• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

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

2020-2021 年哥伦比亚 2019 年冠状病毒病时空模式调查及预测。

An investigation of spatial-temporal patterns and predictions of the coronavirus 2019 pandemic in Colombia, 2020-2021.

机构信息

Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.

Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia, United States of America.

出版信息

PLoS Negl Trop Dis. 2022 Mar 4;16(3):e0010228. doi: 10.1371/journal.pntd.0010228. eCollection 2022 Mar.

DOI:10.1371/journal.pntd.0010228
PMID:35245285
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8926206/
Abstract

Colombia announced the first case of severe acute respiratory syndrome coronavirus 2 on March 6, 2020. Since then, the country has reported a total of 5,002,387 cases and 127,258 deaths as of October 31, 2021. The aggressive transmission dynamics of SARS-CoV-2 motivate an investigation of COVID-19 at the national and regional levels in Colombia. We utilize the case incidence and mortality data to estimate the transmission potential and generate short-term forecasts of the COVID-19 pandemic to inform the public health policies using previously validated mathematical models. The analysis is augmented by the examination of geographic heterogeneity of COVID-19 at the departmental level along with the investigation of mobility and social media trends. Overall, the national and regional reproduction numbers show sustained disease transmission during the early phase of the pandemic, exhibiting sub-exponential growth dynamics. Whereas the most recent estimates of reproduction number indicate disease containment, with Rt<1.0 as of October 31, 2021. On the forecasting front, the sub-epidemic model performs best at capturing the 30-day ahead COVID-19 trajectory compared to the Richards and generalized logistic growth model. Nevertheless, the spatial variability in the incidence rate patterns across different departments can be grouped into four distinct clusters. As the case incidence surged in July 2020, an increase in mobility patterns was also observed. On the contrary, a spike in the number of tweets indicating the stay-at-home orders was observed in November 2020 when the case incidence had already plateaued, indicating the pandemic fatigue in the country.

摘要

哥伦比亚于 2020 年 3 月 6 日宣布首例严重急性呼吸综合征冠状病毒 2 型病例。自那时以来,截至 2021 年 10 月 31 日,该国共报告了 5002387 例病例和 127258 例死亡病例。SARS-CoV-2 的强传染性促使我们在国家和地区层面上对哥伦比亚的 COVID-19 进行调查。我们利用病例发病率和死亡率数据来估计传播潜力,并使用以前验证过的数学模型生成 COVID-19 大流行的短期预测,为公共卫生政策提供信息。通过检查部门层面 COVID-19 的地理异质性以及对流动性和社交媒体趋势的调查,对分析进行了补充。总体而言,国家和地区的繁殖数显示出在大流行的早期阶段持续的疾病传播,表现出亚指数增长动态。而最近的繁殖数估计表明疾病得到了控制,截至 2021 年 10 月 31 日,Rt<1.0。在预测方面,与 Richards 和广义逻辑增长模型相比,亚流行模型在捕捉 30 天内 COVID-19 轨迹方面表现最佳。然而,不同部门之间发病率模式的空间变异性可以分为四个不同的集群。随着 2020 年 7 月病例发病率的飙升,移动模式也有所增加。相反,当病例发病率已经趋于平稳时,2020 年 11 月表明该国已经出现大流行疲劳的推文中表示居家令的推文数量出现了激增。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/754768c95a2f/pntd.0010228.g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/c542bf818172/pntd.0010228.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/0ec1610b249e/pntd.0010228.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/86b3222ab52c/pntd.0010228.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/5bd370340867/pntd.0010228.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/ea15a1854f0a/pntd.0010228.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/33849ea5cf4c/pntd.0010228.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/00993150fe64/pntd.0010228.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/82072a9dba34/pntd.0010228.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/d6188bf07e0f/pntd.0010228.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/5edcd2056fcc/pntd.0010228.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/0498a1490f3a/pntd.0010228.g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/8e2df9769273/pntd.0010228.g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/93db9efa4308/pntd.0010228.g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/754768c95a2f/pntd.0010228.g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/c542bf818172/pntd.0010228.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/0ec1610b249e/pntd.0010228.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/86b3222ab52c/pntd.0010228.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/5bd370340867/pntd.0010228.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/ea15a1854f0a/pntd.0010228.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/33849ea5cf4c/pntd.0010228.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/00993150fe64/pntd.0010228.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/82072a9dba34/pntd.0010228.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/d6188bf07e0f/pntd.0010228.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/5edcd2056fcc/pntd.0010228.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/0498a1490f3a/pntd.0010228.g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/8e2df9769273/pntd.0010228.g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/93db9efa4308/pntd.0010228.g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/235b/8926206/754768c95a2f/pntd.0010228.g014.jpg

相似文献

1
An investigation of spatial-temporal patterns and predictions of the coronavirus 2019 pandemic in Colombia, 2020-2021.2020-2021 年哥伦比亚 2019 年冠状病毒病时空模式调查及预测。
PLoS Negl Trop Dis. 2022 Mar 4;16(3):e0010228. doi: 10.1371/journal.pntd.0010228. eCollection 2022 Mar.
2
Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March-December 2020.2020年3月至12月墨西哥新冠疫情的传播动态与预测
PLoS One. 2021 Jul 21;16(7):e0254826. doi: 10.1371/journal.pone.0254826. eCollection 2021.
3
Short-Range Forecasting of COVID-19 During Early Onset at County, Health District, and State Geographic Levels Using Seven Methods: Comparative Forecasting Study.使用七种方法在县、卫生区和州地理级别对 COVID-19 进行早期发病的短期预测:比较预测研究。
J Med Internet Res. 2021 Mar 23;23(3):e24925. doi: 10.2196/24925.
4
The performance of phenomenological models in providing near-term Canadian case projections in the midst of the COVID-19 pandemic: March - April, 2020.在 COVID-19 大流行期间,现象学模型在提供加拿大近期病例预测方面的表现:2020 年 3 月-4 月。
Epidemics. 2021 Jun;35:100457. doi: 10.1016/j.epidem.2021.100457. Epub 2021 Mar 19.
5
Is Colombia an example of successful containment of the 2020 COVID-19 pandemic? A critical analysis of the epidemiological data, March to July 2020.哥伦比亚是否是成功控制 2020 年 COVID-19 大流行的范例?对 2020 年 3 月至 7 月的流行病学数据的批判性分析。
Int J Infect Dis. 2020 Oct;99:522-529. doi: 10.1016/j.ijid.2020.08.017. Epub 2020 Aug 11.
6
Short-term real-time prediction of total number of reported COVID-19 cases and deaths in South Africa: a data driven approach.南非报告的 COVID-19 病例和死亡总数的短期实时预测:一种数据驱动的方法。
BMC Med Res Methodol. 2021 Jan 11;21(1):15. doi: 10.1186/s12874-020-01165-x.
7
Estimating and forecasting the burden and spread of Colombia's SARS-CoV2 first wave.估计和预测哥伦比亚 SARS-CoV2 第一波的负担和传播。
Sci Rep. 2022 Aug 9;12(1):13568. doi: 10.1038/s41598-022-15514-x.
8
An ensemble -sub-epidemic modeling framework for short-term forecasting epidemic trajectories: Application to the COVID-19 pandemic in the USA.一种用于短期预测疫情轨迹的集成子疫情建模框架:在美国新冠肺炎疫情中的应用。
medRxiv. 2022 Jun 21:2022.06.19.22276608. doi: 10.1101/2022.06.19.22276608.
9
Dynamic Public Health Surveillance to Track and Mitigate the US COVID-19 Epidemic: Longitudinal Trend Analysis Study.动态公共卫生监测以追踪和缓解美国新冠疫情:纵向趋势分析研究
J Med Internet Res. 2020 Dec 3;22(12):e24286. doi: 10.2196/24286.
10
Impact of weekday and weekend mobility and public policies on COVID-19 incidence and deaths across 76 large municipalities in Colombia: statistical analysis and simulation.哥伦比亚 76 个大城市的工作日和周末流动性和公共政策对 COVID-19 发病率和死亡率的影响:统计分析和模拟。
BMC Public Health. 2022 Dec 31;22(1):2460. doi: 10.1186/s12889-022-14781-7.

引用本文的文献

1
Predictive modelling of the effectiveness of vaccines against COVID-19 in Bogotá: Methodological innovation involving different variants and computational optimisation efficiency.波哥大针对新冠病毒疫苗有效性的预测建模:涉及不同变体和计算优化效率的方法创新
Heliyon. 2024 Oct 23;10(21):e39725. doi: 10.1016/j.heliyon.2024.e39725. eCollection 2024 Nov 15.
2
SpatialWavePredict: a tutorial-based primer and toolbox for forecasting growth trajectories using the ensemble spatial wave sub-epidemic modeling framework.空间波预测:基于教程的入门和工具包,用于使用集合空间波亚流行建模框架预测增长轨迹。
BMC Med Res Methodol. 2024 Jun 7;24(1):131. doi: 10.1186/s12874-024-02241-2.
3

本文引用的文献

1
A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research-An International Collaboration.用于开放科学研究的大规模COVID-19推特聊天数据集——一项国际合作。
Epidemiologia (Basel). 2021 Aug 5;2(3):315-324. doi: 10.3390/epidemiologia2030024.
2
Complex correlates of Colombia's COVID-19 surge.哥伦比亚新冠疫情激增的复杂关联因素。
Lancet Reg Health Am. 2021 Nov;3:100072. doi: 10.1016/j.lana.2021.100072. Epub 2021 Sep 10.
3
Factors Associated With SARS-CoV-2 Infection in Bogotá, Colombia: Results From a Large Epidemiological Surveillance Study.
A tutorial-based primer and toolbox for fitting and forecasting growth trajectories using the ensemble -sub-epidemic modeling framework.
一个基于教程的入门指南和工具箱,用于使用集合-子流行模型框架拟合和预测增长轨迹。
Infect Dis Model. 2024 Feb 9;9(2):411-436. doi: 10.1016/j.idm.2024.02.001. eCollection 2024 Jun.
4
GrowthPredict: A toolbox and tutorial-based primer for fitting and forecasting growth trajectories using phenomenological growth models.GrowthPredict:一个基于工具包和教程的入门指南,用于使用现象学增长模型拟合和预测增长轨迹。
Sci Rep. 2024 Jan 18;14(1):1630. doi: 10.1038/s41598-024-51852-8.
5
A computational approach to identifiability analysis for a model of the propagation and control of COVID-19 in Chile.一种用于分析智利 COVID-19 传播和控制模型可识别性的计算方法。
J Biol Dyn. 2023 Dec;17(1):2256774. doi: 10.1080/17513758.2023.2256774.
6
Barriers to conducting independent quantitative research in low-income countries: A cross-sectional study of public health graduate students in Liberia.在低收入国家开展独立定量研究的障碍:利比里亚公共卫生研究生的横断面研究。
PLoS One. 2023 Feb 2;18(2):e0280917. doi: 10.1371/journal.pone.0280917. eCollection 2023.
7
An ensemble n-sub-epidemic modeling framework for short-term forecasting epidemic trajectories: Application to the COVID-19 pandemic in the USA.一种用于短期预测传染病轨迹的集成 n 亚流行模型框架:在美国 COVID-19 大流行中的应用。
PLoS Comput Biol. 2022 Oct 6;18(10):e1010602. doi: 10.1371/journal.pcbi.1010602. eCollection 2022 Oct.
8
An ensemble -sub-epidemic modeling framework for short-term forecasting epidemic trajectories: Application to the COVID-19 pandemic in the USA.一种用于短期预测疫情轨迹的集成子疫情建模框架:在美国新冠肺炎疫情中的应用。
medRxiv. 2022 Jun 21:2022.06.19.22276608. doi: 10.1101/2022.06.19.22276608.
哥伦比亚波哥大与新型冠状病毒感染相关的因素:一项大型流行病学监测研究的结果
Lancet Reg Health Am. 2021 Oct;2:100048. doi: 10.1016/j.lana.2021.100048. Epub 2021 Aug 23.
4
Data driven high resolution modeling and spatial analyses of the COVID-19 pandemic in Germany.基于数据的德国 COVID-19 大流行的高分辨率建模和空间分析。
PLoS One. 2021 Aug 18;16(8):e0254660. doi: 10.1371/journal.pone.0254660. eCollection 2021.
5
The foreseen loss of the battle against COVID-19 in South America: A foretold tragedy.南美洲抗击新冠疫情可预见的失败:一场注定的悲剧。
EClinicalMedicine. 2021 Sep;39:101068. doi: 10.1016/j.eclinm.2021.101068. Epub 2021 Aug 5.
6
COVID-19 spread, detection, and dynamics in Bogota, Colombia.哥伦比亚波哥大的新冠病毒传播、检测及动态情况
Nat Commun. 2021 Aug 5;12(1):4726. doi: 10.1038/s41467-021-25038-z.
7
Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March-December 2020.2020年3月至12月墨西哥新冠疫情的传播动态与预测
PLoS One. 2021 Jul 21;16(7):e0254826. doi: 10.1371/journal.pone.0254826. eCollection 2021.
8
Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates.新型冠状病毒 2019-nCoV (COVID-19):流行病学参数和疫情规模的早期估计。
Philos Trans R Soc Lond B Biol Sci. 2021 Jul 19;376(1829):20200265. doi: 10.1098/rstb.2020.0265. Epub 2021 May 31.
9
Evaluating epidemic forecasts in an interval format.评估区间格式的疫情预测。
PLoS Comput Biol. 2021 Feb 12;17(2):e1008618. doi: 10.1371/journal.pcbi.1008618. eCollection 2021 Feb.
10
Measuring differences between phenomenological growth models applied to epidemiology.测量应用于流行病学的现象学增长模型之间的差异。
Math Biosci. 2021 Apr;334:108558. doi: 10.1016/j.mbs.2021.108558. Epub 2021 Feb 8.