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印度各地新冠疫情数据报告质量参差不齐。

Disparity in the quality of COVID-19 data reporting across India.

作者信息

Vasudevan Varun, Gnanasekaran Abeynaya, Sankar Varsha, Vasudevan Siddarth A, Zou James

出版信息

medRxiv. 2020 Aug 5:2020.07.19.20157248. doi: 10.1101/2020.07.19.20157248.

Abstract

BACKGROUND

Transparent and accessible reporting of COVID-19 data is critical for public health efforts. Each state and union territory (UT) of India has its own mechanism for reporting COVID-19 data, and the quality of their reporting has not been systematically evaluated. We present a comprehensive assessment of the quality of COVID-19 data reporting done by the Indian state and union territory governments. This assessment informs the public health efforts in India and serves as a guideline for pandemic data reporting by other governments.

METHODS

We designed a semi-quantitative framework to assess the quality of COVID-19 data reporting done by the states and union territories of India. This framework captures four key aspects of public health data reporting - availability, accessibility, granularity, and privacy. We then used this framework to calculate a COVID-19 Data Reporting Score (CDRS, ranging from 0 to 1) for 29 states based on the quality of COVID-19 data reporting done by the state during the two-week period from 19 May to 1 June, 2020. States that reported less than 10 total confirmed cases as of May 18 were excluded from the study.

FINDINGS

Our results indicate a strong disparity in the quality of COVID-19 data reporting done by the state governments in India. CDRS varies from 0.61 (good) in Karnataka to 0.0 (poor) in Bihar and Uttar Pradesh, with a median value of 0.26. Only ten states provide a visual representation of the trend in COVID-19 data. Ten states do not report any data stratified by age, gender, comorbidities or districts. In addition, we identify that Punjab and Chandigarh compromised the privacy of individuals under quarantine by releasing their personally identifiable information on the official websites. Across the states, the CDRS is positively associated with the state's sustainable development index for good health and well-being (Pearson correlation: r=0.630, p=0.0003).

INTERPRETATION

The disparity in CDRS across states highlights three important findings at the national, state, and individual level. At the national level, it shows the lack of a unified framework for reporting COVID-19 data in India, and highlights the need for a central agency to monitor or audit the quality of data reporting done by the states. Without a unified framework, it is difficult to aggregate the data from different states, gain insights from them, and coordinate an effective nationwide response to the pandemic. Moreover, it reflects the inadequacy in coordination or sharing of resources among the states in India. Coordination among states is particularly important as more people start moving across states in the coming months. The disparate reporting score also reflects inequality in individual access to public health information and privacy protection based on the state of residence.

FUNDING

J.Z. is supported by NSF CCF 1763191, NIH R21 MD012867-01, NIH P30AG059307, NIH U01MH098953 and grants from the Silicon Valley Foundation and the Chan-Zuckerberg Initiative.

摘要

背景

透明且可获取的新冠疫情数据报告对于公共卫生工作至关重要。印度的每个邦和联邦属地都有自己的新冠疫情数据报告机制,但其报告质量尚未得到系统评估。我们对印度各邦和联邦属地政府的新冠疫情数据报告质量进行了全面评估。该评估为印度的公共卫生工作提供参考,并为其他政府的疫情数据报告提供指导。

方法

我们设计了一个半定量框架来评估印度各邦和联邦属地的新冠疫情数据报告质量。该框架涵盖了公共卫生数据报告的四个关键方面——可获取性、可访问性、粒度和隐私性。然后,我们根据2020年5月19日至6月1日这两周内各邦的新冠疫情数据报告质量,使用该框架为29个邦计算了新冠疫情数据报告得分(CDRS,范围从0到1)。截至5月18日报告的确诊病例总数少于10例的邦被排除在研究之外。

结果

我们的结果表明,印度各邦政府的新冠疫情数据报告质量存在巨大差异。CDRS从卡纳塔克邦的0.61(良好)到比哈尔邦和北方邦的0.0(差)不等,中位数为0.26。只有十个邦提供了新冠疫情数据趋势的可视化表示。十个邦没有报告按年龄、性别、合并症或地区分层的任何数据。此外,我们发现旁遮普邦和昌迪加尔通过在官方网站上公布隔离人员的个人身份信息,侵犯了他们的隐私。在各邦中,CDRS与该邦的健康与福祉可持续发展指数呈正相关(皮尔逊相关系数:r = 0.630,p = 0.0003)。

解读

各邦之间CDRS的差异在国家、邦和个人层面突出了三个重要发现。在国家层面,它表明印度缺乏统一的新冠疫情数据报告框架,并强调需要一个中央机构来监督或审计各邦的数据报告质量。没有统一的框架,就难以汇总来自不同邦的数据、从中获取见解并协调全国范围内对疫情的有效应对。此外,它反映了印度各邦之间在资源协调或共享方面的不足。随着未来几个月越来越多的人开始跨邦流动,邦际协调尤为重要。不同的报告得分还反映了基于居住邦的个人在获取公共卫生信息和隐私保护方面的不平等。

资金来源

J.Z. 得到了美国国家科学基金会CCF 1763191、美国国立卫生研究院R21 MD012867 - 01、美国国立卫生研究院P30AG059307、美国国立卫生研究院U01MH098953以及硅谷基金会和陈 - 扎克伯格倡议的资助。

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