Scenario analysis of COVID-19 dynamical variations by different social environmental factors: a case study in Xinjiang
BackgroundWith the rapid advancement of the One Health approach, the transmission of human infectious diseases is generally related to environmental and animal health. Coronavirus disease (COVID-19) has been largely impacted by environmental factors regionally and globally and has significantly disr...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-02-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2024.1297007/full |
| _version_ | 1797305056987447296 |
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| author | Ruonan Fu Wanli Liu Senlu Wang Senlu Wang Jun Zhao Qianqian Cui Zengyun Hu Zengyun Hu Ling Zhang Fenghan Wang |
| author_facet | Ruonan Fu Wanli Liu Senlu Wang Senlu Wang Jun Zhao Qianqian Cui Zengyun Hu Zengyun Hu Ling Zhang Fenghan Wang |
| author_sort | Ruonan Fu |
| collection | DOAJ |
| description | BackgroundWith the rapid advancement of the One Health approach, the transmission of human infectious diseases is generally related to environmental and animal health. Coronavirus disease (COVID-19) has been largely impacted by environmental factors regionally and globally and has significantly disrupted human society, especially in low-income regions that border many countries. However, few research studies have explored the impact of environmental factors on disease transmission in these regions.MethodsWe used the Xinjiang Uygur Autonomous Region as the study area to investigate the impact of environmental factors on COVID-19 variation using a dynamic disease model. Given the special control and prevention strategies against COVID-19 in Xinjiang, the focus was on social and environmental factors, including population mobility, quarantine rates, and return rates. The model performance was evaluated using the statistical metrics of correlation coefficient (CC), normalized absolute error (NAE), root mean square error (RMSE), and distance between the simulation and observation (DISO) indices. Scenario analyses of COVID-19 in Xinjiang encompassed three aspects: different population mobilities, quarantine rates, and return rates.ResultsThe results suggest that the established dynamic disease model can accurately simulate and predict COVID-19 variations with high accuracy. This model had a CC value of 0.96 and a DISO value of less than 0.35. According to the scenario analysis results, population mobilities have a large impact on COVID-19 variations, with quarantine rates having a stronger impact than return rates.ConclusionThese results provide scientific insight into the control and prevention of COVID-19 in Xinjiang, considering the influence of social and environmental factors on COVID-19 variation. The control and prevention strategies for COVID-19 examined in this study may also be useful for the control of other infectious diseases, especially in low-income regions that are bordered by many countries. |
| first_indexed | 2024-03-08T00:19:27Z |
| format | Article |
| id | doaj.art-cba1a2db668f4816bcc85f98d3cfc75a |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-03-08T00:19:27Z |
| publishDate | 2024-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-cba1a2db668f4816bcc85f98d3cfc75a2024-02-16T13:22:15ZengFrontiers Media S.A.Frontiers in Public Health2296-25652024-02-011210.3389/fpubh.2024.12970071297007Scenario analysis of COVID-19 dynamical variations by different social environmental factors: a case study in XinjiangRuonan Fu0Wanli Liu1Senlu Wang2Senlu Wang3Jun Zhao4Qianqian Cui5Zengyun Hu6Zengyun Hu7Ling Zhang8Fenghan Wang9School of Public Health, Xinjiang Medical University, Urumqi, Xinjiang, ChinaCenter of Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, ChinaSchool of Public Health, Xinjiang Medical University, Urumqi, Xinjiang, ChinaCenter of Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, ChinaCenter of Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, ChinaSchool of Mathematics and Statistics, Ningxia University, Yingchuan, Ningxia, ChinaSchool of Global Health, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaState Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, ChinaSchool of Global Health, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDaizhuang Hospital, Jining, Shandong, ChinaBackgroundWith the rapid advancement of the One Health approach, the transmission of human infectious diseases is generally related to environmental and animal health. Coronavirus disease (COVID-19) has been largely impacted by environmental factors regionally and globally and has significantly disrupted human society, especially in low-income regions that border many countries. However, few research studies have explored the impact of environmental factors on disease transmission in these regions.MethodsWe used the Xinjiang Uygur Autonomous Region as the study area to investigate the impact of environmental factors on COVID-19 variation using a dynamic disease model. Given the special control and prevention strategies against COVID-19 in Xinjiang, the focus was on social and environmental factors, including population mobility, quarantine rates, and return rates. The model performance was evaluated using the statistical metrics of correlation coefficient (CC), normalized absolute error (NAE), root mean square error (RMSE), and distance between the simulation and observation (DISO) indices. Scenario analyses of COVID-19 in Xinjiang encompassed three aspects: different population mobilities, quarantine rates, and return rates.ResultsThe results suggest that the established dynamic disease model can accurately simulate and predict COVID-19 variations with high accuracy. This model had a CC value of 0.96 and a DISO value of less than 0.35. According to the scenario analysis results, population mobilities have a large impact on COVID-19 variations, with quarantine rates having a stronger impact than return rates.ConclusionThese results provide scientific insight into the control and prevention of COVID-19 in Xinjiang, considering the influence of social and environmental factors on COVID-19 variation. The control and prevention strategies for COVID-19 examined in this study may also be useful for the control of other infectious diseases, especially in low-income regions that are bordered by many countries.https://www.frontiersin.org/articles/10.3389/fpubh.2024.1297007/fullCOVID-19 pandemicXinjiang Uygur Autonomous Regionsocial environmental factorssimulation and predictionscenarios analysis |
| spellingShingle | Ruonan Fu Wanli Liu Senlu Wang Senlu Wang Jun Zhao Qianqian Cui Zengyun Hu Zengyun Hu Ling Zhang Fenghan Wang Scenario analysis of COVID-19 dynamical variations by different social environmental factors: a case study in Xinjiang Frontiers in Public Health COVID-19 pandemic Xinjiang Uygur Autonomous Region social environmental factors simulation and prediction scenarios analysis |
| title | Scenario analysis of COVID-19 dynamical variations by different social environmental factors: a case study in Xinjiang |
| title_full | Scenario analysis of COVID-19 dynamical variations by different social environmental factors: a case study in Xinjiang |
| title_fullStr | Scenario analysis of COVID-19 dynamical variations by different social environmental factors: a case study in Xinjiang |
| title_full_unstemmed | Scenario analysis of COVID-19 dynamical variations by different social environmental factors: a case study in Xinjiang |
| title_short | Scenario analysis of COVID-19 dynamical variations by different social environmental factors: a case study in Xinjiang |
| title_sort | scenario analysis of covid 19 dynamical variations by different social environmental factors a case study in xinjiang |
| topic | COVID-19 pandemic Xinjiang Uygur Autonomous Region social environmental factors simulation and prediction scenarios analysis |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2024.1297007/full |
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