Community immunity: Steering the evolutionary course of SARS-CoV-2

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Community immunity: Steering the evolutionary course of SARS-CoV-2
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Researchers in Germany have developed a comprehensive fitness model that forecasts the evolution of SARS-CoV-2 by integrating genetic, epidemiological, and immunological data. The study emphasizes the role of population immunity in shaping viral mutations and provides valuable insights into the emergence of new variants.

By Vijay Kumar MalesuOct 24 2023Reviewed by Susha Cheriyedath, M.Sc. In a recent study published in the journal Cell, a group of researchers in Germany developed and validated a comprehensive fitness model that forecasts Severe Acute Respiratory Syndrome Coronavirus 2 evolution by integrating genetic, epidemiological, and immunological data, emphasizing the role of population immunity in shaping viral mutations and the emergence of new variants.

Why a Sophisticated Fitness Model is Needed This complex interaction underscores the need for further research using a sophisticated fitness model that integrates both intrinsic and antigenic changes and accounts for the influence of widespread immunity. Such a model is crucial for predicting future evolutionary paths of SARS-CoV-2 and informing global health strategies.

The researchers explored cross-immunity trajectories, establishing a factor for reduced infections from previous immunity that wanes over time, and devised a mathematical model of this temporal immunity, essential for grasping population-wide cross-immunity. The study employed a fitness model, bifurcating intrinsic fitness and antigenic fitness, the latter influenced by cross-immunity.

Related StoriesThe study delved into the antigenic evolution of SARS-CoV-2 by utilizing cross-immunity data among different variants, establishing a cross-immunity matrix through neutralization assays, and observed that the highest immunity was present within the same variants, gradually declining with the emergence of new strains. They mapped immunity trajectories by integrating data on immunization timing, infection rates, and vaccinations.

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