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使用残疾调整生命年(DALYs)和印度喀拉拉邦生产力损失估算 COVID-19 的经济负担:基于模型的分析。

Estimation of the economic burden of COVID-19 using disability-adjusted life years (DALYs) and productivity losses in Kerala, India: a model-based analysis.

机构信息

Department of Public Health, Amrita Institute of Medical Sciences and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, India

Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India.

出版信息

BMJ Open. 2021 Aug 18;11(8):e049619. doi: 10.1136/bmjopen-2021-049619.

DOI:10.1136/bmjopen-2021-049619
PMID:34408053
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8375445/
Abstract

OBJECTIVES

From the beginning of the COVID-19 pandemic, clinical practice and research globally have centred on the prevention of transmission and treatment of the disease. The pandemic has had a huge impact on the economy and stressed healthcare systems worldwide. The present study estimates disability-adjusted life years (DALYs), years of potential productive life lost (YPPLL) and cost of productivity lost (CPL) due to premature mortality and absenteeism secondary to COVID-19 in the state of Kerala, India.

SETTING

Details on sociodemographics, incidence, death, quarantine, recovery time, etc were derived from public sources and the Collective for Open Data Distribution-Keralam. The working proportion for 5-year age-gender cohorts and the corresponding life expectancy were obtained from the 2011 Census of India.

PRIMARY AND SECONDARY OUTCOME MEASURES

The impact of the disease was computed through model-based analysis on various age-gender cohorts. Sensitivity analysis was conducted by adjusting six variables across 21 scenarios. We present two estimates, one until 15 November 2020 and later updated to 10 June 2021.

RESULTS

Severity of infection and mortality were higher among the older cohorts, with men being more susceptible than women in most subgroups. DALYs for males and females were 15 954.5 and 8638.4 until 15 November 2020, and 83 853.0 and 56 628.3 until 10 June 2021. The corresponding YPPLL were 1323.57 and 612.31 until 15 November 2020, and 6993.04 and 3811.57 until 10 June 2021, and the CPL (premature mortality) were 263 780 579.94 and 41 836 001.82 until 15 November 2020, and 1 419 557 903.76 and 278 275 495.29 until 10 June 2021.

CONCLUSIONS

Most of the COVID-19 burden was contributed by years of life lost. Losses due to YPPLL were reduced as the impact of COVID-19 infection was lesser among the productive cohorts. The CPL values for individuals aged 40-49 years old were the highest. These estimates provide the data necessary for policymakers to work on reducing the economic burden of COVID-19 in Kerala.

摘要

目的

从 COVID-19 大流行开始,全球的临床实践和研究就集中在预防疾病传播和治疗疾病上。这场大流行对全球经济和医疗体系造成了巨大影响。本研究旨在评估印度喀拉拉邦因 COVID-19 导致的过早死亡和缺勤而导致的伤残调整生命年(DALYs)、潜在工作寿命损失年(YPPLL)和生产力损失成本(CPL)。

设定

社会人口统计学、发病率、死亡率、隔离、康复时间等详细信息均来自公共来源和 Collective for Open Data Distribution-Keralam。5 年年龄性别队列的工作比例和相应的预期寿命从 2011 年印度人口普查中获得。

主要和次要结果测量

通过对不同年龄性别队列的基于模型的分析来计算疾病的影响。通过在 21 种情景下调整六个变量进行了敏感性分析。我们提出了两种估计,一种是截至 2020 年 11 月 15 日,后来更新到 2021 年 6 月 10 日。

结果

感染和死亡率在年龄较大的队列中更高,男性在大多数亚组中比女性更易感。截至 2020 年 11 月 15 日,男性和女性的 DALYs 分别为 15954.5 和 8638.4,截至 2021 年 6 月 10 日,分别为 83853.0 和 56628.3。相应的 YPPLL 截至 2020 年 11 月 15 日分别为 1323.57 和 612.31,截至 2021 年 6 月 10 日分别为 6993.04 和 3811.57,CPL(过早死亡)截至 2020 年 11 月 15 日分别为 2637805799.4 元和 4183600182.0 元,截至 2021 年 6 月 10 日分别为 14195579037.6 元和 2782754952.9 元。

结论

COVID-19 的大部分负担是由生命损失年造成的。由于 COVID-19 感染在生产性队列中的影响较小,因此 YPPLL 造成的损失减少了。40-49 岁个体的 CPL 值最高。这些估计值为决策者提供了必要的数据,以减轻喀拉拉邦 COVID-19 的经济负担。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d951/8375445/bb3c6d5e12b2/bmjopen-2021-049619f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d951/8375445/a7faf3e64ce0/bmjopen-2021-049619f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d951/8375445/bb3c6d5e12b2/bmjopen-2021-049619f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d951/8375445/a7faf3e64ce0/bmjopen-2021-049619f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d951/8375445/bb3c6d5e12b2/bmjopen-2021-049619f02.jpg

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