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Half-Truths and Twisted Data Won’t Help Control COVID-19

Half-Truths and Twisted Data Won’t Help Control COVID-19

The US Centres for Disease Control defines epidemiology as “the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems.” As such, epidemiology is the basic science of public health, and it’s important we grasp the salience of this definition to appreciate what follows.

Clinical medicine involves the study of the progression of disease in an individual and attempting to cure individual patients, or relieve symptoms, and improve their quality of life. The terms ‘epidemic’ and ‘pandemic’ on the other hand imply the spread of disease in society at large, beyond the usual levels.

We know of no cure for a COVID-19 infection thus far (apart from the virus to be eliminated from the body by the immune system). Clinical medicine can help by alleviating the symptoms of individual patients and by preventing extreme outcomes like death.

But since the theatre of disease has shifted to society, the task of comprehending disease dynamics and creating policies to control it falls within the realm of epidemiology. And clinical medicine must conform to the needs of epidemiologically determined disease control strategies.

So as such, marginalising the role of epidemiology amounts to undermining disease control. Twisting epidemiological data also has the same effect. Unfortunately, undermining the epidemiological approach and confounding epidemiological data have been a sine qua non of the Indian government’s COVID-19 response.

ICMR’s seroprevalence survey

On June 11, the director-general of the Indian Council of Medical Research (ICMR) Dr Balram Bhargava, NITI Aayog member V.K. Paul and health ministry joint secretary Lav Kumar organised a press briefing in which they presented the findings of a sero-surveillance study that ICMR researchers had conducted. The study’s purpose was to “monitor the trend of SARS-CoV-2 infection transmission”. The final product, however, appears to be the government’s most brazen attempt at twisting epidemiological data.

The trio present at the briefing sought to vindicate the government’s anti-COVID-19 policies by claiming that the study found a COVID-19 prevalence of only 0.73% and an infection fatality rate (IFR) of only 0.08% in the 80-odd districts surveyed, extrapolated to the national level. This, they said, showed that the countrywide lockdown had successfully prevented the widespread transmission of the novel coronavirus and that there was no community transmission in the country yet.

These claims need greater scrutiny. While Bhargava the cardiologist and Paul the neonatologist could have a genuine acumen for epidemiology, the situation demands that the epidemiological data ought to have been vetted by professional epidemiologists.

Then again, epidemiologists have been missing from the government’s policymaking bodies vis-à-vis COVID-19. A statement by Dr D.S.C. Reddy, the head of ICMR’s panel of epidemiologists, that the panel hadn’t been able to access the study’s findings, had already been reported in the press by then. This panel had specifically been set up to identify research priorities and align them with the current level of outbreak, and the government’s response.

Let us now consider the study’s deliberate omissions. Note: For all graphs, the number of COVID-19 cases for different countries have been obtained from WHO’s situation report #142, as used by ICMR. The estimates of the current population in all countries were obtained from Worldometers.

Figure 1: Recreation of graph entitled ‘Cases per lakh population amongst the lowest in the world’ in the press handout issued by the government

According to the first two graphs in the press handout issued by the government, India has a prevalence of 20.77 cases and 0.59 deaths per lakh population – among the lowest in a select group of countries.

Figure 1 reconstructs this first graph. The graph does indeed show the case rate in India to be much lower than those of other countries in the graph; however, in epidemiological terms this comparison  does not hold because it was stated that the data from containment areas in COVID-19 hotspot cities was still being compiled, and that is where one would expect maximum cases.

Additionally, A comparison with other countries shown in Figure 1 is problematic also because the timing and the stage of the pandemic is different for these countries relative to India. While most of these countries have already overcome the first wave of infections, and flattened their respective epidemic curves, India is just about starting to get a glimpse of it: its curve has become considerably steeper even after a punishing lockdown.

Figure 2: Cases per lakh population in India and its neighbouring countries

Ever since US President Donald Trump deemed India to be a developed country, it seems the Modi government is loath to be seen in the company of India’s neighbours. Between Figures 1 and 2, with the exception of China – the first country to face the pandemic – Figure 2 shows all else being equal that some of our poorer neighbours have done much better in controlling the spread of the virus, that too without imposing as inhuman a lockdown as India had to bear.

In its study, ICMR had claimed that “0.73% of the population in these districts had evidence of past exposure to SARS-CoV-2”. The study specifically included adults aged 18 years and above for sero-surveillance. As such, any prevalence – based on the results of this study – can be calculated only for the population in the age group of 18+ years, and not the entire population, as ICMR suggests.

The most outrageous part of the findings presented was that the IFR according to the study was 0.08%. The press handout itself states that in the serological survey, “blood samples [were] collected from the general population and tested for IgG antibodies,” and “if a person [was] IgG positive, it meant they were infected with SARS-CoV-2 in the past.”

Additionally, according to the handout, “sero-surveys are expected to answer the following questions: What percentage of the general population has been infected by the virus? Who are at higher risk of getting infection? Which are the areas where containment efforts need to be strengthened?” Apart from a serum analysis for antibodies, the other data collected pertained to “socio-demographic details” and “history of respiratory symptoms”.

It is amazing that when the question of deaths attributable to COVID-19 infections can’t even be determined by the tools used in the study, how could any kind of mortality rate be arrived at based on the information collected or generated through this study? What is the number of deaths used by ICMR to calculate IFR? How was it obtained and how was its use justified? These are just some of the questions that ICMR would have done well to answer. Perhaps they may yet do so once they discover the answer.

The study’s samples were collected in mid-May. As such, the results will reflect the epidemic’s picture as on or around April 30, factoring in the virus’s incubation period of two weeks.

Granting ICMR’s contention of 0.73% prevalence and .08% IFR, that’s still 1 crore cases and 8,000 deaths around the country as on April 30. However, on that date, India officially had only 33,050 cases and 1,074 deaths. Is the government willing to acknowledge that its anti-COVID-19 strategies fell over like ninepins in being able to detect a minuscule fraction of the total number of existing cases, and that it underestimated the number of deaths by a factor of 8? The consequences of this colossal failure wouldn’t be lost on anyone.

And failures apart, the point is: what credence can one place on such statistics when the officials have not reflected on the adequacy of their efforts (to detect cases and document deaths)? The woefully low number of samples tested per million population in India compared to other countries attests to the redundancy of the prevalence and mortality data published by the government.

Figure 3: Comparison of COVID-19 tests performed per million as on June 24 (countries in Figure 1 and India’s neighbours). Data from Statista.

The sero-surveillance study acquires prominence since it is the first major attempt on the government’s part to study the prevalence of the novel coronavirus in the community. Unfortunately, its epidemiological objectives have been vitiated by political ones. And this is not the only example of its kind. ICMR also courted controversy following the publication of a preprint paper that India’s COVID-19 epidemic could peak around October. ICMR’s response then was a sycophantic one, aimed at buttressing the government’s mishandling of the COVID-19 pandemic – to put it mildly.

Fallacious arguments continue to be forwarded to ultimately claim that community transmission is yet to take root in the country, so the government can persist with its containment strategy. But there is a purpose in the design. The government is clearly avoiding the task of committing resources towards strengthening publicly funded medical care and the need to forthwith nationalise corporate healthcare to meet the prevailing medical-care crisis.

While we could agree that the transmission of the virus is not in the same stage throughout the country, it is mischievous to use all-India averages to advance misleading claims. Amidst all this, the lethargic response of the country’s scientific community at large has been disquieting. Many doctors of eminence occupying positions of great responsibility should realise that they first and foremost owe allegiance to the people of India, not those who are in power for the time being. It is best that they articulate what is in the interest of the people with full force rather than cater to the convenience of the powers that be.

Vikas Bajpai is an assistant professor at the Centre for Social Medicine and Community Health, Jawaharlal Nehru University, New Delhi.

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