COVID-19, a coronavirus disease 2019, is an ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first case in Kenya was identified on March 13, 2020, with the pandemic increasing to about 237,000 confirmed cases and 4,746 deaths by August 2021. We developed an SEIR model forecasting the COVID-19 pandemic in Kenya using an Autoregressive Integrated moving averages (ARIMA) model. The average time difference between the peaks of wave 1 to wave 4 was observed to be about 130 days. The 4th wave was observed to have had the least number of daily cases at the peak. According to the forecasts made for the next 60 days, the pandemic is expected to continue for a while. The 4th wave peaked on August 26, 2021 (498th day). By October 26, 2021 (60th day), the average number of daily infections will be 454 new cases and 40 severe cases, which would require hospitalization, and 16 critically ill cases requiring intensive care unit services. The findings of this study are key in developing informed mitigation strategies to ensure that the pandemic is contained and inform the preparedness of policymakers and health care workers.

Background COVID-19 disease has persisted since it was declared a global pandemic by World health organization (WHO) in February 2020. Kenya had notified a total of 34,057 cases, reported 574 deaths by end of August 2020. The Country's positivity rate had also come down from 13 to 4 percent between June and August 2020. Despite the gains in controlling the first COVID-19 wave from the non-pharmaceutical interventions, most countries would not sustain the economy with prolonged lockdown and restriction of movements. In Kenya, for instance, it resulted in easing some measures on 27th September 2020 in an attempt to reverse the economic strain. By end of October, the effects of these measures were already reversing with a positivity rate of 14 and bed occupancy of 140 percent. The goal of this study was to model the progression of COVID-19 cases in Kenya post reversed curve of the first wave of infections. Results An SEIR compartmental model was developed to predict the daily cases of COVID-19 post the reversed curve. The model had 8 compartments containing sub-populatoions of: Susceptible, Exposed, Symptomatic Infectious, Asymptomatic Infectious,Hospitalized,Intesive Care Unit, Deaths and Recovered. The model equations were then solved to obtain the number of cases that would be infected on a daily basis beginning March 14th to January 2021. The model results demonstrated that with the abscence of herd immunity in the general human population, relaxation of the mitigation measures will eventually result to resurgence of COVID-19 cases. The wave of infections length of stay will be 4 months upto January 2021 and will be on the rise to the peak for an estimated 45 days. The cumulative number of cases trend depicts the same pattern as that of the daily cases. It is predicted that the trend will be on the rise till January 2021. Conclusion Increased vigilance on post reversed COVID-19 curve is indispensable. Continued interventions such as mass and targetted testing, contact tracing and social distancing measures are imperative to ensure that new infections are isolated real time. This will inform new and appropriate interventions amidst the ongoing pandemic