Author: Yao Yu Yeo; Yao-Rui Yeo; Wan-Jin Yeo
Title: A Computational Model for Estimating the Progression of COVID-19 Cases in the US West and East Coasts Document date: 2020_3_27
ID: 8g64u3ux_59
Snippet: There are currently no predictive models that satisfactorily produce a picture of the spread or clinical impact of the disease as too many variables can affect the spread of a disease, especially for pandemics like COVID-19. Moreover, simulations can vary noticeably with small variations in assumptions and parameters. To cite one example, minor changes in the distribution of the infected population between and can dramatically affect the model's .....
Document: There are currently no predictive models that satisfactorily produce a picture of the spread or clinical impact of the disease as too many variables can affect the spread of a disease, especially for pandemics like COVID-19. Moreover, simulations can vary noticeably with small variations in assumptions and parameters. To cite one example, minor changes in the distribution of the infected population between and can dramatically affect the model's predictions. Also, at the societal level, the length of time that the cohort of patients remain hospitalized is often unknown in the early stages of a pandemic, and can greatly influence the use and deployment of medical supplies and personnel, thus altering the course of the infection and recovery rates.
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