Suppr超能文献

中国河南 1212 例 COVID-19 患者的统计和网络分析。

Statistical and network analysis of 1212 COVID-19 patients in Henan, China.

机构信息

School of Mathematics and Statistics, Henan University, Kaifeng, 475004, China; Institute of Applied Mathematics, Henan University, Kaifeng, 475004, China; Laboratory of Data Analysis Technology, Henan University, 475004, Kaifeng, China.

School of Mathematics and Statistics, Wuhan University, Wuhan, 430070, China.

出版信息

Int J Infect Dis. 2020 Jun;95:391-398. doi: 10.1016/j.ijid.2020.04.051. Epub 2020 Apr 24.

Abstract

BACKGROUND

COVID-19 is spreading quickly all over the world. Publicly released data for 1212 COVID-19 patients in Henan of China were analyzed in this paper.

METHODS

Various statistical and network analysis methods were employed.

RESULTS

We found that COVID-19 patients show gender (55% vs 45%) and age (81% aged between 21 and 60) preferences; possible causes were explored. The estimated average, mode and median incubation periods are 7.4, 4 and 7 days. Incubation periods of 92% of patients were no more than 14 days. The epidemic in Henan has undergone three stages and has shown high correlations with the numbers of patients recently returned from Wuhan. Network analysis revealed that 208 cases were clustering infected, and various People's Hospitals are the main force in treating COVID-19.

CONCLUSIONS

The incubation period was statistically estimated, and the proposed state transition diagram can explore the epidemic stages of emerging infectious disease. We suggest that although the quarantine measures are gradually working, strong measures still might be needed for a period of time, since ∼7.45% of patients may have very long incubation periods. Migrant workers or college students are at high risk. State transition diagrams can help us to recognize the time-phased nature of the epidemic. Our investigations have implications for the prevention and control of COVID-19 in other regions of the world.

摘要

背景

COVID-19 在全球迅速传播。本文分析了中国河南的 1212 例 COVID-19 患者的公开数据。

方法

采用了各种统计和网络分析方法。

结果

我们发现 COVID-19 患者存在性别(55% vs 45%)和年龄(81% 年龄在 21-60 岁之间)偏好;探讨了可能的原因。估计的平均、模态和中位数潜伏期分别为 7.4 天、4 天和 7 天。92%的患者潜伏期不超过 14 天。河南的疫情经历了三个阶段,与近期从武汉返回的患者数量密切相关。网络分析显示,208 例病例呈聚类感染,各人民医院是治疗 COVID-19 的主要力量。

结论

潜伏期进行了统计学估计,提出的状态转移图可以探索新发传染病的流行阶段。我们建议,尽管隔离措施逐渐生效,但在一段时间内仍可能需要采取强有力的措施,因为约 7.45%的患者潜伏期可能很长。农民工或大学生处于高风险之中。状态转移图可以帮助我们认识到疫情的阶段性。我们的调查对世界其他地区 COVID-19 的预防和控制具有启示意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/958e/7180361/b93159c571b6/gr1_lrg.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验