Analysis and Prediction of COVID-19 Characteristics Using a Birth-and-Death Model

Abstract

Its spreading speed together with the risk of fatality might be the main characteristic that separates COVID-19 from other infectious diseases in our recent history. In this scenario, mathematical modeling for predicting the spread of the disease could have great value in containing the disease. Several very recent papers have contributed to this purpose. In this study we propose a birth-and-death model for predicting the number of COVID-19 active cases. It relation to the Susceptible-Infected-Recovered (SIR) model has been discussed. An explicit expression for the expected number of active cases helps us to identify a stationary point on the infection curve, where the infection ceases increasing. Parameters of the model are estimated by fitting the expressions for active and total reported cases simultaneously. We analyzed the movement of the stationary point and the basic reproduction number during the infection period up to the 20th of April 2020. These provide information about the disease progression path and therefore could be really useful in designing containment strategies.

Prediction of COVID-19 Active and Total Cases After a Fall and Rise of Cases

“…The model is the same as the one defined by equations (8) and (9) in [2]. The method is to start the fitting from that point in time where the data begins to rise after falling.…”

“…The active cases data can be used without any change. Figure 4 shows the resulting fit of equations (8) and (9) in [2] to the active and total cases. Table 3 shows the parameters for the fit.…”

“…In the present study, we investigate how the model in [2] can be applied to fit a data where the active cases show a tendency to fall before rising further.…”

“…It can be observed that the path of active COVID-19 cases in the USA shows a decreasing tendency near May 30, 2020 (please refer [1]). A fit of the data between February 15 and May 20, 2020, based on a birth-and-death model (please refer [2]), suggests such a decreasing nature on May 28, 2020. This prediction remained the same, when we extended the data span as from February 15 to June 3, 2020.…”

“… Abstract During the progress of the COVID-19, many countries have observed that their active cases tend to rise again after falling for some time. This may cause some mathematical models like the one discussed in [2] tend to make errors in the future prediction. We discuss a simple method to better the future prediction in such cases.…”