Mbaya, Emmanuel and Alao, Babatunde and Ewejobi, Philip and Nwokolo, Innocent Ozulonye and Oguntosin, V. and Adetiba, E. (2024) NaijaCovidAPI: an application programming interface for retrieval of COVID19 data from the Nigerian Center for Disease Control web platform. F1000Research. pp. 1-21.
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Abstract
Background: In this work, a COVID19 Application Programming Interface (API) was built using the Representational State Transfer (REST) API architecture and it is designed to fetch data daily from the Nigerian Center for Disease Control (NCDC) website. Methods: The API is developed using ASP.NET Core Web API framework using C# programming language and Visual Studio 2019 as the Integrated Development Environment (IDE). The application has been deployed to Microsoft Azure as the cloud hosting platform and to successfully get new data from the NCDC website using Hangfire where a job has been scheduled to run every 12:30 pm (GMT + 1) and load the fetched data into our database. Various API Endpoints are defined to interact with the system and get data as needed, data can be fetched from a single state by name, all states on a particular day or over a range of days, etc. Results: The results from the data showed that Lagos and Abuja FCT in Nigeria were the hardest-hit states in terms of Total Confirmed cases while Lagos and Edo states had the highest death causalities with 465 and 186 as of August 2020. This analysis and many more can be easily made as a result of this API we have created that warehouses all COVID19 Data as presented by the NCDC since the first contracted case on February 29, 2020. This system was tested on the BlazeMeter platform, and it had an average of 11Hits/s with a response time of 2905milliseconds. Conclusions: The extension of NaijaCovidAPI over existing COVID19 APIs for Nigeria is the access and retrieval of previous data. Our contribution to the body of knowledge is the creation of a data hub for Nigeria's COVID-19 incidence from February 29, 2020, to date
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | Patricia Nwokealisi |
| Date Deposited: | 06 Dec 2024 12:17 |
| Last Modified: | 06 Dec 2024 12:17 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/18642 |
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