## 3 Results  
The dynamics of the lineages that make up at least 0.5 counts for the top strains that make up 90% of all Lithuanian sequences in GISAID data, together with other potentially important lineages, are indicated in Figure 1a. The month-wise dynamics of the lineages that make up at least of 0.5% of all Lithuanian sequences in the GISAID data are depicted in the alluvium plots in Figure 1b. The data on relative month-wise frequency are given in Figure 2. The data on the maximum monthly frequencies per lineages are given in Figure 2a. The data on correspondingly month-wise dynamics are divided in two parts, for the most frequent and less frequent lineages, and are depicted in the Figure 2a,b alluvium plots. As we see in terms of the absolute numbers of COVID-19 spread (Figure 1), Lithuania was dominated by several lineages (most notably A.Y.4.5 and Q.1). However, until the autumn of 2020, there was no clear domination of one Lineage (Figures 1a and 2a), and we were then faced with two clear waves: by the end of 2020, B.1.177.60 started a significant spread, and was then overtaken by B.1.1.7 and its localized version Q.1. Both slowly diminished, then a spike in numbers was caused by a Lithuanian Delta variant, A.Y.4.5. As we can see in Figure 2a, the Delta variant A.Y.4.5 dominated over other lineages by the end of June 2021 and was further replaced by other Delta subtypes (Figure 2c). The data on the pace of spread for the lineages are represented in three aspects. The data on initial expansion rate of the month-wise fraction increase per lineages are given in Figure 3a. The corresponding modelled R0 values based on absolute counts are given in Figure 3c. Several lineages managed to reach a month-wise fraction of over 30%. The data on the time over which such lineages reached a certain month-wise fraction are given in Figure 3b. As we see in Figure 3a, the fastest observed spread was in the case of AY.4.5 and B.1.177.60 lineages, followed by Q.1. and B.1.17. Only one lineage, A.Y.4.5, managed to reach an 80% month-wise fraction (due to the limited study interval, data with Omicron Spread in early 2022 are not included), B.1.1.7 and B.1.177.60 reached 50% month-wise fraction, and Q.1 reached 30%. The data of potential transmission to Lithuania were evaluated in two ways. The results on the transmission cluster-based analysis are given in Figure 11, and the results based on the TreeTime are given in Figure 4. In both cases, the upper part of the figures represents aggregated data per country and the smaller graphs give details per different lineages. Additionally, a schematic view of the data shown in Figure 4a is represented in Figure 4b. As we see in Figure 4, the United Kingdom, Denmark, and Norway are notable for the highest transmission intensities to Lithuania; however, the data indicate that some lineages originated from other countries: B.1.1.243 (Ukraine), B.53 (United Arab Emirates), and Q.1 and B.1.617.2 (Germany). Only the analysis based on transmission clusters enabled direct evaluation on rate of non-Lithuanian origin transmissions compared to local origin transmission (Figure 5). The data indicate that the B.1.1.529, B.1.17, B.1.617.2, and B.1.258 lineages stand out as lineages with the highest fraction of potential foreign origin transmissions (listed in decreasing order). Figure 1: The most prevalent lineages in Lithuania. **(a)** Counts of the most prevalent lineages based on GISAID data by the end of 2021—data on the most frequent lineages that make up 90% of all cases are given (separated by blue box line). “VOC” denotes variants of concern, “VUM” denotes variants of interest/under monitoring, and “PMV” denotes lineages that fell into any of the “special” categories in the past. **(b)** The dynamics of absolute count for the lineages which makes up >0.50% of all cases. Figure 2: Month-wise dominating lineages (by the end of 2021). (**a**) The lineages ordered in decreasing order based on a maximum monthly frequency in the GISAID data. Top 24 most dominating month-wise lineages are shown.