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COVID-19 and the Elderly: Who Cares?新冠病毒肺炎与老年人:谁来关心?
Front Public Health. 2020 Apr 21;8:151. doi: 10.3389/fpubh.2020.00151. eCollection 2020.
2
COVID-19, Mental Health and Aging: A Need for New Knowledge to Bridge Science and Service.新型冠状病毒肺炎、心理健康与老龄化:需要新知识来弥合科学与服务之间的差距
Am J Geriatr Psychiatry. 2020 Jul;28(7):695-697. doi: 10.1016/j.jagp.2020.03.007. Epub 2020 Mar 25.
3
The Exponentially Increasing Rate of Patients Infected with COVID-19 in Iran.伊朗 COVID-19 感染患者呈指数级增长。
Arch Iran Med. 2020 Apr 1;23(4):235-238. doi: 10.34172/aim.2020.03.
4
Epidemiology, causes, clinical manifestation and diagnosis, prevention and control of coronavirus disease (COVID-19) during the early outbreak period: a scoping review.新型冠状病毒病(COVID-19)在早期暴发期间的流行病学、病因、临床表现和诊断、预防和控制:范围综述。
Infect Dis Poverty. 2020 Mar 17;9(1):29. doi: 10.1186/s40249-020-00646-x.
5
The SARS-CoV-2 outbreak: What we know.新型冠状病毒爆发:我们所知道的。
Int J Infect Dis. 2020 May;94:44-48. doi: 10.1016/j.ijid.2020.03.004. Epub 2020 Mar 12.
6
Assessing the Impact of Reduced Travel on Exportation Dynamics of Novel Coronavirus Infection (COVID-19).评估旅行减少对新型冠状病毒感染(COVID-19)传播动态的影响。
J Clin Med. 2020 Feb 24;9(2):601. doi: 10.3390/jcm9020601.
7
An interactive web-based dashboard to track COVID-19 in real time.一个基于网络的交互式仪表盘,用于实时追踪新冠病毒。
Lancet Infect Dis. 2020 May;20(5):533-534. doi: 10.1016/S1473-3099(20)30120-1. Epub 2020 Feb 19.
8
Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19).新冠肺炎(COVID-19)康复过程中胸部 CT 肺部变化的时间进程。
Radiology. 2020 Jun;295(3):715-721. doi: 10.1148/radiol.2020200370. Epub 2020 Feb 13.
9
A novel sub-epidemic modeling framework for short-term forecasting epidemic waves.一种新的亚流行建模框架,用于短期预测疫情波。
BMC Med. 2019 Aug 22;17(1):164. doi: 10.1186/s12916-019-1406-6.
10
Using phenomenological models for forecasting the 2015 Ebola challenge.运用现象学模型预测 2015 年埃博拉病毒挑战
Epidemics. 2018 Mar;22:62-70. doi: 10.1016/j.epidem.2016.11.002. Epub 2016 Nov 19.

评估新冠疫情对印度高危年龄组人群的影响。

Estimating the Impact of Covid-19 Outbreak on High-Risk Age Group Population in India.

作者信息

Singh Harjit Pal, Khullar Vikas, Sharma Monica

机构信息

CT Institute of Engineering, Management and Technology, Jalandhar, India.

GNA University, Phagwara, India.

出版信息

Augment Hum Res. 2020;5(1):18. doi: 10.1007/s41133-020-00037-9. Epub 2020 Jul 1.

DOI:10.1007/s41133-020-00037-9
PMID:40477092
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7327483/
Abstract

The new pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), originated at Wuhan, Hubei province, China in December 2019, threatening the world and becomes the public health crisis throughout the globe. Due to changing data and behavior of the current epidemic, appropriate pharmacological techniques to cure are getting delayed day by day. The estimated trends of the global and Indian region for COVID-19 epidemic were predicted for the next 21 days till 05/05/2020 on the data recorded till 14/04/2020 in the present work. The main focus of the work was to estimate the trends of COVID-19 outbreak on population, especially the high-risk age group of elderly people (with age 50 years and greater) in the Republic of India. It was observed that this identified age-group could be more prone to SARS-CoV-2 virus infection and chances of death in this age group could be more. The high-risk Indian states/regions were also identified throughout the nation and trends for infection, death, and cured cases were predicted for the next 21 days. The outcome of the present work was presented in terms of suggestions that the proper social and medical care for the identified high-risk age group of elderly people of the Indian population should be required to prevent the COVID-19 community transmission. The work also supported the extension in countrywide proper lockdown, mass testing, and also the strict rules to follow social distancing.

摘要

由严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引起的新型大流行于2019年12月起源于中国湖北省武汉市,威胁着全世界,并成为全球公共卫生危机。由于当前疫情数据和行为的变化,合适的治疗药理学技术日益滞后。在本研究中,根据截至2020年4月14日记录的数据,预测了全球和印度地区未来21天(直至2020年5月5日)的COVID-19疫情趋势。这项工作的主要重点是评估COVID-19疫情在人群中的趋势,特别是印度共和国高危年龄组的老年人(年龄50岁及以上)。据观察,这一确定的年龄组可能更容易感染SARS-CoV-2病毒,且该年龄组的死亡几率可能更高。还确定了印度全国范围内的高危邦/地区,并预测了未来21天的感染、死亡和治愈病例趋势。本研究结果以建议的形式呈现,即需要对印度人口中确定的高危年龄组老年人提供适当的社会和医疗护理,以防止COVID-19的社区传播。该研究还支持在全国范围内延长适当的封锁、大规模检测以及严格遵守社交距离的规定。