Objective: This study is focused on the analysis of the spread of Covid-19 in Nigeria, applying statistical models and available data from the NCDC. We present an insight into the spread of Covid-19 in Nigeria in order to establish a suitable prediction model, which can be applied as a decision-supportive tool for assigning health interventions and mitigating the spread of the Covid-19 infection. Methodology: Daily spread data from February 27 to April 26, 2020, were collected to construct the autoregressive integrated moving average (ARIMA) model using the R software. Stability analysis and stationarity test, parameter test, and model diagnostic were also carried out. Finally, the fitting, selection and prediction accuracy of the ARIMA model was evaluated using the AICc model selection criteria. Results: The ARIMA (1,1,0) model was finally selected among ARIMA models based upon the parameter test and Box–Ljung test. A ten-day forecast was also made from the model, which shows a steep upward trend of the spread of the COVID-19 in Nigeria within the selected time frame. Conclusion: Federal Government of Nigeria through the presidential task force can apply the forecasted trend of much more spread to make more informed decisions on the additional measures in place to curb the spread of the virus. Application of the model can also assist in studying the effectiveness of the lockdown on the on the spread of Covid-19 in Nigeria.

With increasing fatalities, the COVID-19 pandemic constitutes a formidable global health challenge. The causative agent, SARS-CoV-2 constantly tests the efficacy of the immune system of its victims. The protective ability of the innate immune system as the first responder largely determines the progression of disease and its clinical prognosis. Evidence suggests that mortalities associated with COVID-19 are largely due to hyperinflammation and a dysregulated immune response. Consequently, the degree of the release of pro-inflammatory cytokines such as IL1, IL-6, and TNF alpha remarkably distinguishes between mild and severe cases of COVID-19. The early prediction of a cytokine storm is made possible by several serum chemistry and hematological markers. The prompt use of these markers for laboratory tests, and the aggressive prevention and management of a cytokine release syndrome is critical in determining the level of morbidity and fatality associated with COVID-19. With respect to the SARS-CoV-2 and the host cell, this literature review focuses on the dynamics of the COVID-19 disease highlighting on the pathogenesis, and the markers of Cytokine Storm. It also proffers solutions by critically looking at the current and potential pharmacological agents that are or can be used to mitigate and manage cytokine storms.