When the COVID-19 pandemic hit Nigeria in February 2020, the government and the people were at a loss for what to do. The quick spread of the virus necessitated a global tracker that sought to model the pattern of the spread of the disease.

Location is the most critical factor in how the virus spreads, as it is with all diseases. Being able to track patients who have been exposed to the virus has become a global way to fight the virus. While a host of geospatial and geographic visualizations sprung up to tally the number of cases per geographic location, very few approaches took cognizance of the spatial dynamics of the spread of the virus and localized the contact tracking situation. 

A COVID-19 dashboard was created to understand the problem using data from the Nigerian Center for Disease Control and corroborated by World Bank data. Power BI was used for geospatial visualization, while autoregressive integrated moving average (ARIMA) modeling was used for predicting cases in this dashboard.

Between April 12, 2020, and June 27, 2020, the number of confirmed cases increased by 98%, rising from 318 to 24,077. The number of recoveries and deaths also rose considerably in the same time frame. While recoveries accounted for 35.82% of the total confirmed cases, there have been 558 deaths, accounting for 3.75% of the total confirmed cases. Our model predicted the expected rise in COVID cases with an accuracy of 85%.

Two years down, the world continues to struggle with the effects of the COVID-19 pandemic, and a lot of people, including governments, remain concerned with the trajectory of the spread and growth of this disease.