Coronavirus Disease 2019 (COVID-19): Forecast of an Emerging Urgency in Pakistan

Abstract

Background/Aims Novel coronavirus disease 2019 (COVID-19) is a global challenge due to little available knowledge and treatment protocols. Thus, there is a great need for collecting data related to COVID-19 from all around the world. Hence, we conducted this study, collecting daily data on COVID-19, to map the epidemiology outbreak and forecast its trajectory for May 2020. Methodology The data was collected from the officially released reports of the National Institute of Health (NIH), Pakistan, and the World Health Organization (WHO). The analysis was done using Statistical Package for the Social Sciences (SPSS) version 23 (IBM Corp., Armonk, NY), and forecasting was done using a simple moving average in time series modeler/expert modeler. Results The purpose of this study is to draw the attention of international, as well as national, governing bodies to the rapidly rising number of COVID-19 cases in Pakistan, and the urgency of evaluating the efficacy of the currently implemented strategy against COVID-19. According to this study, there is now an alarming increase in the number of COVID-19 patients in Pakistan, despite a contained spread in the beginning. The predicted number of COVID-19 cases can go over 35,000 by the end of May 2020. Conclusion It is crucial for governing bodies, administrators, and researchers to re-evaluate the current situation, designed policies, and implemented strategies.

A review on COVID-19 forecasting models

“…Machine learning algorithms exhibit many pros and cons, which are described in Table 3. [19,22,26,30,31] Genetic programming [30][31][32][33][34] Simple moving average [23] Other models [35] SEIR [12,36] Exponential models Logistic growth model [24,37,38] Flower pollination algorithm [29] SIRD [13,14] Deep learning Long short-term memory (LSTM) networks [25] Polynomial Neural Network [39] Neural network [31,40] Ecological Niche models [41] Regression methods [42][43][44] Prophet algorithm [45] Phenomenological model [46] Other models Adaptive neurofuzzy inference system [29] Regression tree algorithm [22] Support vector machine [39,47] Iteration method [48] Support vector Kuhntucker [47] 10…”

A Review on COVID-19 Forecasting Models

“…The SMA model is defined as the unweighted mean of the previous data (in finance or in science & engineering) (Sprinthall and Fisk 1990). Example of application of simple moving average in COVID-19 could be found in (Chaudhry, Hanif et al 2020).…”

“…Chakraborty and Ghosh (2020) presented a realtime forecast of confirmed COVID-19 cases for several countries as well as risk assessment of the novel COVID-19 for some affected territory using regression tree algorithm. A simple movingaverage approach was used by(Chaudhry, Hanif et al 2020) to predict COVID-19 confirmed cases in Pakistan (Chen, Chen et al 2020Cheng, Burcu et al (2020).…”

Pandemic induced uncertainties, challenges and threats to developing countries: A case study of Pakistan

“…So would the administration's help bundle, which is just digressively centered on modern quality, effectively rescue enterprises. Chaudhry et al, (2020).…”