Realtime Covid19 Tracker Using React
Keywords:
Dynamic data representation, Responsiveness, API calls, JSX, Sorting algorithms, NPM packages, Page reloads, JSON, Library, componentsAbstract
Analysing the data of a deadly pandemic that has created a mess in this wonderful world and caused a lot of deaths is a need of this hour such that we can easily take preventive measures and hold this pandemic growth and eradicate it with certain measures and proper planning and a study is needed to analyse whether any inter-mediate hosts have facilitated the transmission of the virus to humans or vice versa and this could only be done if precise data is analysed [1][6]. The main objective behind writing this paper is to present an idea that how knowledge to an emerging frontend technology like React JS can lead to a wonderful user interface that can serve as a data analyser web software for this deadly pandemic. The paper revolves around a project created with a bunch of features of React JS from exciting frontend components with Material UI to writing CSS, JSX and making API calls to collect worldwide data related to Corona virus [9]. The major highlights of the project entitled in this paper are no page reloads, Responsiveness, body-parsing, API calls for data collection, JSX (HTML inside JS), sorting algorithms, dynamic data representation, REDUX, data representation in dynamic graphs/pie charts. In this a large number of npm packages like react, react-dom, @material-ui etc along with React JS and CSS library like Material UI has been used in order to code the website such that it results in an attractive, responsive and a beautiful project with a single technology that is JS. The web software entitled in this paper is a complete package of features of React JS integrated with some other frontend technologies like CSS and material UI going through which any user can analyse the data related to corona virus geographically as well as graphically.
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References
Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet 2020.
https://www.researchgate.net/publication/341757281_ Case_Study_Fighting_Covid
_with_Tech_and_Innovation
Carroll LN, Au AP, Detwiler LT, Fu TC, Painter IS, Abernethy NF. Visualization and analytics tools for infectious disease epidemiology: a systematic review. J Biomed Inform. 2014;51:287–98.
Valls J, Tobias A, Satorra P, Tebe C. COVID19- tracker: a shiny app to analise data on SARS-CoV-2 epidemic in Spain. Gac Sanit. 2020;S0213- 9111(20):30085–6.
https://doi.org/10.1016/j.gaceta.2020.04.002. [5] Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect Dis. 2020;20(5):533–4.
Wolkewitz M, Puljak L. Methodological challenges of analysing COVID-19 data during the pandemic. BMC Med Res Methodol. 2020;20(1):81.
Lauer SA, Grantz KH, Bi Q, Jones FK, Zheng Q, Meredith HR, et al. The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: estimation and application. Ann Intern Med. 2020;172(9):577–82.
Roser M, Ritchie H, Ortiz-Ospina E. Hasell J. Coronavirus Pandemic (COVID-19); 2020. Published online at OurWorldInData.org.Reterivedfrom: https://ourworldindata.org/coronavirus.
