Beyond COVID-19 Deaths: Cause-Specific Analysis of Excess Mortality in Russia

This study analyzes Russian mortality data from March 2020 to December 2021 to reveal that excess deaths significantly exceeded official COVID-19 counts, driven primarily by cardiovascular diseases and concentrated among working-age men and populous regions, while highlighting how coding inconsistencies may obscure the full indirect burden of the pandemic.

The Gist

Imagine Russia's population as a massive, aging house. For years, the pipes (the cardiovascular system) have been a bit rusty, and the foundation has had some cracks. Then, a sudden, violent storm hits: the COVID-19 pandemic.

This paper is like a team of structural engineers coming in after the storm to count the damage. They found something shocking: The official damage report said the storm broke 600,000 windows (official COVID deaths), but when they counted every broken pane, cracked wall, and collapsed roof, the real number was over 1 million.

Here is the breakdown of what happened, using simple analogies:

1. The "Missing" 400,000 Deaths

The government's official count only included people who died directly from the virus, and they had very strict rules for counting them (like requiring a specific autopsy test). It was as if they only counted windows that were shattered by a direct hailstone, ignoring the ones that fell because the whole house shook.

The researchers found that for every 10 people who died, only about 6 were officially listed as dying from COVID. The other 4 were listed as dying from other things, mostly heart problems.

2. The "Heart" of the Problem

The biggest surprise wasn't just the virus; it was the heart.

• The Analogy: Imagine the virus didn't just break the windows; it also caused the plumbing to burst.
• The Reality: About 60% of the "extra" deaths (the ones not officially listed as COVID) were due to heart disease and other cardiovascular issues.
• Why? The researchers suspect two things happened:
  1. Mislabeling: Many people who actually died from the virus were labeled as having a "heart attack" because the doctors were overwhelmed or the rules were too strict.
  2. The Ripple Effect: The pandemic scared people away from hospitals. People with chest pain didn't go in, or treatments were delayed. So, the virus didn't kill them directly, but the chaos caused by the virus made their heart conditions fatal.

3. The Two Big Waves

The damage didn't happen all at once. It came in two massive surges:

• Wave 1 (Winter 2020-2021): A cold, hard freeze.
• Wave 2 (Late 2021): An even bigger, hotter wave.
  Interestingly, the second wave hit women harder, especially older women, while the first wave hit working-age men harder. It's like the storm changed its wind direction and intensity over time.

4. The Neighborhood Effect (Regional Differences)

Russia is huge, and the damage wasn't spread evenly.

• The "Hot Zones": The central and southern parts of the country (like the Volga region) took the hardest hit. Some of these areas had "excess death" rates that were through the roof, yet their official COVID numbers were surprisingly low. This suggests that in these specific neighborhoods, the "damage report" was very inaccurate.
• The "Cold Zones": The vast, empty lands of Siberia and the Far East had lower death rates, partly because fewer people lived there to begin with.

5. Why Did This Happen?

The paper points to a few key reasons why the house got so damaged:

• Distrust: Many people didn't trust the government or the science, so they didn't get vaccinated or follow safety rules.
• Short-Lived Lockdowns: The "storm shutters" (lockdowns) were opened too quickly.
• Strict Rules: The way deaths were counted was like using a ruler that was too short; it missed a lot of the real damage.

The Bottom Line

The pandemic in Russia was a disaster that was much bigger than the official numbers suggested. It wasn't just the virus killing people; it was the virus breaking the heart of the healthcare system, causing people to die of heart attacks, and then failing to count those deaths correctly.

The takeaway: If you only look at the official "COVID" number, you are only seeing half the story. The real story is about a system that was overwhelmed, a population that was vulnerable, and a counting method that missed the true scale of the tragedy. To fix the house for the future, they need to stop just counting broken windows and start fixing the plumbing.

Technical Summary

1. Problem Statement

The study addresses the significant discrepancy between officially registered COVID-19 deaths and total excess mortality in Russia during the pandemic (March 2020–December 2021). While Russia is known to have one of the highest excess mortality burdens globally, official COVID-19 death counts (approx. 595,815) capture only about half of the estimated total excess deaths (approx. 1.04 million).

The core problem is the lack of granular, cause-specific understanding of this gap. Existing literature often focuses on aggregate excess mortality without decomposing it by cause, age, sex, or region. The authors hypothesize that the discrepancy stems from:

• Misclassification: Restrictive, autopsy-based certification criteria in Russia may have shifted deaths involving SARS-CoV-2 to underlying causes (e.g., Ischemic Heart Disease).
• Indirect Effects: Pandemic-related disruptions to healthcare systems, leading to untreated chronic conditions.
• Regional Heterogeneity: Variations in reporting practices and healthcare capacity across Russia's vast geography.

2. Methodology

The authors employed a robust statistical framework using official data from Russia's Federal State Statistics Service (Rosstat).

Data Sources:

• National Level: Weekly death records (Jan 2015–Dec 2021) disaggregated by age (15–44, 45–74, 75+), sex, and cause of death (ICD-10). Causes were grouped into nine categories: COVID-19, Ischemic Heart Disease (IHD), other Cardiovascular Diseases (CVD), respiratory, cancer, substance-related, suicides, external causes, and residual.
• Regional Level: Monthly all-cause death data (Jan 2015–Dec 2022) for Russian regions, distinguishing only between COVID-19 and "all other causes."

Statistical Modeling:

• Generalized Additive Models (GAMs): The study utilized a two-part modeling strategy to estimate expected deaths.
  1. Total Deaths: Modeled using Poisson GAMs with a log link to capture long-term trends ($f_{trend}$) and seasonal cycles ($f_{season}$).
  2. Cause/Regional Shares: Modeled using Compositional Data Analysis (CoDa). The vector of death shares was transformed using the centered-log-ratio (clr) transformation. GAMs were fitted to each clr-coordinate to ensure the predicted shares sum to one (add-up constraints).
• Coherence: The final expected deaths for a specific cause were calculated as the product of the expected total deaths and the predicted share: $D_{t}^{(j)} = \lambda_t \times p_t^{(j)}$.
• Validation: The authors benchmarked GAMs against four other common models, finding GAMs yielded the lowest Root Mean Square Error (RMSE) and Mean Absolute Error (MAE).
• Excess Calculation: Excess deaths were defined as Observed minus Expected for the period March 2020–December 2021. The "Residual" was calculated as Total Excess minus Officially Registered COVID-19 deaths.

3. Key Contributions

• Granular Decomposition: This is one of the first studies to systematically decompose Russian excess mortality by specific causes, age groups, and sex at a weekly/national and monthly/regional level.
• Methodological Rigor: The application of compositional GAMs ensures that the sum of cause-specific estimates aligns perfectly with the total mortality estimates, avoiding the statistical inconsistencies common in separate modeling of causes.
• Evidence of Misclassification: The study provides strong quantitative evidence that restrictive certification practices (reliance on autopsies) likely led to the systematic under-assignment of COVID-19 as the underlying cause, particularly shifting deaths to cardiovascular categories.
• Regional Mapping: It identifies distinct spatial patterns of mortality that deviate from pre-pandemic gradients, highlighting specific regions with high "residual" excess (indicating potential under-reporting of COVID-19).

4. Key Results

Overall Mortality Burden:

• Total Excess Deaths: 1,044,914 (95% CI: 1,012,626 – 1,076,741).
• Official COVID-19 Deaths: 595,815.
• Discrepancy: Official COVID-19 deaths accounted for only 57% of total excess mortality.

Cause-Specific Findings:

• Cardiovascular Dominance: Ischemic Heart Disease (IHD) and other CVDs accounted for roughly 60% of the non-COVID excess mortality. The timing of these spikes (late 2020 and late 2021) closely mirrored COVID-19 waves, suggesting misclassification.
• Respiratory Diseases: Showed pronounced winter pulses aligned with COVID waves.
• Cancer: Showed a slight deficit in deaths (negative excess), likely due to delayed diagnoses or coding displacement rather than a true reduction in incidence.
• External Causes & Suicide: No evidence of excess mortality; suicide rates remained stable or slightly declined.
• Substance-Related: Notable increases among men, particularly in working ages.

Demographic Patterns:

• Sex Differences:
  • Women: Excess mortality was concentrated in older ages (75+), with the highest peak in late 2021.
  • Men: Excess mortality was higher in working ages (45–74) and showed a sharper rise in late 2020. Men had a higher proportion of non-COVID excess (44% of total male excess was non-COVID) compared to women.
• Age Groups: The 45–74 age group showed the most significant non-COVID excess, particularly for men, suggesting severe under-reporting of COVID-19 in this demographic.

Regional Analysis:

• Spatial Clustering: High excess mortality was concentrated in the Central European and Volga regions (e.g., Lipetsk, Moscow, Saint Petersburg), rather than following the traditional northeast-southwest gradient.
• Residual Excess: Regions like Lipetsk showed massive total excess rates (1,065/100k) but low official COVID-19 shares (27%), indicating severe under-assignment.
• Population Weight: The top five most populous regions accounted for ~25% of the national excess deaths.

5. Significance and Implications

• Certification Practices: The study highlights how Russia's reliance on autopsy-based confirmation for COVID-19 certification, while scientifically rigorous in routine settings, created distortions during a pandemic. It likely suppressed official counts by reassigning deaths to chronic conditions (IHD/CVD) when autopsies were not feasible or during system strain.
• Public Health Surveillance: The findings argue for the necessity of tracking cause-specific excess mortality alongside official case counts. Divergences between total excess and specific cause trends (especially cardiovascular) serve as early warning signals for misclassification or healthcare system collapse.
• Policy Recommendations:
  • Healthcare Continuity: Maintaining access to cardiovascular care during respiratory epidemics is critical to preventing indirect deaths.
  • Regional Targeting: Regions with high "residual" excess require audits of certification practices and investment in health system capacity.
  • Future Outlook: Russia's mortality trajectory depends on addressing the backlog in cardiovascular care and rebuilding public trust in vaccination and health institutions. Without structural improvements, the pandemic may have permanently elevated the baseline of cardiovascular mortality.

In conclusion, the paper demonstrates that Russia's pandemic mortality was not only severe but compositionally skewed, driven largely by cardiovascular deaths that were likely misclassified or exacerbated by indirect pandemic effects, resulting in a mortality burden significantly larger than official statistics suggest.