Expert Speak Health Express
Published on May 12, 2022 Updated 12 Days ago
Questions emerge as GOI dismisses the recently-released report by WHO: Are the COVID-19 death toll numbers fudged or is the WHO’s methodology flawed?
The WHO report on death toll of COVID-19: Unpack the concepts, reset the discourse

The World Health Organization (WHO) recently released a report titled, “Global excess deaths associated with COVID-19, January 2020–December 2021” to present a comprehensive view of global deaths directly and indirectly associated with the COVID-19 pandemic. While the global toll of excess mortality associated with COVID-19 was put at nearly 15 million, nearly 4.7 million excess deaths (a third of the global toll) were attributed to India. This figure contrasted (and perhaps conflated) with the cumulative 0.52 million COVID-19 deaths. At about the same time, the Registrar General of India released the Vital Statistics of India based on the Civil Registration System (CRS) 2020 which provides the mortality statistics for 2020. India observed that “(N)ow that actual count of excess deaths from all the causes is available, there is no rationale for using modelling-driven estimates based on pure conjectures and assumptions”.

The fine distinction between confirmed COVID-19 deaths and excess mortality

Excess mortality refers to the number of deaths from all causes during a crisis, above and beyond what is expected under ‘normal’ conditions. It is a more comprehensive measure of the total impact of the pandemic on deaths that are attributable to the overall crisis conditions than the confirmed COVID-19 death count alone, including:

  • Deaths attributable directly to COVID-19 that were counted and reported to WHO by countries
  • Deaths attributable directly to COVID-19 that were not counted or reported by countries.
  • Deaths indirectly associated with COVID-19, due to other causes and diseases, resulting from the wider impact of the pandemic on health systems and society.
  • Minus any deaths that would have occurred under normal circumstances but were averted due to pandemic-related changes in social conditions and personal behaviours, e.g., fewer traffic deaths or influenza deaths due to local lockdowns and less travel.

India observed that “(N)ow that actual count of excess deaths from all the causes is available, there is no rationale for using modelling-driven estimates based on pure conjectures and assumptions”.

The exercise, therefore, sought to unravel how the number of deaths during the COVID-19 pandemic compares to the deaths that were expected had the pandemic not occurred; by its very nature, it can only be estimated. There are thus two distinct metrics: Confirmed deaths due to COVID-19 and excess mortality due to the pandemic. The confirmed deaths are more often than not an undercount; significantly, they provide information about the cause of death though. Both measures are needed to understand the total impact of the pandemic on deaths. 

The relevance of a parsimonious model

Since excess deaths are estimated and not counted, it necessitates building models. Models have to make the unenviable tradeoff between comprehensiveness and comprehensibility. The WHO experts opted for a parsimonious model, one that is described by a fewer number of parameters with better predictive ability given new data. Effective parsimonious models potentially offer five types of benefits: Fewer data requirements; reduced computational complexity; improved system representation; transparency; and insightfulness.

Parsimonious models are relevant in this case as the behaviour of a population in aggregate is more important than the behaviour of each agent. This model addressed a wide range of covariate data. These included high-income country binary indicator, COVID-19 test positivity rate, COVID-19 death rate, temperature, population density, sociodemographic index (SDI), human development index (HDI), stringency index (for lockdown restrictions and closures), overall government response, economic (including measures such as income support and debt relief), historic non-communicable disease rates, life expectancy, the proportion of the population under-15, and the proportion of the population over-65 years. While, for example, age composition and prevalence of non-communicable diseases could worsen outcomes, containment measures including income support and relief measures could contribute toward ‘negative’ excess deaths.

What explains India as a tier II country

The Government of India pointed out that “given the accuracy of the mortality data collected through an effective and robust statutory system, India doesn’t deserve to be placed in tier II countries”. Two aspects are relevant: (i) What are the current limitations in the civil registration system, and (ii) did the WHO model have access to the full range of Indian data?

According to government sources, death registration was 99.9 percent in 2020; the calculation of estimated deaths is based on the death rate of 6 percent given in the Sample Registration System (SRS) data for 2019.

While the civil registration system has been growing in strength, a recent analysis indicates that mortality measures may not be entirely reliable for states with reporting coverage and/or estimated completeness levels of less than 80 percent. According to government sources, death registration was 99.9 percent in 2020; the calculation of estimated deaths is based on the death rate of 6 percent given in the Sample Registration System (SRS) data for 2019. The SRS was noted to underestimate mortality risks for ages between 30 and 69 years in several states. Significantly, the National Family Health Survey 5 (2019-20) reported death registration at an average of 71 percent (ranging from 36 percent in Bihar to 97.8 percent in Kerala).

Civil registration and vital statistics (CRVS) systems provide ACM data, defined as all of the deaths that occur in a population regardless of the cause. In the WHO model, “full national” countries had data overall 24 months (January 2020 to December 2021); these were classified as tier I countries. Countries categorised by the WHO as tier II, including India, were reported to not have complete data at the time of computation; the Government of India has refuted this though. The report mentions India as a “most complex subnational scenario” in which the number of regions with monthly data varied by month. A variety of sources for the registered number of deaths in the States and Union territories were drawn upon; these included official reports of the states and reports by data journalists who obtained death registration information through their respective Right to Information requests. This classification is not a reflection of the public health system of a country; it reflects the availability of complete data for the limited purpose of this exercise.

Resetting the discourse

The CRS 2020 registered an excess of 4.75 lakh deaths. There was a 2.4 percent all-India reduction in the recording of births; the decline in the recording of births in Andhra Pradesh (one of the best performers in terms of registration of vital events) was 6.5 percent. The decline in the recording of births exemplifies the stress that the registration system was under; it is entirely possible that despite the overall increase in recorded deaths, there may still be an undercount of death registration. The value of mean excess deaths for 2020 in India was computed to be 8.2 lakhs. While for the reasons explained above, the CRS and WHO figures are not directly comparable, these are not very inconsistent either. In contrast to some of the other WHO regions, most of the excess deaths in India are attributed to 2021 and not 2020.

The unfolding discourse around this report calls for consensual outcomes. A shared scientific paradigm, recognising problems with broad interpretational scope and wording for precise issues of great details, are some of the key ingredients to developing consensus incrementally. Addressing the 147th WHO Executive Board session as its Chair, India’s Health Minister committed to building “a heroic collective leadership”. Let that be the guiding spirit.

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Rajib Dasgupta

Rajib Dasgupta

Dr. Rajib Dasguptais a Professor and Chairperson at the Centre of Social Medicine &amp: Community Health Jawaharlal Nehru University.He is also a member of the ...

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