‘Nagaland tops Covid-19 surveillance reporting in India’: Study - Hindustan Times
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‘Nagaland tops Covid-19 surveillance reporting in India’: Study

ByAlice Yhoshü
Aug 31, 2021 10:09 PM IST

The paper which is stated to be currently under review, evaluates and quantifies the reporting quality of surveillance, vaccination, and vacant bed availability.

Nagaland has come out as the state with the best quality of Covid-19 surveillance data reporting in the country as per the findings of a study on Covid-19 data reporting conducted by research students from Stanford University, US and few other health specialists from India.

Representational image (AFP)
Representational image (AFP)

The paper which is stated to be currently under review, evaluates and quantifies the reporting quality of surveillance, vaccination, and vacant bed availability data across more than 100 government platforms (websites and apps) in India during May and June 2021, focusing on granular data.

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It is authored by Varun Vasudevan, Abeynaya Gnanasekaran and Professor James Zou from Stanford University, Bhavik Bansal from the All India Institute of Medical Sciences (AIIMS) New Delhi, public policy and health systems specialist Chandrakant Lahariya and Giridara Gopal Parameswaran from the Center for Disease Dynamics, Economics and Policy, New Delhi.

“Our recent findings show that the quality of surveillance data reporting from Nagaland is the best in the country. Nagaland scored highest in our metric because of high-quality granular data reporting through weekly bulletins,” said co-authors of the study Varun and Abeynaya in a letter to the Nagaland health department on Tuesday, a copy of which was obtained by HT.

Appreciating the effort of the state government in bringing out the “high-quality bulletins”, the letter stated that Nagaland government is empowering people to be proactive about their health by releasing the data and its interpretations, along with public health recommendations.

“It’s a joint effort by team Nagaland, driven by the belief that all data should be made available to the public transparently,” principal secretary of Nagaland Health and Family Welfare Department, Amardeep S Bhatia, told HT.

With India among the top three countries in the world both in Covid-19 cases and death counts, and the pandemic being far from over, the study was stated to have been conducted in view that timely, transparent, and accessible reporting of Covid-19 data continues to be critical for India’s pandemic efforts.

The paper states that Nagaland reports cumulative cases and deaths disaggregated by age and gender and cumulative deaths disaggregated by comorbidities, while in contrast, the low scoring sub-nationals report little or no granular data.

While Nagaland topped the surveillance reporting score, Kerala, Ladakh, Odisha, Punjab and Tamil Nadu followed close. Bihar, Lakshadweep, Uttar Pradesh, and Dadra and Nagar Haveli and Daman and Diu scored the lowest.

As per the study, Chandigarh and Haryana were found to be violating privacy by including individually

identifiable information in their reporting. Chandigarh continues to release a document containing the name and address of people who have completed or are under quarantine, while Haryana is releasing a document containing the name, age, gender, and address of cases from its Jhajjar district.

On vaccination reporting, the paper states that the CoWIN application does not report total vaccination stratified by eligibility category for each dose. The number of severe and serious events disaggregated by vaccine type is missing and only 14 out 36 sub-nationals report on their digital platforms the total vaccination stratified by eligibility category for each dose. Karnataka is the only sub-national that is reporting the number of severe and serious (adverse event following immunization) AEFI cases.

As for vacant bed availability reporting, 20 out of 36 sub-nationals report by hospitals and frequently update them while others are either not publishing any data on vacant bed availability or are reporting the total/vacant number of beds without classifying them.

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