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COVID pandemic analysis using Auto- Regression-Based moving average method.
Gupta, Sangeeta; Ramadevi, Y; Agarwal, Kavita; Shekhar Yadav, Chandra.
Afiliación
  • Gupta S; Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana, India.
  • Ramadevi Y; Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana, India.
  • Agarwal K; Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana, India.
  • Shekhar Yadav C; STQC, Hyderabad, Telangana, India.
Mater Today Proc ; 2021 Feb 25.
Article en En | MEDLINE | ID: mdl-33654660
ABSTRACT
COVID (Corona Virus) 2019 proved to be a pandemic worldwide, with more than 30 lakhs of life's in danger and more than 2 lakh people dead as of 01 May 2020. The disease is spreading across the world in various phases, with assumptions of having an impact based on the weather conditions, where the true reason is not yet confirmed. However, several precautionary measures such as maintaining social distancing, covering mouth and hands using masks and gloves, avoiding huge public gatherings to attend conferences, meetings, worship places, etc proved to put a pause on the spread of this air-borne contagious disease. Though there is an impact on the overall economy world-wide, lockdown is strictly implemented in countries like India and also at various other places to control the spread and save several lives. There is a necessity to track the spread to find out the rate at which the virus is spreading and accordingly taking measures to control the same. This work presents an analysis of the growth rate and death rate of the COVID pandemic in developing countries like India using the Auto regression-based Moving Average method. The results presented in this work show the future predictions analyzed via the proposed model and drives a path to take preventive measures accordingly and curb the COVID spread.
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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Mater Today Proc Año: 2021 Tipo del documento: Article País de afiliación: India

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Mater Today Proc Año: 2021 Tipo del documento: Article País de afiliación: India