Fu Ruonan, Liu Wanli, Wang Senlu, Zhao Jun, Cui Qianqian, Hu Zengyun, Zhang Ling, Wang Fenghan
School of Public Health, Xinjiang Medical University, Urumqi, Xinjiang, China.
Center of Disease Control and Prevention of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, China.
Front Public Health. 2024 Feb 16;12:1297007. doi: 10.3389/fpubh.2024.1297007. eCollection 2024.
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.
随着“同一健康”理念的迅速推进，人类传染病的传播通常与环境和动物健康相关。冠状病毒病（COVID-19）在区域和全球范围内受到环境因素的很大影响，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域，使用动态疾病模型研究环境因素对COVID-19变异的影响。鉴于新疆针对COVID-19的特殊防控策略，重点关注社会和环境因素，包括人口流动性、检疫率和返程率。使用相关系数（CC）、归一化绝对误差（NAE）、均方根误差（RMSE）以及模拟与观测之间的距离（DISO）指数等统计指标评估模型性能。新疆COVID-19的情景分析涵盖三个方面：不同的人口流动性、检疫率和返程率。
结果表明，所建立的动态疾病模型能够高精度地准确模拟和预测COVID-19的变异情况。该模型的CC值为0.96，DISO值小于0.35。根据情景分析结果，人口流动性对COVID-19变异有很大影响，检疫率的影响比返程率更强。
考虑到社会和环境因素对COVID-19变异的影响，这些结果为新疆COVID-19的防控提供了科学见解。本研究中考察的COVID-19防控策略可能对其他传染病的防控也有用，特别是在与许多国家接壤的低收入地区。
