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Wednesday, December 02, 2020

The peak could be premature

Different states are at different stages of the pandemic. With a fresh spurt of cases in Delhi and other cities, it would be wrong to assume that the worst is over.

Updated: November 10, 2020 7:35:06 pm
west bengal coronavirus latest updates, bengal covid cases, bengal covid updates, west bengal covid deaths, bengal covid senior citizens, bengal covid call centresWith the number of Covid-19 cases on the rise in the Tricity, the second wave, say doctors, is proving to be more severe than the first. (Representational Image)

Written by Rijo M John

Last month, a government panel report used mathematical modelling to make the extraordinary claim that COVID-19 cases have peaked in India and the virus will be under control by February 2021. However, the real nature of the peak can only be deduced by looking at multiple variables, including serological surveys and testing patterns. Based on the current data, it is too early to suggest that we have hit “the peak”, especially because different regions in India are at different phases of the pandemic.

Cities such as Delhi and Mumbai are seeing rising number of cases after reaching a “peak” in the past. Till now, the metropolitan and tier-1 cities with dense populations have seen most of the cases. In many rural areas and tier 2, tier 3 cities, the first wave has not passed. With scant medical resources available in these areas, an increasing share of testing capacity should be shifted into these areas.

What explains the falling Covid cases at the national level?

There can be several explanations for a decline in daily new cases currently seen at the national level. One, many densely populated large cities/districts which contributed to a significant share of total reported cases in the past may have already reached higher prevalence of infection as evidenced by sero-surveys leading to fewer new cases from these places. The top 10 cities/districts in terms of the total caseload contribute 26 per cent of the total reported cases in India.

Two, as the infection spreads to smaller towns and rural areas where the population density is much lower, the rate of spread of the virus may be much slower and their relative contribution in the national total would be less.

Three, by Increasingly relying on Rapid Antigen Detection Tests (RADTs) we may be missing out a lot of cases unlike in the early phase of the pandemic where less of RADTs were used.

Four, the rate of growth of tests has decreased along with a decline in the growth rate of cases. This could be due to a weaker testing infrastructure in smaller town and rural areas. It is also possible that people are reluctant about getting tested due to varied reasons ranging from fear of hospitalization and allied costs, social stigma, loss of employment/income to their lack of knowledge and understanding of the disease and its impact.

Five, Increased on-demand testing done at private labs could also affect the probability of reporting detected cases.

Finally, increased testing does not mean testing where it matters. For example, Maharashtra alone has contributed to 21 per cent of reported cases in India while the state conducted only about 7.7 per cent of tests. Uttar Pradesh and Bihar have conducted 22 per cent of all tests in India and yet, reported only 8.6 per cent of cases. Consequently, the very low test positivity rates in both Bihar and Uttar Pradesh pulls down the national average test positivity rate while high positivity from Maharashtra will have the opposite effect. Even within states, testing is not necessarily done were it really matters. For example, Patna alone contributed to 16 per cent of all reported cases in Bihar while conducting only 4.4 per cent of total tests in the state. If states are conducting most of their tests in less prevalent areas and using RADTs in an attempt to showcase better test positivity rates and low case loads, this may be depicting a picture which is good only on paper.

The lack of transparency and insufficiency around the Covid-19 data is obstructing our fight and preparedness against the pandemic. Reporting is not standardised across states and there is a discrepancy in reported testing numbers between the ICMR and those reported jointly by states. While ICMR reported a total of 10.9 crore tests by October end, all states together reported 11.6 crore, a difference of 6.5 per cent.

Only some states report disaggregated data on the type of tests and an even smaller subset report the results by test types. While increasing reliance on RADT may be a more cost effective strategy to find truly positive cases in a resource poor country, no state has furnished data on whether and how many symptomatic false negatives from RADTs are being re-tested as recommended by the ICMR. In fact, in states that predominantly rely on RADT, there may not be sufficient RT-PCR capacity even to do this re-testing. This may be limiting our ability to correctly identify as many cases as possible and potentially cast a shadow on the reported numbers of cases.

In addition, data are unavailable on a slew of variables – such as, cases and deaths split by demographic and socio-economic status which could become highly useful for devising effective mitigation and containment strategies and targeted interventions. Updated information on available oxygen beds and ventilators for COVID-19 patients are also missing in the daily state COVID-19 bulletins of most states.

To get ahead of the curve and fight the pandemic effectively, the authorities need to take the people, including stakeholders such as researchers and scientists, into confidence. This can only be established by sharing the necessary and accurate data transparently with everyone. Even though ‘health’ is a state subject, COVID-19 being a national crisis, the Ministry and ICMR should issue advisories on appropriate reporting standards to states. Before that, these central agencies must themselves showcase excellent examples of data reporting. A pandemic is fought not only with medicines and vaccines, but also with appropriate collection and reporting of useful granular data in a transparent manner.

The writer is a public health economist and an adjunct faculty at Rajagiri College of Social Sciences, Kochi

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