Using SORMAS Data to Understand the Attributable Fraction of COVID-19 in Nigeria

Public Health Emergency Operation Centers are established to coordinate COVID-19 disease and other public health threats. Surveillance is pivotal in enabling countries to monitor disease patterns and trends, and the use of a Surveillance Outbreak Response Management and analysis system (SORMAS) helps with real-time cases. SORMAS users can notify health departments about new cases of epidemic-prone diseases, detect outbreaks, and simultaneously manage outbreaks. SORMAS is a management process system that supports supervisors to validate cases and control the spread of disease. These SORMAS features enable data analysis for stakeholders, local responders, and policymakers to analyze disease data and make informed decisions for efficient and effective responses. This paper examined national data on COVID-19. We computed the proportion of patients with COVID-19 disease in Nigeria and the 95% confidence interval (CI) for the COVID-19 attributable fraction. This study shows that the proportion of patients who had COVID-19 lies between 6.35% and 6.39%. The SORMAS platform has increased Nigeria's capacity for accurate and timely data reporting and response.