A vulnerability index for the management of and response to the COVID-19 epidemic in India: an ecological study
A vulnerability index for the management of and response to the COVID-19 epidemic in India: an ecological study
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DOI：
10.1016/s2214-109x(20)30300-4
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发表时间：
2020-09-01
影响因子：
34.3
通讯作者：
Porwal, Akash
中科院分区：
文献类型：
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作者：
Acharya, Rajib;Porwal, Akash
背景COVID-19在印度和世界其他地区迅速蔓延。尽管印度政府努力控制受影响地区的疾病，但640个地区中有627个（98%）报告了病例。有必要设计一种工具，用于地区一级的规划、优先次序安排和有效分配资源。根据公开的数据，本研究报告的脆弱性指数，以确定在印度的基础上，人口和基础设施的特点。方法，我们计算了一个综合指数的脆弱性在国家和地区层面的基础上，在以下五个领域的15个指标：社会经济，人口，住房和卫生，流行病学，卫生系统。我们使用百分位数排序方法来计算特定领域和整体脆弱性，并在空间上展示了各地区COVID-19阳性病例数的结果。结果九个大邦的一些地区-比哈尔邦，中央邦，特兰加纳，贾坎德，北方邦，马哈拉施特拉邦，西孟加拉，奥里萨邦和古吉拉特邦-位于该国除东北部以外的每个地区，总体脆弱性较高（指数值超过0.75）。根据五个领域中的大多数，这些国家也具有高度脆弱性。尽管我们的目的不是预测一个地区或一个州的感染风险，但我们观察到脆弱性与州一级当前COVID-19病例集中度之间的相似之处。本文提出的脆弱性指数确定了印度的一些脆弱地区，这些地区目前没有大量的COVID-19病例，但可能受到疫情的强烈影响。我们的指数旨在帮助规划者和政策制定者有效地优先考虑资源分配的地区，并采取风险缓解策略，以更好地准备和应对COVID-19疫情。版权所有（C）2020作者。爱思唯尔有限公司出版
Background COVID-19 is spreading rapidly in India and other parts of the world. Despite the Indian Government's efforts to contain the disease in the affected districts, cases have been reported in 627 (98%) of 640 districts. There is a need to devise a tool for district-level planning and prioritisation and effective allocation of resources. Based on publicly available data, this study reports a vulnerability index for identification of vulnerable regions in India on the basis of population and infrastructural characteristics.Methods We computed a composite index of vulnerability at the state and district levels based on 15 indicators across the following five domains: socioeconomic, demographic, housing and hygiene, epidemiological, and health system. We used a percentile ranking method to compute both domain-specific and overall vulnerability and presented results spatially with number of positive COVID-19 cases in districts.Findings A number of districts in nine large states-Bihar, Madhya Pradesh, Telangana, Jharkhand, Uttar Pradesh, Maharashtra, West Bengal, Odisha, and Gujarat-located in every region of the country except the northeast, were found to have high overall vulnerability (index value more than 0.75). These states also had high vulnerability according to most of the five domains. Although our intention was not to predict the risk of infection for a district or a state, we observed similarities between vulnerability and the current concentration of COVID-19 cases at the state level. However, this relationship was not clear at the district level.Interpretation The vulnerability index presented in this paper identified a number of vulnerable districts in India, which currently do not have large numbers of COVID-19 cases but could be strongly impacted by the epidemic. Our index aims to help planners and policy makers effectively prioritise regions for resource allocation and adopt risk mitigation strategies for better preparedness and responses to the COVID-19 epidemic. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.