Data Analysis and Prediction for Emergency Supplies Demand Through Improved Dynamics Model: A Reflection on the Post Epidemic Era
Throughout history, humanity has grappled with infectious diseases that pose serious risks to health and life. The COVID-19 pandemic has profoundly impacted society, prompting significant reflection on preparedness and response strategies. In the future, humans may face unexpected disasters or crise...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
|
| Series: | Computation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-3197/12/11/231 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849221002756620288 |
|---|---|
| author | Weiqing Zhuang Qiong Wu Morgan C. Wang |
| author_facet | Weiqing Zhuang Qiong Wu Morgan C. Wang |
| author_sort | Weiqing Zhuang |
| collection | DOAJ |
| description | Throughout history, humanity has grappled with infectious diseases that pose serious risks to health and life. The COVID-19 pandemic has profoundly impacted society, prompting significant reflection on preparedness and response strategies. In the future, humans may face unexpected disasters or crises, making it essential to learn from the COVID-19 experience, especially in ensuring adequate emergency supplies and mobilizing resources effectively in times of need. Efficient emergency medical management is crucial during sudden outbreaks, and the preparation and allocation of medical supplies are vital to safeguarding lives, health, and safety. However, the unpredictable nature of epidemics, coupled with population dynamics, means that infection rates and supply needs within affected areas are uncertain. By studying the factors and mechanisms influencing emergency supply demand during such events, materials can be distributed more efficiently to minimize harm. This study enhances the existing dynamics model of infectious disease outbreaks by establishing a demand forecasting model for emergency supplies, using Hubei Province in China as a case example. This model predicts the demand for items such as masks, respirators, and food in affected regions. Experimental results confirm the model’s effectiveness and reliability, providing support for the development of comprehensive emergency material management systems. Ultimately, this study offers a framework for emergency supply distribution and a valuable guideline for relief efforts. |
| format | Article |
| id | doaj-art-d7cb82be817447bbaa94d1541ea44cba |
| institution | Kabale University |
| issn | 2079-3197 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computation |
| spelling | doaj-art-d7cb82be817447bbaa94d1541ea44cba2024-11-26T17:58:16ZengMDPI AGComputation2079-31972024-11-01121123110.3390/computation12110231Data Analysis and Prediction for Emergency Supplies Demand Through Improved Dynamics Model: A Reflection on the Post Epidemic EraWeiqing Zhuang0Qiong Wu1Morgan C. Wang2School of Internet Economics and Business, Fujian University of Technology, Fuzhou 350118, ChinaSchool of Tourism Geography and Historical Culture, Hulunbuir University, Hulunbuir 021008, ChinaCollege of Science, University of Central Florida, Orlando, FL 32801, USAThroughout history, humanity has grappled with infectious diseases that pose serious risks to health and life. The COVID-19 pandemic has profoundly impacted society, prompting significant reflection on preparedness and response strategies. In the future, humans may face unexpected disasters or crises, making it essential to learn from the COVID-19 experience, especially in ensuring adequate emergency supplies and mobilizing resources effectively in times of need. Efficient emergency medical management is crucial during sudden outbreaks, and the preparation and allocation of medical supplies are vital to safeguarding lives, health, and safety. However, the unpredictable nature of epidemics, coupled with population dynamics, means that infection rates and supply needs within affected areas are uncertain. By studying the factors and mechanisms influencing emergency supply demand during such events, materials can be distributed more efficiently to minimize harm. This study enhances the existing dynamics model of infectious disease outbreaks by establishing a demand forecasting model for emergency supplies, using Hubei Province in China as a case example. This model predicts the demand for items such as masks, respirators, and food in affected regions. Experimental results confirm the model’s effectiveness and reliability, providing support for the development of comprehensive emergency material management systems. Ultimately, this study offers a framework for emergency supply distribution and a valuable guideline for relief efforts.https://www.mdpi.com/2079-3197/12/11/231emergency materialssupply schedulingdynamics model |
| spellingShingle | Weiqing Zhuang Qiong Wu Morgan C. Wang Data Analysis and Prediction for Emergency Supplies Demand Through Improved Dynamics Model: A Reflection on the Post Epidemic Era Computation emergency materials supply scheduling dynamics model |
| title | Data Analysis and Prediction for Emergency Supplies Demand Through Improved Dynamics Model: A Reflection on the Post Epidemic Era |
| title_full | Data Analysis and Prediction for Emergency Supplies Demand Through Improved Dynamics Model: A Reflection on the Post Epidemic Era |
| title_fullStr | Data Analysis and Prediction for Emergency Supplies Demand Through Improved Dynamics Model: A Reflection on the Post Epidemic Era |
| title_full_unstemmed | Data Analysis and Prediction for Emergency Supplies Demand Through Improved Dynamics Model: A Reflection on the Post Epidemic Era |
| title_short | Data Analysis and Prediction for Emergency Supplies Demand Through Improved Dynamics Model: A Reflection on the Post Epidemic Era |
| title_sort | data analysis and prediction for emergency supplies demand through improved dynamics model a reflection on the post epidemic era |
| topic | emergency materials supply scheduling dynamics model |
| url | https://www.mdpi.com/2079-3197/12/11/231 |
| work_keys_str_mv | AT weiqingzhuang dataanalysisandpredictionforemergencysuppliesdemandthroughimproveddynamicsmodelareflectiononthepostepidemicera AT qiongwu dataanalysisandpredictionforemergencysuppliesdemandthroughimproveddynamicsmodelareflectiononthepostepidemicera AT morgancwang dataanalysisandpredictionforemergencysuppliesdemandthroughimproveddynamicsmodelareflectiononthepostepidemicera |