Understanding the shocking increase in Madhya Pradesh deaths in April and May


Representative photo: Health workers carry the body of a person who died of complications from COVID-19 to a crematorium in New Delhi, India, in June 2021. Photo: Reuters / Danish Siddiqui.

In April and May 2021, Madhya Pradesh saw an astonishing increase in mortality. According to death registration data reported by Rukmini S., in those two months, the state recorded 1.7 lakh of “excess” deaths beyond what one would expect from data from previous years. In May alone, the number of recorded deaths was about five times higher than in 2018 and 2019.

Shocking as they are, these numbers may underestimate the true scale of this surge. According to latest data available only around 80% of deaths in Madhya Pradesh are recorded. The total excess mortality during these two months may even have been higher.

Taking the numbers at face value, let’s try to get a sense of what they mean. On a population of approximately 85 million inhabitants, 1.7 lakh of excess deaths is equivalent to approximately 0.2% of excess mortality (2 excess deaths per 1000 people). A panchayat with a population of 5,000 would typically have seen around 10 additional deaths over the two-month period.

Contrary to the figure of 1.7 lakh, there have so far been less than 5,000 deaths from COVID-19 reported in Madhya Pradesh in 2021. The excess mortality is thus more than 35 times the recorded COVID mortality. We don’t know if all of the excess deaths were due to the novel coronavirus. But we can say with certainty that the state is not recording nearly all of its deaths from COVID-19.

Mortality rate

If we assume that much of the excess mortality was, indeed, due to COVID-19, then what does this say about the death rate from the disease?

The COVID-19 Infection Death Rate (IFR) is the fraction of people infected with SARS-CoV-2 who perish. The IFR is generally not constant across regions or over time. We know that the IFR will be influenced by the two variants of SARS-CoV-2 in circulation. But that will depend on the environment in which the virus is circulating, especially the age structure of the population, and the availability of medical care.

We can take Madhya Pradesh’s age structure into account when trying to calculate the expected COVID-19 IFR in the state. For this, let’s use two international studies from 2020, one by Megan O’Driscoll et al (paper 1), and the other by Andrew Levin et al (paper 2).

Using Madhya Pradesh estimated age pyramid For 2021, we expect the state to have a COVID-19 IFR of 0.21% on the first article basis and 0.36% on the second article basis.

These percentages tell us that if everyone in the state were infected with the virus, we would expect 1.8 lakh (paper 1) or 3 lakh (paper 2) deaths. It is astonishing that the additional 1.7 lakh deaths recorded in just two months are close to the first estimate. Granted, not everyone in the state was infected in a short time. Additionally, parts of the state were also hit hard last year, and we expect some disease immunity to protect those previously infected from serious illness.

To explain the huge toll of April and May, we have to assume a combination of factors:

* Very high spread

* More lethal variants pushing up IFR

* Avoidable deaths from COVID-19, again increasing IFR

* Deaths from other causes as a result of overwhelmed health systems

Strong spread, including in rural areas

We know COVID-19 can easily spread in cities. But this wave has, in addition, seen a flood of reports of rural epidemics across the country. The spread in rural areas was probably accelerated by highly transmissible variants and unlimited mobility as the wave rode.

Once the disease enters a village, it looks like it can rage through the population. A study of rural epidemics, based on reports from northern and central India, found many examples of rapid spread in villages. Reports often mentioned that a large portion of the villagers had symptoms such as fever and difficulty breathing.1

Among the 61 villages or clusters examined, the median excess mortality was around 3 per 1,000. A typical village of around 5,000 people would lose about 15 inhabitants within two to three weeks. A significant minority of villages experienced an even higher mortality, reaching more than 5 per 1,000.

These reports have shown that rural mortality can be very high; but they couldn’t tell us how common these village epidemics were. The excess mortality data strongly suggests that the rapid and devastating spread journalists saw in many villages was typical rather than exceptional, at least in Madhya Pradesh.

New variants, poor health infra

There is evidence in the UK that the delta variant of SARS-CoV-2 (B.1.617.2, first reported in India), causes more serious illness than the alpha variant (B.1.1.7, first reported in the UK). Alpha is, in turn, known to cause more serious illness than the previously circulating variants.

There is limited genome sequencing data from Madhya Pradesh on GISAID, the open access repository for genomic data. The limited data suggests that in the last wave, the delta variant came to dominate a mix of variants including both alpha and B.1.617.1 (a delta-related variant whose properties are less well studied). This development towards the delta is broadly similar to what has taken place in many other regions of the country.

The history of the variants is incomplete for lack of good data, but it seems likely that more deadly variants have increased the IFR of COVID-19 in Madhya Pradesh.

Aside from the variants, it is likely that poor health infrastructure and a lack of medical oxygen have pushed IFR even further. In an order dated April 30, the high court of Madhya Pradesh newspaper articles cited detailing up to 74 deaths due to disruptions in the oxygen supply. It is likely that the reported events were only the tip of an iceberg and that such events increased in number in May.

While much of the reporting focuses on cities, the rural reports discussed earlier indicate that lack of oxygen and medical care is the norm in rural areas.

Deaths from other causes

Deaths from many causes are likely to increase when medical services are overwhelmed. For example, infant mortality and maternal mortality are both susceptible to disruptions in health care; and both are already considerably higher than the national average in Madhya Pradesh.

Additional data and detailed investigations may be needed to understand the relative contribution of deaths from COVID-19 and deaths from other causes in the state’s mortality outbreak.

Conclusion

Madhya Pradesh’s huge increase in mortality indicates a rapid spread of the disease and high death rates. It’s shocking – but consistent with data from across the country. In a state where around 70% of the population is rural, it seems likely that the virus has penetrated deep into rural areas.

More deadly variants of the virus have likely led to more serious illness. Poor health infrastructure meant that many people had nowhere to turn when the disease struck. Almost none of the COVID-19 deaths that have occurred have been officially recorded. Deaths from other causes are likely to have increased as the epidemic has exceeded the limited resources available.

Reports from across the country tell us to reject any assumptions about slow rural spread or low mortality. They also tell us to treat official COVID-19 death tolls with extreme skepticism. When it comes to tracking the toll of the pandemic, we once again see the government failing in its responsibilities, as data collectors and journalists step in to fill in the gaps.

Murad Banaji is a mathematician interested in the modeling of diseases.

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