Estimating the size of COVID-19 epidemic outbreak

Abstract

In this work, we analyze the epidemic data of cumulative infected cases collected from many countries as reported by WHO starting from January 21st,2020 and up till March 21st,2020. Our inspection is motivated by the renormalization group (RG) framework. Here we propose the RG-inspired logistic function of the form αE(t) = a(1 + ec(t-t0))-n as an epidemic strength function with n being asymmetry in the modified logistic function. We perform the non-linear least-squares analysis with data from various countries. The uncertainty for model parameters is computed using the squared root of the corresponding diagonal components of the covariance matrix. We carefully divide countries under consideration into 2 categories based on the estimation of the inflection point: the maturing phase and the growth-dominated phase. We observe that long-term estimations of cumulative infected cases of countries in the maturing phase for both n=1 and n≠ 1 are close to each other. We find from the value of root mean squared error (RMSE) that the RG-inspired logistic model with n≠ 1 is slightly preferable in this category. We also argue that n determines the characteristic of the epidemic at an early stage. However, in the second category, the estimated asymptotic number of cumulative infected cases contain rather large uncertainty. Therefore, in the growth-dominated phase, we focus on using n≠ 1 for countries in this phase. Some of them are in an early stage of an epidemic with an insufficient amount of data leading to a large uncertainty on parameter fits. In terms of the accuracy of the size estimation, the results do strongly depend on limitations on data collection and the epidemic phase for each country.

Possibilities of exponential or Sigmoid growth of Covid19 data in different states of India

“…Similar kind of phenomenological investigation is initiated by Ref. [7] through renormalization group inspired logistic function. The epidemiology study on covid19 data of India is started by few Refs.…”

Fear of exponential growth in Covid19 data of India and future sketching

“…Recent time Refs. [10, 11, 12] might be a guiding points about that kind of studies. Next section will focus on that kind of discussions.…”

An Environmental GIS-based Variable Analysis on SARS-CoV-2 in the City of Recife, Brazil

“…Mathematical models have been used as a tool to gather information about trends even among countries 14,15 for which an extension of the classical SIRD model is used including relevant aspects for decisionmaking such as parameters for sanitary policies (distancing, border control, reported cases and the elapse of time between doing the exam and obtaining the result) 14 . Spatial analysis has been applied in the Covid-19 context, as noted in an exploratory review developed by 16 .…”