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病毒潜伏期影响因素分析——基于对数正态分布
Analysis of Factors Affecting Incubation Period of Virus—Based on Log-Normal

DOI: 10.12677/sa.2024.133096, PP. 943-953

Keywords: 病毒潜伏期,描述统计,对数正态分布,方差分析
Incubation Period of Virus
, Descriptive Statistics, Log-Normal, ANOVA

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Abstract:

鉴于传染病、疫情等突发性疾病的严峻性,其出现无疑会对人们的生产生活造成极其严重的冲击。若控制不力,将引发医疗资源紧张、经济质量下滑等一系列关乎生存与发展的问题。因此,对发病源的规律性进行深入探究显得尤为重要。通过掌握疾病的发展规律,医者能够及时制定相应医疗方案,实施有效干预,进而遏制疾病的进一步扩散,控制医疗成本。自2019年COVID-19疫情爆发以来,该病毒已对全球的经济、卫生、医疗等多个领域造成了巨大冲击,同时也对人类的生存安全提出了严峻挑战。本文以国家卫生健康委员会公布的各省市感染人数的真实数据为基础,经过严格的信息完整度筛查,依据病源仅暴露一次、暴露源清晰、暴露信息记录完整的标准,筛选出78位患者的病历数据作为研究样本。通过深入分析,探索了新型冠状病毒的潜伏期天数,结果表明,该病毒在人体内的平均潜伏期约为16天。此外,研究还发现,潜伏期长短与患者的性别、年龄无显著关联,但与已感染群体的接触方式和病毒的地域浓度密切相关。
Given the severity of infectious diseases, pandemics, and other sudden illnesses, their emergence undoubtedly poses a grave impact on people’s lives and production. If not controlled effectively, it will lead to a series of issues concerning survival and development, such as the strain on medical resources and a decline in economic quality. Therefore, it is crucial to conduct in-depth research on the regularity of the source of the disease. By grasping the development pattern of the disease, doctors can promptly formulate corresponding medical treatment plans, implement effective interventions, and thereby curb the further spread of the disease and control medical costs. Since the outbreak of the COVID-19 pandemic in 2019, the virus has had a tremendous impact on various fields such as global economy, health, and medical care, while also posing severe challenges to human survival and safety. Based on the real data of the number of infections in various provinces and cities announced by the National Health Commission, this article has strictly screened for information completeness and selected 78 patients’ medical record data as research samples according to the criteria of only one exposure to the source of the disease, clear exposure source, and complete exposure information records. Through in-depth analysis, the latent period of the novel coronavirus was explored, and the results showed that the average latent period of the virus in the human body is approximately 16 days. Additionally, the study found that the length of the latent period was not significantly associated with the patient’s gender or age, but was closely related to the mode of contact with infected individuals and the regional concentration of the virus.

References

[1]  郭德银, 江佳富, 宋宏彬, 秦天, 李振军, 张定梅, 黄森忠, 舒跃龙, 徐建青, 姜世勃, 郑涛, 田怀玉, 郝荣章, 徐建国. 2020-2021年度新型冠状病毒肺炎疫情发展趋势分析与应对[J]. 疾病监测, 2020, 35(12): 1068-1072.
[2]  赵芳, 赵静, 张海霞, 战寒秋, 王硕, 董伟杰. 传染病定点收治医院静脉药物配置中心新型冠状病毒肺炎疫情综合应急防控措施[J]. 中国消毒学杂志, 2022, 39(12): 958-961.
[3]  邓江霞, 江博文, 刘传, 杨柳, 古赛. 新型冠状病毒肺炎疫情期间非高风险地区发热门诊患者的临床特征分析[J]. 现代医药卫生, 2020, 36(24): 3949-3951.
[4]  沈燕, 高晓东, 胡必杰. 新型冠状病毒肺炎疫情防控期间内镜诊疗相关感染防控建议[J]. 微生物与感染, 2020, 15(6): 408-412.
[5]  赵艳婷. 新冠病毒传播分数阶动力学研究: 建模预测、数值分析及优化管控[D]: [博士学位论文]. 合肥: 中国科学技术大学, 2022.
[6]  任建强, 崔亚鹏, 倪顺江. 基于机器学习的新冠肺炎疫情趋势预测方法[J]. 清华大学学报(自然科学版), 2023, 63(6): 1003-1011.
[7]  甘雨, 吴雨, 王建勇. 新冠肺炎疫情趋势预测模型[J]. 智能系统学报, 2021, 16(3): 528-536.
[8]  刘小惠, 何阳, 麻先思, 罗良清. 有关新冠肺炎潜伏期和疑似期的统计数据分析: 基于湖北省外2172条确诊数据[J]. 应用数学学报, 2020, 43(2): 278-294.
[9]  徐听怡, 顾蓓青. 基于BS疲劳寿命分布的新型冠状病毒肺炎潜伏期的实证研究[J]. 数理统计与管理, 2022, 41(6): 982-988.
[10]  叶莹, 范威, 王文华, 等. 新型冠状病毒肺炎潜伏期分析[J]. 实用预防医学, 2021, 28(2): 129-131.
[11]  周瑜, 郑庭庭. 具有潜伏期时滞的登革热病毒传播模型研究[J]. 首都师范大学学报(自然科学版), 2020, 41(4): 7-12.
[12]  邱明悦, 胡涛, 崔恒建. 双区间删失下新冠病毒肺炎潜伏期分布的参数估计[J]. 应用数学学报, 2020, 43(2): 200-210.
[13]  张美玲. 基于广义差异比混合治愈模型对新型冠状病毒肺炎潜伏期的统计分析[D]: [硕士学位论文]. 大连: 大连理工大学, 2021.
[14]  赵宜宾, 张艳芳, 任晴晴. 基于对数正态分布的新型冠状病毒肺炎病例统计特征分析[J]. 工程数学学报, 2022, 39(4): 589-598.
[15]  于洋. 对数正态分布的几个性质及其参数估计[J]. 廊坊师范学院学报(自然科学版), 2011, 11(5): 8-11.
[16]  于晓红, 张来斌, 王朝晖, 等. 基于新的威布尔分布参数估计法的设备寿命可靠性分析[J]. 机械强度, 2007, 29(6): 932-936.

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