Estimating the size of COVID-19 epidemic outbreak

Chakrit Pongkitivanichkul; Daris Samart; Takol Tangphati; Phanit Koomhin; Pimchanok Pimton; Punsiri Dam-O; Apirak Payaka; Phongpichit Channuie

In the present analysis, we have collected data of the number of cumulative infections reported by WHO starting from January 21 st 2020 and up till March 21 st 2020, see [1] . The data are counted using the first day of an epidemic as day one such that the comparison between countries are feasible. We perform the non-linear least squares to fit with the 4-parameters model (a, t 0 , c, n) from Eq.(1). We are also interested in the case n = 1 where our results becomes the general model of population growth (S-curve). The uncertainty for model parameters is estimated 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, t 0 , which is the point where the growth rate begins to decline, see FIG.1. We label any country where the current situation has already passed an estimated inflection point of the S-curve as currently in the maturing phase. A country in this phase will provide a good fit to all model parameters in our model. Whereas any country where the current situation has not reached an estimated inflection point yet is labelled as currently in the growthdominated phase. Generally, a model fit of a country in this phase yields no reliable result. Only exponential function seems to fit a country in this phase. All rights reserved. No reuse allowed without permission. the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.