COVID-19 Statistics Based on Location

References

[1] Zhou Yang, Jiwei Xu, Zhenhe Pan, and Fang Jin. Covid19 tracking: An interactive tracking, visualizing and analyzing platform. In 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pages 941–943. IEEE, 2020.

[2] Sumindar Kaur Saini, Vishal Dhull, Sarbjeet Singh, and Akashdeep Sharma. Visual exploratory data analysis of covid-19 pandemic. In 2020 5th IEEE International Conference. on Recent Advances and Innovations in Engineering (ICRAIE), pages 1–6, 2020.

[3] Jamal Alsakran and Loai Alnemer. Visual analysis of covid-19 trends. In 2020 Seventh International Conference on Information Technology Trends (ITT), pages 196–201, 2020.

[4] Xuemin Yu, Martha Dais Ferreira, and Fernando V. Paulovich. Senti- covid19: An interactive visual analytics system for detecting public sentiment and insights regarding covid-19 from social media. IEEE Access, 9:126684–126697, 2021.

[5] A. Mokdad, J. Haydar, J. Itani and W. Fahs,” CTAP: Covid-19 Tracking Application,” 2021 22nd International Arab Confer- ence on Information Technology (ACIT), 2021, pp. 1-5, doi: 10.1109/ACIT53391.2021.9677142.

[6] T. Saxena, P. Anuragi, G. Shinde, N. Yadav and M. Digalwar, ”COWAR: An Android Based Mobile Application to Help Citi- zens and COVID-19 Warriors,” 2020 IEEE 4th Conference on In- formation Communication Technology (CICT), 2020, pp. 1-6, doi: 10.1109/CICT51604.2020.9312073.

[7] Z. A. El Mouden, A. Jakimi, R. M. Taj and M. Hajar, ”A Graph- based Methodology for Tracking Covid-19 in Time Series Datasets,” 2020 IEEE 2nd International Conference on Electronics, Control, Op- timization and Computer Science (ICECOCS), 2020, pp. 1-5, doi: 10.1109/ICECOCS50124.2020.9314516.

[8] J. Berglund, ”Tracking COVID-19: There’s an App for That,” in IEEE Pulse, vol. 11, no. 4, pp. 14-17, July-Aug. 2020, doi: 10.1109/MPULS.2020.3008356.

@article{1703317,
      author = {Saurabh Pradeep Pawar, Mahesh Anant Mestri, Siddhesh Shrikrishna Pednekar},
      title = {COVID-19 Statistics Based on Location},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {5},
      number = {9},
      pages = {593-596},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1703317.pdf},
      abstract = {Covid-19 Statistics based on location- React-Native project. The idea for this application came from mini project we did about predictions and visualization of virus at start of 2020, When covid-19 virus was new and there was no predictions about it. In that application we used machine learning algorithms to visualize the trends in covid-19 outbreak in charts and graph formats. Since then world has changed allot and tracking the virus become need of time, Hence this app was created to track the daily number of cases, deaths and recoveries.
This app works on bases of React-Native which is a open source UI software with JavaScript framework for writing real, natively creating mobile applications for iOS and Android And for the data collection part it uses rest AP-I?s.
This types of app are easy to use and fast rendering. We can use the react components to render different parts so that we don?t have to render the whole page again, which reduces the load on users mobile.
This app can give you real time updates on covid-19 based on the location you have selected, also the historical records of that location regarding the covid-19.
This app can be very helpful to gain incites about current covid- 19 condition, And also with its user friendliness it can be used by anyone who has a smartphone.},
      keywords = {component, formatting, style, styling, insert},
      month = {March},
  }