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http://dx.doi.org/10.22937/IJCSNS.2021.21.1.24

Modeling Exponential Growth in Population using Logistic, Gompertz and ARIMA Model: An Application on New Cases of COVID-19 in Pakistan  

Omar, Zara (Department of Statistics, University of Karachi.)
Tareen, Ahsan (Capra Timber Private Limited)
Publication Information
International Journal of Computer Science & Network Security / v.21, no.1, 2021 , pp. 192-200 More about this Journal
Abstract
In the mid of the December 2019, the virus has been started to spread from China namely Corona virus. It causes fatalities globally and WHO has been declared as pandemic in the whole world. There are different methods which can fit such types of values which obtain peak and get flattened by the time. The main aim of the paper is to find the best or nearly appropriate modeling of such data. The three different models has been deployed for the fitting of the data of Coronavirus confirmed patients in Pakistan till the date of 20th November 2020. In this paper, we have conducted analysis based on data obtained from National Institute of Health (NIH) Islamabad and produced a forecast of COVID-19 confirmed cases as well as the number of deaths and recoveries in Pakistan using the Logistic model, Gompertz model and Auto-Regressive Integrated Moving Average Model (ARIMA) model. The fitted models revealed high exponential growth in the number of confirmed cases, deaths and recoveries in Pakistan.
Keywords
Logistics; Gompert; ARIMA; Pakistan; Covid-19; time series; NIH;
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