The spread of COVID-19 is incearsing day by day and it has put the entire world and the whole humankind at the stack. The assets of probably the biggest economies are worried because of the enormous infectivity, and transmissibility of this ailment. Because of the developing extent of the number of cases and its ensuing weight on the organization and wellbeing experts, some expectation strategies would be required to anticipate the quantity of evidence in the future. In this paper, we have utilized time series forecasting approach entitled autoregressive integrated moving average, and bend fitting for the forecast of the quantity of COVID-19 cases in Canadian Province for 30 days ahead. The estimates of different parameters (number of positive cases, number of recouped cases, and decrease cases) got by the proposed strategy is exact inside a specific range, and will be a beneficial apparatus for overseers, and wellbeing officials to organize the clinical office in the distinctive Canadian Province.
CITATION STYLE
Kamboj, V. K., Verma, C., & Gupta, A. (2020). Early Detection of Covid-19 in Canadian Provinces and its Anticipatory Measures for a Medical Emergency. SN Computer Science, 1(6). https://doi.org/10.1007/s42979-020-00347-0
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