The epidemic trend of COVID-19 in SAARC countries: a predictive modelling and analysis
Keywords:COVID-19 cases, Logistic model, Best fit, Growth rate parameter, Inflection point, Predictive cases
This paper aims to integrate novel coronavirus daily cases in SAARC countries; India, Pakistan, Bangladesh, Nepal, Sri Lanka, Afghanistan, Maldives and Bhutan to forecast the epidemic trend of COVID-19 by using logistic model. The recent trend of coronavirus cases were analyzed from the COVID-19 epidemiological data for SAARC countries from 23 January 2020 to 31 May 2021. The final size, growth rate parameter and point of inflection of COVID-19 for each countries were calculated by fitting the logistic curve with the cumulative cases. The graphical patterns of COVID-19 daily cases reflect that its second wave impact is more devastating than the first wave in SAARC countries. The increasing trend of COVID-19 cases in these countries was well described by logistic model with coefficient of determination greater than 0.96. The predictive final size of the second wave infections is maximum for India which is 19.8 million with growth rate parameter of 0.08 and inflection time of 68 days whereas the predictive final size is minimum for Afghanistan which is 0.041 million with growth rate parameter of 0.06 and inflection time of 71 days. The logistic model is helpful in predicting the trajectory of the infected cases in a country if the current scenario of this type of infectious disease remains same. Also, it helps the government to frame policy decisions and necessary actions that controls the transmission of COVID-19 in the South Asian region.