Research on the Ways to Improve COVID-19 Detection—Based on Divide and Conquer Philosophy
- 10.2991/978-2-494069-31-2_44How to use a DOI?
- COVLD-19; nucleic acid testing (COVID TEST); susceptible/vulnerable population
The study is based on the shortcomings of prevention and treatment methods for COVID-19, the current challenge facing the world. The topic of this study is how to use the divide-and-conquer philosophy of computer science to improve the efficiency of NUCLEIC acid testing for COVID-19. To complete this research, we need to use the concept of divide and conquer, divide a big problem into smaller problems, and solve the small problems one by one to solve the big problem. This research needs to use the information of Internet big data and the population information registered in the community. The most difficult part of this study is data collection. The data of this experiment mainly come from the basic information of owners provided by the community, users’ dynamic travel chart of communication operators, and basic information provided by a questionnaire survey. Through this study, we found that the prevention and control process of COVID-19 is too complicated, and detection efficiency can be improved in many places.
- © 2022 The Author(s)
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- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Weibo Sun PY - 2022 DA - 2022/12/29 TI - Research on the Ways to Improve COVID-19 Detection—Based on Divide and Conquer Philosophy BT - Proceedings of the 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022) PB - Atlantis Press SP - 347 EP - 352 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-494069-31-2_44 DO - 10.2991/978-2-494069-31-2_44 ID - Sun2022 ER -