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Is Excess Mortality a Better Measure of Success or Failure During the Pandemic?

Is Excess Mortality a Better Measure of Success or Failure During the Pandemic?

Medics wearing PPE rest during a COVID-19 check-up at Malad in Mumbai, July 22, 2020. Photo: PTI.

Death is defined as the end of life. It is the termination of all biological functions that sustain life in a living organism. All living organisms die. As Seneca, the Roman philosopher, wrote, “Death is the wish of some, the relief of many, and the end of all.”

Earth’s humans have an average life span of 72 years. To compare, bow-headed whales live for 200 years and deep sea sponges, for over 11,000 years. Some plants and trees like spruces can live for several thousand years. Bacteria may survive half a million years in the permafrost.

The COVID-19 pandemic has compelled people to ponder their frail existence and mortality. It has also baffled them – us – with numerous epidemiological terms associated with death, like the case fatality rate and the infection fatality rate. These terms help us understand the pandemic as an epidemiological phenomenon and help plan healthcare policy and socio-economic recovery. However, such measures are poor indicators of the success or failure of a nation’s response altogether.

The case fatality rate is the number of deaths in those confirmed to have an infection by a positive test. However, the sensitivity (correctly identifying a person with infection) of the tests currently used in India ranges from 30% to 70%. At least a third of infected individuals will hence be missed even if tested. Therefore, any deaths among the people who falsely tested ‘negative’ will be not counted in case fatality estimates.

The infection fatality rate, the number of deaths amongst all humans infected with the virus, will never be known. This is because all infected humans cannot be tested and identified, especially as up to 69% of infected individuals may be asymptomatic.

The recovery rate, which is the corollary of the infection fatality rate, is hence also futile. It similarly depends on all humans, symptomatic or asymptomatic, being tested – an impossible feat.

Now, the hospitalisation rate is the number of people with a medical condition admitted to a hospital every year. For COVID-19, this figure depends on all infected people being correctly identified, all unwell patients being hospitalised (which is difficult in nations where hospital beds are scarce or patchy), and being incorporated in government statistics.

When death does occur, it should be counted. A medically trained healthcare worker should properly ascertain the cause of death and record it in a register. This register needs to be well-maintained, accessible and easy to interrogate with reliable output. Unfortunately in India, only 22% of deaths are certified. In a fair proportion of deaths, the cause of death is not correctly documented.

Further, there is a time lag between the date of death and the date of registration. An additional delay occurs between registration and inclusion in national statistics. In the midst of a pandemic with lockdown measures, delays and gaps at every stage of registration are inevitable. Oother potential problems are reporting bias, under-reporting or over-reporting of information, based on social and political compulsions.

Given these limitations, how does one determine the impact of a pandemic?

One way would be to determine the excess mortality – a metric that has been used to determine the impact of prior pandemics.

WHO defines excess mortality in the context of a crisis, as the mortality above what would be expected based on the non-crisis mortality rate in the population of interest. It can be expressed as a rate (the difference between observed and non-crisis mortality rates) or as a total number of excess deaths. Simply put, it is the number of deaths in a particular year due to both viral and non-viral causes above and beyond the number of deaths expected in a ‘normal’ year.

Approximately 95 lakh Indians die every year in India. Some 11% of deaths are due to injuries; 218,000 die in road traffic accidents. There is typically a low year-to-year variability  as well. Extra deaths beyond expected deaths could thus help estimate the COVID-19 mortality. The factors to consider in calculations include anticipated population growth and lower than normal deaths due to injuries and road traffic accidents in the lockdown periods in different states. Other variables, such as fewer deaths due to lower air pollution, will need to be considered as well.

Pandemics lead to other health and socio-economic consequences. For example, tuberculosis (TB) kills 440,000 Indians a year. WHO has estimated that with even a 25% dip in TB detection rates, 13% more TB patients will die as compared to when the detection rate is ‘normal’. Economic hardships during the pandemic may cause 10,000 child deaths per month globally. Such collateral damage should ideally be mitigated by government policy, and will inevitably be captured by the excess mortality data.

However, estimating excess mortality is not easy. More accurate estimates typically originate in high-income nations with high-quality death registration and statistical agencies. India has poor registration and statistical infrastructure, and Indian mortality statistics typically take two to three years to estimate after a ‘normal’ year. Excess mortality is typically not calculated by government agencies either. It would therefore need to be specifically studied by an independent body or research group. Indians will therefore have to bide their time to learn India’s excess mortality due to the pandemic.

The truth of success or failure of a government will only be evident in totality at the end of the pandemic. And that may be some years away.

Dr Saif Razvi, MD, FRCP is a consultant neurologist in the UK. The views expressed here are the author’s own.

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