Mathematical model for estimating unconfirmed cases of COVID-19 in Ethiopia, and targeting sensitive parameters

Abstract

The novel coronavirus (COVID-19) pandemic was originated from the Wuhan city of China at the end of December, 2019. The virus has spread to 216 countries and territories around the globe. The outbreak of this sever acute respiratory syndrome (Covid-19) killed 757,727 with, 21,092,096 cases as of August 14,2020. In this paper, we propose an SPIuIcR deterministic mathematical model which contain protected class to incorporate people who follow the guidelines of WHO to keep themselves and others from Covid-19 infection in Ethiopia. Unconfirmed cases of new incidences were estimated, and sensitive parameters which exasperate the transmission of the virus were identified. According to the sensitivity result, the transmission rate(β1), the rate of applying protective measures(η), the rate of being reluctant (ω) and the rate of Covid-19 test (ψ) are found to be the most sensitive parameters. For estimated and fitted values of parameters Re work out to be 1.5, which indicate the disease will be epidemic in the population. We found that the current protective measures are not enough to reduce the transmission of Covid-19 in Ethiopia. The numerical result of our model shows that new incidence of unconfirmed cases are higher than confirmed cases, and this escalate the transmission of the virus in the community. Increasing both the rate of transfer of individuals from susceptible class to protected class and the rate of Covid-19 test play a significant role in capturing unconfirmed cases and reduce the secondary infection Re less than unity.