Mathematical Modelling of COVID-19 Transmission in Kenya: A Model with Reinfection Transmission Mechanism

Abstract

In this study we propose a Coronavirus Disease 2019 (COVID-19) mathematical model that stratifies infectious subpopulations into: infectious asymptomatic individuals, symptomatic infectious individuals who manifest mild symptoms and symptomatic individuals with severe symptoms. In light of the recent revelation that reinfection by COVID-19 is possible, the proposed model attempt to investigate how reinfection with COVID-19 will alter the future dynamics of the recent unfolding pandemic. Fitting the mathematical model on the Kenya COVID-19 dataset, model parameter values were obtained and used to conduct numerical simulations. Numerical results suggest that reinfection of recovered individuals who have lost their protective immunity will create a large pool of asymptomatic infectious individuals which will ultimately increase symptomatic individuals with mild symptoms and symptomatic individuals with severe symptoms (critically ill) needing urgent medical attention. The model suggests that reinfection with COVID-19 will lead to an increase in cumulative reported deaths. Comparison of the impact of non pharmaceutical interventions on curbing COVID19 proliferation suggests that wearing face masks profoundly reduce COVID-19 prevalence than maintaining social/physical distance. Further, numerical findings reveal that increasing detection rate of asymptomatic cases via contact tracing, testing and isolating them can drastically reduce COVID-19 surge, in particular individuals who are critically ill and require admission into intensive care.

Multiple COVID-19 Waves and Vaccination Effectiveness in the United States

“…However, Edridge et al [ 47 ] highlighted that reinfection with the same seasonal coronavirus often occurred within 12 months of infection. Wangari et al [ 48 ] proposed a model with a mechanism of reinfection transmission and emphasized that reinfected individuals would eventually lead to an increase in cumulative reported deaths. Coutinho et al [ 49 ] estimated the transmissibility and reinfection of the P.1 (Gamma) variant based on an extended SEIR model and public health data, and derived a reinfection rate for P.1 variant.…”

“…Coutinho et al [ 49 ] estimated the transmissibility and reinfection of the P.1 (Gamma) variant based on an extended SEIR model and public health data, and derived a reinfection rate for P.1 variant. However, neither model [ 48 , 49 ] takes into account the possibility of reducing infectivity and pathogenicity of reinfected individuals, which may overestimate the severity of reinfection. Although there are certain cases of reinfection [ 14 ], the number is small with the under-reporting into consideration.…”

Operationalisation of Model for Dynamics of COVID-19 in Kenya: Trajectory of Omicron Wave in Kenya

“…The period coincided with fourteen ( 14) days average communicable period for COVID-19. People's livelihoods were interrupted [14] A very important characteristic of the model is the ability to establish both seasonality and periodicity with accuracy [3] before they occur, as shown in Kenya media 10 and international media including Europe 11 , Eastern US 12 , and international conferences 13 . Because of its accuracy, the National Emergency Response Committee, National Vaccine 14 Committee, and National Oxygen…”

Forecasting the Severity of COVID-19 Pandemic Amidst the Emerging SARS-CoV-2 Variants: Adoption of ARIMA Model

“…Researchers attempt to use modelling techniques to explain the observable trends and predict specific patterns in the future so that health practitioners can organize health care programs, and their responses can be planned to mitigate such situations [ 4 , 5 ]. Wangari et al [ 6 ] noted that epidemiological models are becoming increasingly useful for understanding the complex processes regulating infectious disease transmission.…”