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. 2024 Dec 20;19(12):e0316213.
doi: 10.1371/journal.pone.0316213. eCollection 2024.

Dynamics of SARS-CoV-2 lineages in children and adults in 2021 and 2022

Hiie Soeorg  1   2 , Aare Abroi  3 , Taavi Päll  1 , Liidia Dotsenko  4 , Erik Jaaniso  5 , Katrin Kaarna  6   7 , Andrio Lahesaare  8 , Paul Naaber  1   8 , Heiki Niglas  4 , Ott Eric Oopkaup  9 , Hedi Peterson  5 , Tuuli Reisberg  10 , Olga Sadikova  4 , Steven Smit  10 , Ulvi Gerst Talas  9 , Radko Avi  1 , Irja Lutsar  1 , Kristi Huik  1
Affiliations

Dynamics of SARS-CoV-2 lineages in children and adults in 2021 and 2022

Hiie Soeorg et al. PLoS One. .

Abstract

Purpose: We aimed to describe SARS-CoV-2 lineages and diversity in children and adults in Estonia and similarity to travel-related cases and neighbouring countries.

Methods: SARS-CoV-2 sequences in 2021-2022 from a nationwide study were included. The proportion of predominant lineages in Estonian regions and among travel-related cases was described by multinomial logistic regression. Simpson's indices of diversity were compared using linear regression. Dynamics of Bray-Curtis dissimilarity was described by applying fuzzy clustering to non-metrical dimensional scaling results.

Results: A total of 2,630 sequences from children (<15 years) and 23,031 from adults (≥15 years) were included. The increase in the proportion of Alpha/Delta/Omicron BA.1/BA.2 lineages was delayed in smaller regions (by 3.5-27.5 days). The proportion of Alpha/Delta/Omicron BA.1 increased earlier among travel-related (n = 4,654) than non-travel-related cases (10.5 days). Diversity was lower in non-travel-related than travel-related cases until Delta period by 0.066. Dynamics of lineages and diversity were similar in adults and children. Similarity of lineages was delayed compared to Finland during Alpha/Omicron BA.1/BA.2 periods and different from all neighbouring countries during Delta period.

Conclusion: SARS-CoV-2 lineages in children and adults were similar. Differences between regions and travel-related cases and varying similarity to neighbouring countries suggest the importance of mobility in the spread.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Parameters describing the spread of SARS-CoV-2 in different regions.
Boxplots of parameters derived from the final multinomial regression model by variants and regions: (A) log10-transformed maximum growth rate of lineages, (B) maximum proportion, (C) time of maximum growth rate relative to the location where the maximum growth rate was reached the earliest. From the models of derived parameters, BA.5.2 was omitted as the time when it reached its maximum proportion was estimated to be in the last week of the observation period, possibly leading to incorrect estimates.
Fig 2
Fig 2. Parameters describing the spread of SARS-CoV-2 among travel-related and non-travel-related.
Boxplots of parameters derived from the final multinomial regression model of the proportion of most common lineages among travel-related cases and non-travel-related cases in the two largest regions in Estonia (Harju and Tartu) by variants and origin: (A) log10-transformed maximum growth rate of lineages, (B) maximum proportion, (C) time of maximum growth rate relative to the location where the maximum growth rate was reached the earliest. From the models of derived parameters, B.1.1, B.1.1.317, B.1.1.7, B.1.177.60, B.1.221 and B.1.258 were omitted as the time when it reached its maximum proportion or maximum growth rate was estimated to be in the first week of the observation period, possibly leading to incorrect estimates.
Fig 3
Fig 3. Simpson’s genetic diversity indices.
Simpson’s genetic diversity index over time in (A) Harju, Tartu and Other counties between which no differences were detected, (B)-(D) Harju, Tartu and Other, respectively, vs Ida-Viru county where differences between weeks marked by vertical dashed lines were detected, (E) children and adults, (F) travel-related and non-travel-related cases in Harju, Tartu and Other counties where difference before week marked by vertical dashed lines was detected.
Fig 4
Fig 4. Bray-Curtis dissimilarity indices.
Bray-Curtis dissimilarity index over time between weekly lineage distributions in Estonian adults and Estonian children, travel-related cases, Finland, Latvia and St. Petersburg. Dashed vertical lines delineate the periods of the predominance of Alpha, Delta, Omicron BA.1 or BA.2 and Omicron BA.5 variant.
Fig 5
Fig 5. Fuzzy clustering of non-metric multidimensional scaling results.
Membership degrees of weekly lineage distributions of Estonian adults, children and travel-related cases, and Finland, Latvia and St. Petersburg according to fuzzy clustering applied to non-metric multidimensional scaling results of Bray-Curtis dissimilarity matrix. Colours indicate the same cluster only in case of the same time period, i.e., in the same column.
See this image and copyright information in PMC

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