analysis and Guidelines , 2020, 2004.00056.
[30] R. Meyer,et al. The Fundamental Theorem of Exponential Smoothing , 1961 .
[31] C. Anastassopoulou,et al. Data-based analysis, modelling and forecasting of the COVID-19 outbreak , 2020, PloS one.
[32] M. Wang,et al. Epidemiological Parameters of COVID-19: Case Series Study , 2020, Journal of medical Internet research.
[33] Y. Hu,et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China , 2020, The Lancet.
[34] Dug Hun Hong,et al. Short-term load forecasting for the holidays using fuzzy linear regression method , 2005 .
[35] K. Koenig,et al. 2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus , 2020, The western journal of emergency medicine.
[36] Malek Alrashidi,et al. Energy-Efficiency Clustering and Data Collection for Wireless Sensor Networks in Industry 4.0 , 2020 .