Research reveals how isolation measures influence SARS-CoV-2's evolutionary trajectory

In a recent study published in Nature Communications, researchers used previously reported empirical clinical data analysis and multi-level mathematical modeling to forecast changes in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dynamics during infection and evolution.

Study: Isolation may select for earlier and higher peak viral load but shorter duration in SARS-CoV-2 evolution. Image Credit: Kateryna Kon/Shutterstock.com
Study: Isolation may select for earlier and higher peak viral load but shorter duration in SARS-CoV-2 evolution. Image Credit: Kateryna Kon/Shutterstock.com

Background

The coronavirus disease 2019 (COVID-19) altered human behavior through non-pharmaceutical interventions (NPIs) like isolation and quarantine, contributing to SARS-CoV-2 variants of concern (VOC) emergence.

Changes in population size, immunity, and behavior impact viral evolution and can accelerate virus development. Understanding emerging infectious disease epidemiological and clinical features is critical to developing adaptive therapies such as antivirals, vaccines, and SARS-CoV-2 screening techniques.

About the study

In the present study, researchers investigated whether isolation may be a selection pressure driving SARS-CoV-2 evolution.

The researchers analyzed data on SARS-CoV-2 variations to prepare for future pandemics. They evaluated SARS-CoV-2 dynamics from existing viral load data during SARS-CoV-2 infections by pre-Alpha, Alpha, and Delta VOCs using a mathematical model explaining viral dynamics that considered individual and VOC-specific kinetic differences.

The team designed a multiple-level population dynamics model combining modeling data for SARS-CoV-2 transmission at a population level with an individual-level SARS-CoV-2 population-level infection model. The researchers examined variations in the time-series viral load patterns and SARS-CoV-2 evolution in COVID-19 patients with varied clinical characteristics. Non-linear mixed-effect modeling was performed to estimate parameters considering inter-individual heterogeneity in the viral loads of patients.

The researchers assessed the distributions of viral load peaks, peak duration, and viral shedding periods to assess the infection dynamics of various SARS-CoV-2 variants during evolution. They also used the probabilistic multi-level model and the genetic algorithm (GA), which replicates viral phenotypic evolution, to compute the transmission potential (RTP) of each VOC depending on the period following infection.

The team analyzed the additional impact of isolation, which was only relevant to symptomatic individuals, and the baseline effect of isolation, which applied to all participants regardless of whether they were symptomatic or asymptomatic.

Under NPIs, the team validated SARS-CoV-2 evolution using SARS-CoV-2 Omicron VOCs since Omicron BA.1 emerged during Delta VOC transmission, which was the most prevalent variation globally before BA.1. The researchers analyzed longitudinal viral load information from 49 infected individuals, including the BA.1 subvariant, Delta variant, and Omicron variant. The Delta VOC analysis included 64 patients from the United States (US) and the United Kingdom (UK), whereas the Omicron VOC analysis included 49 patients from the US. The team excluded data from 29 US and UK patients due to inadequate data.

Results

The study investigated SARS-CoV-2 variant evolution from pre-Alpha to Delta VOCs, focusing on peak viral load dynamics and transmission likelihood. The researchers discovered that selection for greater transmissibility altered viral load dynamics, with isolation measures catalyzing the evolutionary shifts. Since SARS-CoV-2 changed to adapt to human behavior (i.e., Omicron variants), a shorter incubation period and a higher proportion of asymptomatic infections were also positively selected.

Peak times did not change significantly between pre-Alpha VOC and the Alpha VOC, although viral load peaks were higher for the Alpha VOC and the Delta VOC than pre-Alpha VOCs. The Delta variation showed shorter peaks and viral shedding durations than pre-Alpha VOCs, indicating that the COVID-19-causing virus seems to develop an acute phenotype, characterized by a longer peak time but a shorter viral shedding duration.

The RTP of Alpha was higher than that of pre-Alpha VOCs over longer periods, whereas that of Delta peaked three days after infection and dropped to almost nil by eight days. The Alpha VOC had higher peaks in viral loads compared to pre-Alpha VOCs, despite shorter viral shedding periods for Alpha.

For incubation periods (T) of 1.0 and 3.0 days, optimal sets of infection rate (β) and virus production rate (p) were discrete, whereas, for T values of six and ten days, there were limited optimal sets. Due to isolation, the incubation period heavily influenced the time-series viral load patterns with ideal parameters.

Considering past immunity from vaccinations and prior SARS-CoV-2 infections, the selection pressure for greater transmissibility altered viral load dynamics, and isolation techniques were likely a significant driver of these evolutionary shifts.

Conclusion

Overall, the study findings showed that human-mediated selection pressure, such as isolation, may impact SARS-CoV-2 variant development. Viral shedding durations were decreased, except for the Omicron variant, and viral load peak increased and progressed. The benefit of higher viral load peaks depends on the clinical characteristics and the community setting. The findings indicated that SARS-CoV-2 variants with shorter incubation benefit from early viral load peaks and that these forces must be balanced to mitigate infectious diseases.

Journal reference:
  • Sunagawa, J., Park, H., Kim, K.S. et al. Isolation may select for earlier and higher peak viral load but shorter duration in SARS-CoV-2 evolution. Nat Commun 14, 7395 (2023). doi: https://doi.org/10.1038/s41467-023-43043-2
Pooja Toshniwal Paharia

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Pooja Toshniwal Paharia

Dr. based clinical-radiological diagnosis and management of oral lesions and conditions and associated maxillofacial disorders.

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