Survival analysis of SARS-CoV-2 variant epidemics: Influencing factors and duration of epidemics

Abstract


Background: The COVID-19 pandemic has been marked by the emergence of numerous variants and mutations of the SARS-CoV-2 virus, each exhibiting distinct epidemiological characteristics. Understanding the factors influencing the duration of these variant-specific epidemics is crucial for effective public health planning and response.


Survival analysis of SARS-CoV-II variants


Objective: This study aims to analyze the impact of various SARS-CoV-2 variants and associated factors on epidemic duration using survival analysis techniques. We investigate the influence of mortality rates, basic reproduction numbers (R0), specific variants types, and epidemic waves on the duration of local outbreaks.

Methods: We utilized a dataset containing information on SARS-CoV-2 variants, their dates of detection, and associated case and mortality data across different countries. We applied survival analysis using a Cox proportional hazards model with time-varying covariates to model the duration of epidemics. We further explored potential interaction effects between variables.

Results: Our analysis showed a strong association of the mortality_rate and the contamination_rate in reducing the duration of the epidemics. The R0 was associated with an increase in the duration of the epidemic, although without a significant impact when we consider the interaction terms. In comparison to the reference group (Delta), the S and mutation type are associated with a more prolonged duration of the epidemics. We also found that a higher number of waves are associated with a reduced duration of épidémie. Finally, our model revealed the importance of the context in the interpretation of the impact of these different variables, by highlighting significant interactions between the type of variants and the continents.

Conclusion: This study demonstrates the complexity of COVID-19 epidemic dynamics and the factors that influence their duration. While a higher mortality rate and the presence of certain types of variants, as well as the rate of contamination, are linked to shorter epidemics, a higher R0 is associated with longer epidemics. Our results suggest that a nuanced approach to disease management, taking into account the different dynamics and the complex interactions between the various factors is important for effective public health decision-making.

Lets see the entire notebook of our analysis.


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