Times of India’s Edit Page team comprises senior journalists with wide-ranging interests who debate and opine on the news and issues of the day.
The outbreak of the global pandemic last year turned the spotlight on an arcane field, applied epidemiology. It provides a guide to decision-making in a world of patchy data. The situation has changed quite a bit since then. There is a lot more knowledge about the SARS-CoV-2 virus. This rapidly growing bank of knowledge complemented by the arrival of vaccines puts all countries on a sounder footing. But the key assumption here is that governments have the right approach to data. Both in terms of collection, the first step, and its subsequent analysis.
Right from the first wave of Covid-19, the world has struggled to capture accurate data. Reasons are many, including lack of resources, social stigma forcing patients to withhold information, and political incentives which favour data suppression. In India, it was clear from the beginning that testing for Covid-19 across states, both in terms of quality and quantity, varied. Large serosurveys carried out by ICMR indicated that the presence of antibodies in the population far exceeded what the test results showed. Its survey carried out over December-January showed that 21% of Indians were exposed to Covid.
Key elements in putting data to good use are its interpretation and the right political incentives. There was nothing in the data to conclusively say that we had reached herd immunity or dealt with the challenge. In another serious shortcoming, it was as late as December that the Indian SARS-CoV-2 Genomics Consortium (INSACOG), a network of 10 labs to monitor genomic changes of SARS-CoV-2, was set up. And it’s still not fulfilling its potential. For example, the B.1.617 variant appears to have played a big role in Maharashtra’s surge but not enough samples have been sequenced and policy response is lagging.
One reason why policy response is inadequate is that political incentives to fudge data are high. There is a clear mismatch between official data on Covid deaths and the reportage across cities over the last few weeks. Under-reporting of crucial data leaves governments ill-equipped to respond. Epidemiology’s usefulness is influenced by the quality of data that can be used. When the data doesn’t capture reality, by design or otherwise, we will be caught napping. It’s important to remember that with a pathogen that is highly infectious, there may not be an endgame. Instead, tools such as reliable data limit its adverse impact, or further waves. So they must be kept sharp, and used smartly.
Courtesy - TOI
0 comments:
Post a Comment