Epidemic Surveillance/Public Health Emergency Response Center, Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China.
School of Public Health, Kunming Medical University, Kunming, Yunnan, China.
Medicine (Baltimore). 2022 Jul 8;101(27):e29733. doi: 10.1097/MD.0000000000029733.
This study aimed to assess the risk of coronavirus disease 2019 in the border areas of southwest China, so as to provide guidance to targeted prevention and control measures in the border areas of different risk levels. We assessed the dependence of the risk of an outbreak in the southwest China from imported cases on key parameters such as the cumulative number of infectious diseases in the border area of southwest China in the past 3 years; the connectivity of the neighboring countries with China's Southwest border, including baseline travel numbers, travel frequencies, the effect of travel restrictions, and the length of borders with neighboring countries; the cumulative number of close contacts of coronavirus disease 2019 patients; (iv) the population density in border areas; the efficacy of control measures in border areas; experts estimated risks in border areas based on experience and then given a score; Spearman correlation and Logistic regression models were used to analyze the associated factors of novel coronavirus. According to the correlation of various factors, we assigned values to each parameter, calculated the risk score of each county, and then divided each county into high, medium, and low risk according to the sick score and took different control measure according to different risk levels. Finally, the total risk level was evaluated according to the Harvard disease risk index model. The number of infectious diseases in the past 3 years, travel numbers, travel frequencies, experts estimated risk score, effect of travel restrictions, and the number of close contacts were associated with the incidence of new coronary pneumonia. It is concluded that bilateral transportation convenience is a risk factor for new coronary pneumonia, (odds ratio = 9.23, 95% confidence interval, 1.99-42.73); the number of observers is a risk factor for new coronary pneumonia (odds ratio = 1.04, 95% confidence interval, 1.00-1.08). We found that in countries with travel numbers, travel frequencies, and experts' estimated risk scores were the influencing factors of novel coronavirus. The effect of travel restrictions and the cumulative number of close contacts of the case are risk factors for novel coronavirus.
本研究旨在评估中国西南边境地区 2019 年冠状病毒病的风险,为不同风险水平的边境地区提供有针对性的防控措施指导。我们评估了西南边境地区传染病累计病例数、与中国西南边境接壤的邻国之间的连通性(包括基线旅行人数、旅行频率、旅行限制效果和与邻国接壤的长度)、2019 年冠状病毒病密切接触者的累计人数、边境地区人口密度、边境地区控制措施的有效性、专家根据经验对边境地区的风险进行评估并给出评分等关键参数对西南地区疫情爆发风险的依赖性。采用 Spearman 相关和 Logistic 回归模型分析新型冠状病毒的相关因素。根据各因素的相关性,我们为每个参数赋值,计算每个县的风险评分,然后根据评分将每个县分为高、中、低风险,并根据不同风险水平采取不同的控制措施。最后,根据哈佛疾病风险指数模型评估总风险水平。过去 3 年的传染病数量、旅行人数、旅行频率、专家估计的风险评分、旅行限制的效果以及密切接触者的数量与新发冠状动脉肺炎的发病率有关。结果表明,双边交通便利是新发冠状动脉肺炎的危险因素(比值比=9.23,95%置信区间,1.99-42.73);观察者人数是新发冠状动脉肺炎的危险因素(比值比=1.04,95%置信区间,1.00-1.08)。我们发现,在旅行人数、旅行频率和专家估计的风险评分较高的国家,旅行限制的效果和病例的密切接触者人数是新型冠状病毒的影响因素。