On 11 March 2020, the World Health Organization (WHO) declared covid to be a global pandemic. As the world came to a standstill, all eyes turned towards the trajectory of the virus. For many, the interactive web-based dashboard created by a small team at the US-based Johns Hopkins University was the first port of call. Given the public hunger for covid data, many countries set up similar dashboards, providing a wealth of information to their citizens.
Among large, there was one outlier that did not set up such a portal: India. The country’s Union health ministry only provided state-wise daily infection and death numbers, without providing either back data for previous days or a tool to examine trends at a more granular level. The ministry struggled to maintain a regular schedule even for putting out these bare details. The country’s most widely-used covid portal, Covid19india.org came up thanks to a volunteer-driven initiative.
The Center’s lack of interest in making covid data accessible was matched only by its enthusiasm to track citizens’ movement data during the pandemic. It quickly gathered the will and resources to launch an app for that. Aarogya Setu proved to be of limited utility, and only aroused the suspicion of a war citizen. If only the government had spent similar efforts in creating an app that provided detailed testing and infection data at a neighborhood level, it would have met people’s data needs better. It would also have created an opportunity to improve data quality. People would have spotted mismatches in their local tallies, and a system responsive to their feedback would have become more accurate over time.
An authentic geo-tagged database would have given epidemiologists a better shot at predicting the evolution of the epidemic. The horrific second wave could perhaps have been averted. This tells us that an open data ecosystem can be literally life-saving. That’s the first pandemic data lesson.
The manner in which ministers and government officials used flawed covid data was even more problematic. Many of them used it to reinforce just one message: India was ‘managing’ the pandemic better than peers. During those phases, when even the official numbers looked scary, these officials disappeared from public view.
An ‘India Shining’ message came from the top and trickled down to states and districts. Much of the ‘covid management’ protocol focused on imposing stringent conditions for recording covid deaths. State governments set up audit committees to certify covid deaths. Across several states, members of these panels faced pressure to whittle down death tolls, as data journalist Rukmini S. wrote in her book, Whole Numbers and Half Truths.
Yet, several government officials used these very numbers to argue that India’s covid mortality rate was much lower than its peers. At some point, they perhaps began believing their own hype. What else explains the poor progress in ramping up health infrastructure and the slow pace of the vaccination program till the second wave hit us in the spring of 2021?
This brings us to the second pandemic data lesson: When data quality is poor, uncritical use of data in policymaking is fraught with dangers.
Given that the government itself generates the metrics by which its performance is judged, there is an inherent conflict of interest in the official statistical system. Any data that showcases the achievements of the government is trumpeted, the rest is liable to be tampered with. Political pressures on data systems may vary across time and space, but they are omnipresent.
To tackle this issue, most mature democracies have institutionalized a system of independent oversight and regular audits of core databases. India’s progress on this front has been extremely tardy (See ‘Let’s revamp our data ecosystem: A wish list for 2022’, Mint, 4 January 2022). So when the health ministry was struggling to provide accurate, relevant and timely data, there was no agency that could point out its failings and set things right. There was little attempt even to harmonize data reporting norms across states.
A well-regulated data ecosystem is very hard to build overnight. But countries that invest in such systems in normal years are able to reap the benefits during a crisis. For instance, the UK’s statistics watchdog, the Office for Statistics Regulation (OSR), made several interventions throughout the pandemic to keep the data honest.The OSR reported a three-fold jump in case work in the April 2020-March 2021 period largely because of covid-related data complaints.
In one famous intervention, the OSR chief chided the British health minister for misleading the public on testing numbers. The minister had been using data on testing kits that were sent out daily rather than the actual number of tests taking place, perhaps to present an inflated picture of testing. The OSR intervention made him change track. In India, lesser mortals got away with far more serious data abuses.
Ministers and their lackeys will always be tempted to distort data. An independent and credible watchdog can thwart their attempts and keep public data clean and reliable. That’s the third pandemic data lesson.
A healthy democracy needs an empowered statistical regulator that is answerable to its citizens and Parliament rather than the ruling regime. The absence of such a regulator poses grave risks to our well-being.
Pramit Bhattacharya is a Chennai-based journalist. His Twitter handle is prime_b
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