India has been in regular and in-depth technical exchanges with WHO on the issue. While using
mortality figures directly obtained from Tier –I set of countries, the analysis uses a mathematical modelling process for Tier II countries (which includes India). India’s primary objective has not been with the result (whatever they might have been) but rather the methodology adopted.
India has shared its concerns with the methodology along with the other Member States through a series of formal communications including six letters issued to WHO (on 17 November, 20 December 2021, 28 December 2021, 11 January 2022, 12 February 2022 and 2 March 2022) and virtual meetings held on 16 December 2021, 28 December 2021, 6 January 2022, 25 February 2022 and the SEARO Regional Webinar held on 10th February 2022. During these exchanges, specific queries have been raised by India and the other Member States, e.g. China, Iran, Bangladesh, Syria, Ethiopia and Egypt, regarding the methodology and use of unofficial data sets.
The concern includes explicitly how the statistical model projects estimates for a country of geographical size & population of India and also fits in with other countries with a smaller population. Such a one-size-fits-all approach and models for smaller countries like Tunisia may not apply to India, with a population of 1.3 billion. WHO is yet to share the confidence interval for the present statistical model across various countries.
The model gives two highly different sets of excess mortality estimates when using the data from Tier I countries and unverified data from 18 Indian States. Such wide variation in estimates raises concerns about the validity and accuracy of such a modelling exercise.
India has asserted that if the model was accurate and reliable, it should be authenticated by running it for all Tier I countries. The result of such exercise may be shared with all Member States.
The model assumes an inverse relationship between monthly temperature and monthly average deaths, which does not have any scientific backing to establish such a particular empirical relationship. India is a country of continental proportions; climatic and seasonal conditions vary vastly across different states and even within a state, and therefore, all states have widely varied seasonal patterns. Thus, estimating national level mortality based on these 18 States data is statistically unproven.
The Global Health Estimates (GHE) 2019, on which the modelling for Tier II countries is based is an estimate. The present modelling exercise seems to provide calculations based on another set of historical estimates, disregarding the country’s available data. It is unclear why GHE 2019 has been used for estimating expected deaths figures for India. In contrast, for the Tier 1 countries, their historical datasets were used when it has been repeatedly highlighted that India has a robust data collection and management system.
To calculate the age-sex death distribution for India, WHO determined standard patterns for age and sex for the countries with reported data (61 countries) and then generalized them to the other countries (incl. India) that had no such distribution in their mortality data. Based on this approach, India’s age-sex distribution of predicted deaths was extrapolated based on the distribution of deaths reported by four countries (Costa Rica, Israel, Paraguay and Tunisia).
Of the covariates used for analysis, a binary measure for income has been used instead of a more realistic graded variable. Using a binary variable for such an important measure may lend itself to amplifying the magnitude of the variable. WHO has conveyed that a combination of these variables was found to be most accurate for predicting excess mortality for a sample of 90 countries and 18 months (January 2020-June, 2021). The detailed justification of how the combination of these variables is found to be most accurate is yet to be provided by WHO.
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The test positivity rate for Covid-19 in India was never uniform throughout the country at any point in time. But, this variation in covid-19 positivity rate within India was not considered for modelling purposes. Further, India has undertaken COVID-19 testing faster than what WHO has advised. India has maintained molecular testing as preferred and used Rapid Antigen for screening purposes only. Whether these factors have been used in the model for India is still unanswered.
Containment involves many subjective approaches (such as school closing, workplace closing, cancelling of public events etc.) to quantify itself. But, it is impossible to quantify various containment measures in such a manner for a country like India, as the strictness of such measures has varied widely even among the States and Districts of India. Therefore, the approach followed in this process is very much questionable. In addition, a subjective approach to quantifying such measures will always involve many biases that will not present the actual situation. WHO has also agreed about the subjective approach of this measure. However, it is still used.
While India has expressed the above and similar concerns with WHO but a satisfactory response is yet to be received from WHO.
During interactions with WHO, it has also been highlighted that some fluctuations in official reporting of COVID-19 data from some of the Tier I countries, including the USA, Germany, France etc., defied knowledge of disease epidemiology. Further inclusion of a country like Iraq undergoing a complex extended emergency under Tier I countries raises doubts on WHO’s assessment in categorising countries as Tier I/II and its assertion on quality of mortality reporting from these countries.
While India has remained open to collaborating with WHO as data sets like these will be helpful from the policy-making point of view, India believes that in-depth clarity on methodology and clear proof of its validity are crucial for policymakers to feel confident about any use of such data.
It is shocking that while New York Times purportedly could obtain the alleged figures of excess COVID19 mortality with respect to India, it was “unable to learn the estimates for other countries”!
