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      Global Population Aging, National Development Level, and Vulnerability to the Pandemic

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          Abstract

          Purpose

          This study examined the roles of population aging and national development level in affecting different phases of novel coronavirus disease development with a view to advancing preparedness and corresponding policy.

          Methods

          Regression analysis was conducted using multisource data from the World Bank and Johns Hopkins COVID-19 Dashboard.

          Results

          Population aging is positively associated with confirmed cases of day-10, day-20, and day-30. The positive association between population aging and death does not emerge until day-20. Countries with a higher proportion of older males face higher risks of death.. Countries with a higher proportion of males aged 70–74 years are at the highest risk of confirmed cases. National development level is not associated with confirmed cases, but developing countries face significantly higher risks of death of day-10 and day-20.

          Conclusion

          Prevention and control policies for older adults and underdeveloped areas and sex differences need to be studied.

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          Most cited references66

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          Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy

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            Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis

            Highlights • COVID -19 cases are now confirmed in multiple countries. • Assessed the prevalence of comorbidities in infected patients. • Comorbidities are risk factors for severe compared with non-severe patients. • Help the health sector guide vulnerable populations and assess the risk of deterioration.
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              Comorbidity and its impact on 1590 patients with Covid-19 in China: A Nationwide Analysis

              Background The coronavirus disease 2019 (Covid-19) outbreak is evolving rapidly worldwide. Objective To evaluate the risk of serious adverse outcomes in patients with coronavirus disease 2019 (Covid-19) by stratifying the comorbidity status. Methods We analysed the data from 1590 laboratory-confirmed hospitalised patients 575 hospitals in 31 province/autonomous regions/provincial municipalities across mainland China between December 11th, 2019 and January 31st, 2020. We analyse the composite endpoints, which consisted of admission to intensive care unit, or invasive ventilation, or death. The risk of reaching to the composite endpoints was compared according to the presence and number of comorbidities. Results The mean age was 48.9 years. 686 patients (42.7%) were females. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached to the composite endpoints. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD [hazards ratio (HR) 2.681, 95% confidence interval (95%CI) 1.424–5.048], diabetes (HR 1.59, 95%CI 1.03–2.45), hypertension (HR 1.58, 95%CI 1.07–2.32) and malignancy (HR 3.50, 95%CI 1.60–7.64) were risk factors of reaching to the composite endpoints. The HR was 1.79 (95%CI 1.16–2.77) among patients with at least one comorbidity and 2.59 (95%CI 1.61–4.17) among patients with two or more comorbidities. Conclusion Among laboratory-confirmed cases of Covid-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes.
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                Author and article information

                Journal
                Risk Manag Healthc Policy
                Risk Manag Healthc Policy
                rmhp
                rmhp
                Risk Management and Healthcare Policy
                Dove
                1179-1594
                18 February 2021
                2021
                : 14
                : 705-717
                Affiliations
                [1 ]School of Tourism Management, Sun Yat-Sen University , Guangzhou, People’s Republic of China
                [2 ]Institute of Advanced Studies in Humanities and Social Sciences, Beijing Normal University , Beijing, People’s Republic of China
                Author notes
                Correspondence: Jiannan Li Beijing Normal University , 19 Xinjiekouwai Street, Haidian District, Beijing, People’s Republic of China Email 91122020111@bnu.edu.cn
                Guojun Zeng Sun Yat-Sen University , 135 West Xingang Road, Haizhu District, Guangzhou, People’s Republic of China Email zenggj@mail.sysu.edu.cn
                Author information
                http://orcid.org/0000-0002-6918-5483
                http://orcid.org/0000-0001-5981-6731
                http://orcid.org/0000-0002-2932-2949
                Article
                292440
                10.2147/RMHP.S292440
                7917308
                33658872
                35ca6f95-32a6-4671-885a-1b66b1c88097
                © 2021 Yuan et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                History
                : 18 November 2020
                : 01 January 2021
                Page count
                Figures: 4, Tables: 2, References: 66, Pages: 13
                Funding
                Funded by: National Social Science Fund of China;
                We appreciate the support from the National Social Science Fund of China (20CTY017).
                Categories
                Original Research

                Social policy & Welfare
                population aging,sex difference,policy preparedness,national development level,pandemic

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