Published: 29 April 2020| Version 1 | DOI: 10.17632/3xsb9nyfhp.1
Kabir Abdulmajeed


The Coronavirus disease COVID-19 at this point of writing is a pandemic that has rampaged planet earth. It is regarded as a global threat and in some quarters an existential threat. Every possible effort should be made in the application of mathematical models, artificial intelligence, big data, and other resources to stem the spread of this disease. In this dataset, the daily total number of COVID-19 cases in Nigeria from February 27, 2020, to April 5, 2020, were automatically mined every 24 hours from the official websites of NCDC and Wikipedia. The initial data is in raw Excel file format nigeria_covid19.csv. Data with regularly updated case numbers and prediction results from an ensemble of forecasting algorithms can be found in nigeria_covid19_updated.csv. These data are useful as they present facts that drive analytics on COVID-19 cases in Nigeria. It also represents an early reference that can be used in the future. Academic institutions, public health agencies, scientific communities, researchers, students, and self-explorers can use this data to explore, analyze, and develop reliable insights on COVID-19 cases in Nigeria and beyond. The data with regular updates presented can be applied to drive analytics, policy development, and decision making in other countries where data is scarce.


Steps to reproduce

The forecasts can be generated by following the instructions in the DIB article "Online Forecasting of COVID-19 Cases in Nigeria using Limited Data." The total number of COVID-19 cases can be mined from the web. A sample Python (3.5) script is provided. This code can be run using any Python IDE. Note that if the URL source or template changes, the code must be adapted otherwise no data would be returned. Efforts would be made to keep this working.


Infectious Disease, Machine Learning, Decision Science, Analytical Modeling, Nigeria, Epidemic, Time Series Forecasting, Statistical Prediction, Data Analytics, COVID-19