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One-Size-Fits-All Policies Are Unacceptable: A Sustainable Management and Decision-Making Model for Schools in the Post-COVID-19 Era.
Yang, Cunwei; Wang, Weiqing; Li, Fengying; Yang, Degang.
  • Yang C; Department of Computer Science and Technology, Southwest University, Chongqing 402460, China.
  • Wang W; Department of Management Science and Engineering, Southwest University, Chongqing 402460, China.
  • Li F; Department of Environmental Science, Nanjing University of Information Science and Technology, Nanjing 210044, China.
  • Yang D; State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China.
Int J Environ Res Public Health ; 19(10)2022 05 12.
Article in English | MEDLINE | ID: covidwho-1855601
ABSTRACT
This paper proposes a sustainable management and decision-making model for COVID-19 control in schools, which makes improvements to current policies and strategies. It is not a case study of any specific school or country. The term one-size-fits-all has two meanings being blind to the pandemic, and conducting inflexible and harsh policies. The former strategy leads to more casualties and does potential harm to children. Conversely, under long-lasting strict policies, people feel exhausted. Therefore, some administrators pretend that they are working hard for COVID-19 control, and people pretend to follow pandemic control rules. The proposed model helps to alleviate these problems and improve management efficiency. A customized queue model is introduced to control social gatherings. An indoor-outdoor tracking system is established. Based on tracing data, we can assess people's infection risk, and allocate medical resources more effectively in case of emergency. We consider both social and technical feasibility. Test results demonstrate the improvements and effectiveness of the model. In conclusion, the model has patched up certain one-size-fits-all strategies to balance pandemic control and normal life.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Topics: Long Covid Limits: Child / Humans Language: English Year: 2022 Document Type: Article Affiliation country: Ijerph19105913

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Topics: Long Covid Limits: Child / Humans Language: English Year: 2022 Document Type: Article Affiliation country: Ijerph19105913