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Disparity in the quality of COVID-19 data reporting across India.
Vasudevan, Varun; Gnanasekaran, Abeynaya; Sankar, Varsha; Vasudevan, Siddarth A; Zou, James.
Afiliación
  • Vasudevan V; Institute for Computational & Mathematical Engineering, Stanford University, Palo Alto, California, USA. devan@stanford.edu.
  • Gnanasekaran A; Institute for Computational & Mathematical Engineering, Stanford University, Palo Alto, California, USA.
  • Sankar V; Independent Researcher, Palo Alto, California, USA.
  • Vasudevan SA; Independent Researcher, Neuchatel, Switzerland.
  • Zou J; Department of Biomedical Data Science, Stanford University, Palo Alto, California, USA.
BMC Public Health ; 21(1): 1211, 2021 06 24.
Article en En | MEDLINE | ID: mdl-34167499
ABSTRACT

BACKGROUND:

Transparent and accessible reporting of COVID-19 data is critical for public health efforts. Each Indian state 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 governments between 19 May and 1 June, 2020.

METHODS:

We designed a semi-quantitative framework with 45 indicators to assess the quality of COVID-19 data reporting. The framework captures four key aspects of public health data reporting - availability, accessibility, granularity, and privacy. We used this framework to calculate a COVID-19 Data Reporting Score (CDRS, ranging from 0-1) for each state.

RESULTS:

Our results indicate a large disparity in the quality of COVID-19 data reporting across 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. Ten states do not report data stratified by age, gender, comorbidities or districts. Only ten states provide trend graphics for COVID-19 data. In addition, we identify that Punjab and Chandigarh compromised the privacy of individuals under quarantine by publicly releasing their personally identifiable information. 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).

CONCLUSIONS:

Our assessment informs the public health efforts in India and serves as a guideline for pandemic data reporting. The disparity in CDRS 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, and coordinate an effective nationwide response to the pandemic. Moreover, it reflects the inadequacy in coordination or sharing of resources among the states. The disparate reporting score also reflects inequality in individual access to public health information and privacy protection based on the state of residence.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: BMC Public Health Asunto de la revista: SAUDE PUBLICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: BMC Public Health Asunto de la revista: SAUDE PUBLICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos