DELHI, APRIL 16:India has been in regular and in-depth technical exchange with WHO on the issue. The analysis while uses mortality figures directly obtained from Tier –I set of countries, uses a mathematical modelling process for Tier II countries (which includes India). India’s basic objection has not been with the result (whatever they might have been) but rather the methodology adopted for the same.
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India has shared its concerns with the methodology along with other Member States through a series of formal communications including six letters issued to WHO (on 17th November, 20th December 2021, 28thDecember 2021, 11th January 2022, 12thFebruary 2022 and 2nd March 2022) and virtual meetings held on 16th December 2021, 28th December 2021, 6th January 2022, 25th February 2022 and the SEARO Regional Webinar held on 10th February 2022. During these exchanges, specific queries have been raised by India along with other Member States e.g. China, Iran, Bangladesh, Syria, Ethiopia and Egypt regarding the methodology, and use of unofficial sets of data.
The concern specifically includes on how the statistical model projects estimates for a country of geographical size & population of India and also fits in with other countries which have smaller population. Such one size fit all approach and models which are true for smaller countries like Tunisia may not be applicable 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 of when using the data from Tier I countries and when using unverified data from 18 Indian States. Such wide variation in estimates raises concerns about validity and accuracy of such a modelling exercise.
India has asserted that if the model accurate and reliable, it should be authenticated by running it for all Tier I countries and if 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 peculiar 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 modeling for Tier II countries is based, is itself an estimate. The present modeling exercise seems to be providing its own set of estimates based on another set of historic estimates, while disregarding the data available with the country. It is not clear as to why GHE 2019 has been used for estimating expected deaths figures for India, whereas for the Tier 1 countries, their own historical datasets were used when it has been repeatedly highlighted that India has a robust system of data collection and management.
In order 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) who 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 age-sex 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.
The test positivity rate for Covid-19 in India was never uniform throughout the country at any point of time. But, this variation in covid-19 positivity rate within the India was not considered for modeling purposes. Further, India has undertaken COVID-19 testing at much faster rate then what WHO has advised. India has maintained molecular testing as preferred testing methods and used Rapid Antigen as screening purpose only. Whether these factors have been used in the model for India is still unanswered.
Containment involves a lot of subjective approach (such as school closing, workplace closing, cancelling of public events etc.,) to quantify itself. But, it is actually impossible to quantify various measures of containment in such a manner for a country like India, as the strictness of such measures have varied widely even among the States and Districts of India. Therefore, the approach followed in this process is very much questionable. In addition, subjective approach to quantify such measures will always involve a lot of biasness which will surely not present the real situation. WHO has also agreed about the subjective approach of this measure. However, it is still used.
While India has expressed above and such 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 USA, Germany, France etc. defied knowledge of disease epidemiology. Further inclusion of a country like Iraq which is undergoing an extended complex emergency under Tier I countries raises doubts on WHO’s assessment in categorization of countries as Tier I/II and its assertion on quality of mortality reporting from these countries.
While India has remained open to collaborate 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 policy makers to feel confident about any use of such data.
It is very surprising that while New York Times purportedly could obtain the alleged figures of excess COVID19 mortality in respect to India, it was “unable to learn the estimates for other countries”!!