PDF(Pubmed)
Abstract：
With 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.
We 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.
The 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.
These 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.
We 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.
The 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.
These 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.
摘要：
■随着“一个健康”方法的快速发展，人类传染病的传播通常与环境和动物健康有关。冠状病毒病(COVID-19)在很大程度上受到区域和全球环境因素的影响，并严重扰乱了人类社会，特别是在与许多国家接壤的低收入地区。然而,很少有研究探讨环境因素对这些地区疾病传播的影响。
■我们以新疆维吾尔自治区为研究区，使用动态疾病模型研究了环境因素对COVID-19变异的影响。鉴于新疆针对COVID-19的特殊控制和预防策略，重点是社会和环境因素，包括人口流动，检疫率，和回报率。使用相关系数(CC)、归一化绝对误差(NAE)，均方根误差(RMSE)，以及模拟和观察(DISO)指数之间的距离。新疆COVID-19的情景分析包括三个方面：不同的人口流动性，检疫率，和回报率。
■结果表明，所建立的动态疾病模型可以以高精度准确地模拟和预测COVID-19的变异。该模型具有0.96的CC值和小于0.35的DISO值。根据情景分析结果，人口流动对COVID-19的变异有很大影响，检疫率比退货率有更强的影响。
■这些结果为新疆COVID-19的控制和预防提供了科学见解，考虑社会和环境因素对COVID-19变异的影响。本研究中检查的COVID-19的控制和预防策略也可能对控制其他传染病有用，特别是在与许多国家接壤的低收入地区。
■我们以新疆维吾尔自治区为研究区，使用动态疾病模型研究了环境因素对COVID-19变异的影响。鉴于新疆针对COVID-19的特殊控制和预防策略，重点是社会和环境因素，包括人口流动，检疫率，和回报率。使用相关系数(CC)、归一化绝对误差(NAE)，均方根误差(RMSE)，以及模拟和观察(DISO)指数之间的距离。新疆COVID-19的情景分析包括三个方面：不同的人口流动性，检疫率，和回报率。
■结果表明，所建立的动态疾病模型可以以高精度准确地模拟和预测COVID-19的变异。该模型具有0.96的CC值和小于0.35的DISO值。根据情景分析结果，人口流动对COVID-19的变异有很大影响，检疫率比退货率有更强的影响。
■这些结果为新疆COVID-19的控制和预防提供了科学见解，考虑社会和环境因素对COVID-19变异的影响。本研究中检查的COVID-19的控制和预防策略也可能对控制其他传染病有用，特别是在与许多国家接壤的低收入地区。
