Modelling the impact of detection on COVID-19 transmission dynamics in Ghana

Recently, due to the global increase in new cases of infections, the World Health Organisation declared COVID-19 disease a pandemic. We present a deterministic model to investigate the impact of detection of infected individuals on the transmission dynamics of COVID-19. The model is extended to capture the role of immigration, governmental interventions and public perception of risk regarding the number of critical cases and deaths. The model is fitted to the currently available data on cumulative COVID-19 cases in Ghana and trends of outcomes quantitatively estimated. Results suggest that intervention in the form of lockdown lengthens the period of reaching the peak of infection, thereby giving time for policymaking and management of pandemic. Simulation results suggest that detection of exposed individuals has great potential to reduce daily detected cases and flatten the cumulative curve during the early stages of the pandemic. Thus, more effort should be targeted towards increasing contact tracing and detection of those suspected to be exposed to COVID-19 in order to curtail the spread of the disease. Results from this study would be useful in informing government policy direction and management regarding the control of COVID-19 in Ghana and other countries.