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The Future Evolution of the Mortality Acceleration Due to the COVID-19: The Charlson Comorbidity Index in Stochastic

Maria Carannante1, Valeria D'Amato1, Guido Iaccarino2

  • 1Department of Pharmacy, University of Salerno, Fisciano, Italy.

Frontiers in Cardiovascular Medicine
|August 1, 2022
PubMed

Insights

Many COVID-19 deaths involve individuals with pre-existing conditions, accelerating mortality. This study forecasts future excess deaths by revising the Charlson Comorbidity Index in a stochastic environment, accounting for individual comorbidities.

Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health

Background:

  • Empirical evidence suggests many COVID-19 fatalities occurred in individuals with pre-existing frailties or comorbidities.
  • The concept of mortality acceleration posits that COVID-19 hastens deaths that might have occurred sooner than expected.

Purpose of the Study:

  • To forecast future mortality acceleration attributed to COVID-19.
  • To quantify the contribution of individual comorbidities to this acceleration.
  • To project the future trend of excess deaths linked to COVID-19.

Main Methods:

  • Development of a revised Charlson Comorbidity Index within a stochastic framework.
  • Application of a post-stratification scheme for unbiased index calculation.
  • Analysis of comorbidity impact on mortality acceleration forecasting.

Main Results:

  • The revised Charlson Comorbidity Index provides an unbiased measure of comorbidity burden.
  • The index varies by age and is centered on the reference population.
  • Quantification of each comorbidity's contribution to mortality acceleration is achieved.

Conclusions:

  • The study offers a novel method for forecasting COVID-19-related excess mortality.
  • Understanding comorbidity's role in mortality acceleration is crucial for public health.
  • The revised index can inform future epidemiological and public health strategies.

Keywords:
Charlson Comorbidity Indexmortality projectionsproportional hazards modelrelative frailtystochastic modeling

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