SARS-CoV-2 transmission routes from genetic data: A Danish case study

Abstract

Background
The first cases of COVID-19 caused by the SARS-CoV-2 virus were reported in China in December 2019. The disease has since spread globally. Many countries have instated measures to slow the spread of the virus. Information about the spread of the virus in a country can inform the gradual reopening of a country and help to avoid a second wave of infections. Our study focuses on Denmark, which is opening up when this study is performed (end-May 2020) after a lockdown in mid-March.

Methods
We perform a phylogenetic analysis of 742 publicly available Danish SARS-CoV-2 genome sequences and put them into context using sequences from other countries.

Results
Our findings are consistent with several introductions of the virus to Denmark from independent sources. We identify several chains of mutations that occurred in Denmark. In at least one case we find evidence that the virus spread from Denmark to other countries. A number of the mutations found in Denmark are non-synonymous, and in general there is a considerable variety of strains. The proportions of the most common haplotypes remain stable after lockdown.

Conclusion
Employing phylogenetic methods on Danish genome sequences of SARS-CoV-2, we exemplify how genetic data can be used to trace the introduction of a virus to a country. This provides alternative means for verifying existing assumptions. For example, our analysis supports the hypothesis that the virus was brought to Denmark by skiers returning from Ischgl. On the other hand, we identify transmission routes which suggest that Denmark was part of a network of countries among which the virus was being transmitted. This challenges the common narrative that Denmark only got infected from abroad. Our analysis concerning the ratio of haplotypes does not indicate that the major haplotypes appearing in Denmark have a different degree of virality.

Full text

RESEARCH ARTICLE
SARS-CoV-2 transmission routes from genetic
data: A Danish case study
Andreas BluhmID
☯
, Matthias Christandl
☯
*, Fulvio Gesmundo
☯
, Frederik Ravn Klausen
☯
,
Laura Mančinska
☯
, Vincent Steffan
☯
, Daniel Stilck Franc¸a
☯
, Albert H. Werner
☯
Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark
☯These authors contributed equally to this work.
*christandl@math.ku.dk
Abstract
Background
The first cases of COVID-19 caused by the SARS-CoV-2 virus were reported in China in
December 2019. The disease has since spread globally. Many countries have instated mea-
sures to slow the spread of the virus. Information about the spread of the virus in a country
can inform the gradual reopening of a country and help to avoid a second wave of infections.
Our study focuses on Denmark, which is opening up when this study is performed (end-May
2020) after a lockdown in mid-March.
Methods
We perform a phylogenetic analysis of 742 publicly available Danish SARS-CoV-2 genome
sequences and put them into context using sequences from other countries.
Results
Our findings are consistent with several introductions of the virus to Denmark from indepen-
dent sources. We identify several chains of mutations that occurred in Denmark. In at least
one case we find evidence that the virus spread from Denmark to other countries. A number
of the mutations found in Denmark are non-synonymous, and in general there is a consider-
able variety of strains. The proportions of the most common haplotypes remain stable after
lockdown.
Conclusion
Employing phylogenetic methods on Danish genome sequences of SARS-CoV-2, we exem-
plify how genetic data can be used to trace the introduction of a virus to a country. This pro-
vides alternative means for verifying existing assumptions. For example, our analysis
supports the hypothesis that the virus was brought to Denmark by skiers returning from
Ischgl. On the other hand, we identify transmission routes which suggest that Denmark was
part of a network of countries among which the virus was being transmitted. This challenges
the common narrative that Denmark only got infected from abroad. Our analysis concerning
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OPEN ACCESS
Citation: Bluhm A, Christandl M, Gesmundo F,
Ravn Klausen F, Mančinska L, Steffan V, et al.
(2020) SARS-CoV-2 transmission routes from
genetic data: A Danish case study. PLoS ONE
15(10): e0241405. https://doi.org/10.1371/journal.
pone.0241405
Editor: Peter Gyarmati, University of Illinois College
of Medicine, UNITED STATES
Received: June 26, 2020
Accepted: October 14, 2020
Published: October 29, 2020
Copyright: ©2020 Bluhm et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data
about the sequences used can be found within the
manuscript and its Supporting Information files.
The sequences themselves are available from
https://www.gisaid.org/. The R code used is
available from https://github.com/qmath/phylo_
qmath.
Funding: All authors acknowledge financial support
from VILLUM FONDEN via the QMATH Centre of
Excellence (Grant no. 10059). AHW is supported
by VILLUM FONDEN with a Villum Young

the ratio of haplotypes does not indicate that the major haplotypes appearing in Denmark
have a different degree of virality.
Introduction
According to peer-reviewed studies, the first cases of COVID-19 were reported in the city of
Wuhan (China) at the first of December 2019 and a new virus, named SARS-CoV-2, was later
identified as its origin [1]. At the time of writing, the pandemic is ongoing and has spread to
more than 180 countries [2].
The first European case was reported in France on January 24, 2020 [3]. Italy confirmed its
first two cases only a few days later on January 31 [4]. Austria reported its first cases on Febru-
ary 25 [5]. In March, Europe was the center of the global pandemic with many European coun-
tries introducing lockdown measures and travel restrictions. Early on, the ski area of Ischgl in
Tyrol, Austria, was identified as a transmission hot-spot by some countries, so Iceland already
declared it a risk area on March 5 [6]. Quarantine measures in Ischgl, however, were only
imposed on March 13 [7].
Denmark confirmed its first case on February 27 after a man who returned home on Febru-
ary 24 from skiing holidays in Northern Italy had tested positive [8]. The second case was con-
firmed on February 28 and it was also associated to a traveller returning home from Northern
Italy [9]. The number of cases kept increasing, and there was increased suspicion of commu-
nity transmission after two cases had been confirmed at a local high school on March 8 [10].
During this first phase of the pandemic Denmark had issued travel warnings for certain
high-risk areas. On March 2, Denmark advised against all travel to Northern Italy [11]. On
March 10, Denmark additionally advised against travel to the Austrian state of Tyrol, as many
travellers had tested positive after returning home from ski holidays in Ischgl. [12].
On March 11, the Danish prime minister Mette Frederiksen announced a lockdown, which
happened in several stages and included closures of borders and schools [13]. Overall, the mea-
sures were not as severe as in some other European countries. On April 6, the prime minister
announced that the first phase of reopening would start from April 14 [14]. The country has
opened up further since.
As of May 26, there were 11,428 confirmed infections and 563 deaths in Denmark in con-
nection with the disease [15]. From March 12, only people with serious symptoms and people
in risk groups were tested. Since April 1, the number of tests has been increased [16].
In this work, we study all the publicly available genome sequences of the SARS-CoV-2 virus
from Denmark as of May 26. The amount of sequences available makes Denmark a natural
choice for a case study. Moreover, Denmark can serve as a prototype for a country which was
internationally well-connected at the beginning of the pandemic and subsequently went into a
strict lockdown. An investigation of the transmission routes of the virus in Denmark could
therefore be used to understand the development in other countries as well.
For this investigation, we compare the Danish sequences used for our work to genome
sequences from abroad. See S2 File for a list of sequences and their labs of origin. We use the
mutations in the genomic data to identify transmission routes. These appear in the genetic
data as sequences of consecutive mutations and can be thought of as a coarse-grained version
of transmission chains where one cannot resolve the transmission between individuals,
because some of the sequences might be identical. Our focus is on chains of mutations
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Investigator Grant (Grant No. 25452). See https://
veluxfoundations.dk/en for the webpage of
VILLUM FONDEN. The authors received no specific
funding for this work. The funders had no role in
study design, data collection and analysis, decision
to publish, or preparation of the manuscript.
Competing interests: The authors have declared
that no competing interests exist.

highlighting the introduction of the virus to Denmark, its transmission within Denmark, and
its spread to other countries.
Materials and methods
In this work, we use publicly available sequenced genome of the SARS-CoV-2 virus. In the fol-
lowing, we describe how we obtained and analyzed these sequences. For a flow chart of this
process, see Fig 1.
Acquisition of samples
The sequences were downloaded from the GISAID EpiCoV database [17,18] on May 26, 2020,
including 742 Danish sequences. See the S2 File for a full list of sequences including their ori-
gins. From the available sequences, we selected those which we deemed of high quality and
used them for our analysis. Specifically, we only consider sequences with at least 29,000 nucle-
otides having at most 300 unidentified nucleotides (N’s). This corresponds to the requirement
of having at most 1% unidentified nucleotides, which is also imposed by GISAID for sequences
designated as high coverage. Similar cut-off values are used, for example, in [19]. Moreover,
we only consider sequences that originate from a human host. After these steps, we were left
with 582 Danish sequences, which we focus on in our analysis. As such our analysis is based
on significantly more data as compared to the more global, but less Denmark-specific analysis
by Nextstrain. Moreover, the analysis is carried out in greater detail. Nextstrain lists 132 Dan-
ish sequences for the relevant date range (retrieved on: August 21 2020).
Fig 1. The tree building process as a flow chart.
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Tree inference
Based on the genetic data the phylogenetic trees of this manuscript where inferred from
BEAST [20] in conjunction with the statistical software package R [21]. In particular, in a first
step the sequences were aligned with the help of the R package DECIPHER [22,23]. The
resulting alignments were then further processed with BEAST in order to construct the phylo-
genetic trees. In all cases, the GTR + I + G model was used as the basis for the phylogenetic
analysis. In order to cross-check this procedure, a maximum likelihood tree was built addition-
ally, which in all cases supports the conclusions drawn from the BEAST results. The specific
code we used can be found at https://github.com/qmath/phylo_qmath. We use the R-package
treedater [24] to estimate mutation rates.
The mutations identified by this haplotype analysis were cross-validated via bootstrapping
for the corresponding maximum-likelihood phylogenetic trees, with resulting bootstrap values
consistent with the number of mutations defining the different clades. Moreover, we cross-
checked our results with TreeTime [25], which led to similar tree-topologies. However, we do
not require the additional time information provided by the TreeTime package in order to
reach our conclusions.
Haplotypes and rooting conventions
We choose to root our trees with respect to the reference sequence NC-045512.2 (SARS-CoV-
2 isolate Wuhan-Hu-1), which is also the reference for Nextstrain [26] and for [19,27,28].
This is unlikely to be the original sequence, as argued in [29]. The same work suggests rooting
with respect to sequences found in bats and there is a debate in the literature concerning the
most appropriate rooting strategy [29–31]. However, our haplotypes build upon the ones used
in [27], which use this sequence as a reference. These haplotypes were in turn derived from
(the original clades of) Nextstrain [26]. Furthermore, the sequences we consider were not col-
lected before late February 2020. Therefore, the sequence NC-045512.2 from December 31,
2019 is sufficiently distant to serve as an outgroup to root our tree. In light of that, we believe
that rooting with respect to NC-045512.2 has the advantage of allowing for a more straightfor-
ward comparison of the results of this work with [27] without compromising the quality of the
displayed trees.
In Table 1, we list the mutations corresponding to the names we will use, following [27]. In
addition, we list their names in the more recent Nextstrain convention [32] and the clades
from the pangolin system that they are included in [28]. Finally, we list the corresponding
amino acid changes and in which genes they can be found. See [33] for an overview of the
SARS-CoV-2 genome.
Table 1. Naming of different haplotypes.
[27] mutations new Nextstrain pang. amino acid change
A2 C241T, C3037T, A23403G 19A/C241T/C3037T/A23403G B D614G in S
A2a A2 + C14408T 19A/C241T/C3037T.20A B.1 A2 + P4715L in Orf1ab
A2a1 A2a + GGG28881AAC 19A/C241T/C3037T.20A.20B B.1.1 A2a + R203K + G204R in N
A2a2 A2a + G25563T 19A/C241T/C3037T.20A/G25563T B.1 A2a + Q57H in Orf3a
A2a2a A2a2 + C1059T 19A/C241T/C3037T.20A.20C B.1 A2a2 + T265I in Orf1a
List of relevant haplotypes with their definition in terms of mutations as well as their new Nextstrain label. We note that both the reference string used and all the
haplotypes listed have the four mutations specified as haplotype A in [27]. We therefore do not list those. The second to last column is the label for the currently
identified pangolin lineage clades they are included in. The last column gives the corresponding amino acid changes and the genes they occur in.
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To get an overview of mutations prevalent in Denmark, we identify positions where suffi-
ciently many of the analyzed sequences exhibit a substitution or a deletion as compared to the
reference sequence. For a better overview and readability we choose different thresholds
depending on the context. We analyze the co-occurrence of the new mutations with previously
identified haplotypes from [27] and with each other in the entire worldwide data set.
Results
In this section, we review our results. After a general overview of the mutations over time, we
study three different types of mutations in more detail: First, we consider mutations which
were present in some region of the world and appeared in Denmark at some point. Second, we
look at chains of mutations which only appear in Denmark. Finally, we look at mutations for
which a Danish origin is predominant. The mutations we identify here are used subsequently
in the Discussion section to analyze the spread from, to and within Denmark.
Distribution of mutations over time in Denmark
Let us now investigate the ratio of the haplotypes over time. The most common haplotypes in
Denmark are A2a2a and A2a1. Fig 2 shows in the top panel the relative weight of those haplo-
types over time with a seven-day rolling average. In the lower panel we plot the seven-day roll-
ing average of the number of sequences. We observe a larger fraction of A2a1, which is
associated to Italy, before the lockdown. From the onset of the lockdown, the fractions stay
rather stable in time with A2a2a, which we discuss in detail below, making up around 70%. A
lower number of sequences may be interpreted as a larger error bar on the haplotype percent-
ages, making the haplotype distribution in time consistent with constant proportions.
The mutation rate we infer from the Danish data is consistent with the 6 �10
−4
nucleotides/
genome/year found in [19]. Please see [19, Table 1] for an overview of mutation rates for
SARS-CoV-2 obtained in the literature.
Mutations from other regions appearing in Denmark
In the following, we study haplotypes present in Denmark which are also common in other
countries. The aim is to identify from where they have been introduced to Denmark. We start
with the haplotypes most common in the Danish data and proceed with specific examples of
mutations less prevalent in Denmark. For an overview we refer to S1 Fig in S1 File.
A2a2a: A common mutation in Denmark and Ischgl. Approximately 70% of the avail-
able Danish sequences have haplotype A2a2a. This makes it the most common haplotype in
our Danish data with 405 out of 582 sequences. In our complete data set, we see that 4343 out
of 20239 sequences have this haplotype (see S1 Table in S1 File), with sequences originating
from the US, Denmark, the UK, Australia, France and other countries. This haplotype was
already reported in [27] where the authors point out that travelers from Austria had the haplo-
type A2a2 together with the mutation C1059T which is the definition of A2a2a. The haplotype
A2a2 corresponds to an amino acid change Q57H in Orf3a as compared to A2a and the haplo-
type A2a2a corresponds to an amino acid change T265I in Orf1a as compared to A2a2 (see
also Table 1). Both mutations have already been studied in [34].
In the following we first give evidence that some of the sequences with A2a2a originate
from the skiing area of Ischgl in the region of Tyrol, Austria, by identifying specific chains of
mutations. We will then argue that most, but likely not all of this haplotype comes from that
area.
In order to identify a specific chain of mutations, we will look at mutations that occur in
addition to A2a2a. Consider therefore mutation A6825C which corresponds to the amino acid
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change N2187T in Orf1a and which is seen in nine sequences that have A2a2a worldwide.
These include six Danish ones, while the others are from Austria, Norway and Scotland. The
Norwegian sequence can be traced with metadata to Austria. The Norwegian sequence is
dated to March 9, which makes it likely that this mutation has been present in Austria prior to
that date. It is therefore consistent with the hypothesis that the Danish sequences, the first of
which also is dated to March 9, originate from Austria. Since the Austrian sequence is from
Ischgl, a spread from Ischgl, a tourist skiing destination, seems likely.
Similarly, the mutation G15380T (corresponding to S5039L in Orf1a) appears with haplo-
type A2a2a in 32 sequences worldwide. Among those 32 are 16 of Danish origin. Of the
remaining ones with A2a2a, there are eight Austrian sequences. All of them stem from the
region of Tyrol and in particular six are from Ischgl.
In order to argue that most Danish sequences with A2a2a originate from Austria, we first
observe that the ratio of sequences with A2a2 versus A2a2a is close to 1 in Germany, Denmark,
Norway, Austria, Iceland, Sweden and Switzerland what regards European countries, and
lower in other European countries such as the UK, France and the Netherlands from which
significant travel to Denmark would be expected. Since the number of Danish sequences with
A2a2a is high even when restricting to the time around the onset of the lockdown, there must
Fig 2. Haplotypes over time. Top panel: relative frequencies of major haplotypes in Denmark over time; bottom panel: total number of sequences over
time. Both graphs are based on seven-day rolling averages.
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have been multiple introductions of A2a2a to Denmark, and it therefore seems unlikely that
this could have happened from a country with a much different ratio than that of Denmark.
Tourism from European countries to Alpine ski resorts around February and March would
provide a natural travel route for the virus, in particular to Denmark, Sweden, Norway and
Germany. For Iceland, this assumption is supported by the travel information collected in
[27].
The sequences from Switzerland have no travel histories, but location data shows that the
Swiss sequences with A2a2a are mainly spread across the German-speaking part and that they
are in particular not concentrated at one location. This makes it unlikely that there was a hot-
spot in a Swiss ski resort.
In contrast, the Austrian sequences can be mainly attributed to the skiing region of Ischgl.
We refer to the Austrian data presented in S2 Fig of S1 File, where one sees that the haplotype
A2a2a is mostly present in sequences from the ski village of Ischgl in the region of Tyrol, Aus-
tria, and the adjacent region of Vorarlberg.
Accordingly, it seems very plausible that Ischgl was indeed a hotspot for the transmission of
the haplotype A2a2a to the aforementioned countries.
The Norwegian sequences have travel metadata and give further supporting evidence for
this infection route. Here, three out of twelve sequences with the haplotype A2a2a also have
recent travel history to Austria (the others having unknown travel history). This is shown in
S3 Fig in S1 File. The Icelandic study [27] also associated the haplotype A2a2a with travel to
Austria.
However, due to the abundance of the haplotype A2a2a in the world, it is likely that some
portion of the sequences with the haplotype A2a2a are not part of transmission route through
Ischgl. As an example we discuss A2a2a + G24368T in Subsection S1.4 of S1 File, which we
identify as likely originating from the UK.
A2a1: A common mutation in Denmark and Italy. While the previous haplotype could
be linked to Austria, we now proceed with a haplotype that can be traced back to a different
country. The haplotype A2a1, which we consider now, appears 38 times in Denmark. More-
over, 36 sequences with haplotype A2a1 were found in the early targeted testing group (Janu-
ary 31-March 15) in the Icelandic study [27 Table 2]. Out of these, 29 had a travel history from
Italy and three from Austria. Furthermore, the earliest Danish sequence (dated February 26) is
from when there was only one confirmed case in Denmark. As reported in the news, this case
has travel history to an Italian ski-area. It also has haplotype A2a1.
The triple deletion ATGA1605A with coincident mutation T514C. Both in the Danish
and the worldwide data sets we observe sequences with a triple deletion at sites 1606–1608
(ATGA1605A) which is sometimes coincident with a substitution T514C (identified as A6 in
[27 Table S3]). The triple deletion corresponds to the triple deletion ATGA1604A identified as
haplotype A9 in [27 Table S3]. Note that [27 Table S3] places it at position 1604 rather than
1605, which seems to be a typo. The CoV-GLUE database confirms the deletion at the nucleo-
tides where we find it [35].
Most of the sequences in our data set with the triple deletion ATGA1605A but without the
substitution T514C are from the UK (293 out of 346). Noticeably, there are six sequences from
early February (the remaining dated from earliest March 1). Five of these are from the UK and
one is from France. In contrast, most of the sequences with both the deletion ATGA1605A
and the substitution T514C are from the Netherlands (98 out of 138). In addition, the earliest
of the sequences with both ATGA1605A and T514C are from the Netherlands as well. There-
fore, we conclude it to be likely that the triple deletion originated in the UK and then spread
to the Netherlands, where it picked up the mutation T514C. Interestingly, some of the UK
sequences also exhibit mutation T514C. We deem that they originate from the UK thus
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highlighting the multidirectional spread of the virus. In Denmark, we observe nine sequences
with ATGA1605A, two of which additionally have T514C. These latter two Danish sequences
are likely of Dutch origin. The mutation T514C is not shown in S1 Fig of S1 File, since it
appears only twice in the Danish data. However, the sequences in question are those at the
very bottom, with numbers EPI_ISL_444828|2020-03-11 and EPI_ISL_429295|2020-03-13.
Chains of mutations starting in Denmark
Now, we turn to chains of mutations which occurred inside Denmark. From S1 Fig in S1 File,
one identifies several such chains of mutations. Here we report two of the most pronounced.
Chain of mutations starting at C15842A. The first chain we consider starts at C15842A.
The corresponding phylogenetic tree with an overview of the associated haplotypes for this
mutation can be found in Fig 3. There are 20 sequences with the mutation C15842A and the
haplotype A2a2a worldwide and they are all of Danish origin.
From the 20 (all Danish) sequences with A2a2a and C15842A, there are 17 which also have
the mutation C12781T. Furthermore, of the sequences that have both the mutations C15842A
(T5193N in Orf1a) and C12781T (synonymous), there are eight which in addition have the
non-synonymous mutation G22103C (G181R in the spike protein). Another four sequences
have the mutation A23975G instead and finally, there are two which have C25499T. Some of
the previously mentioned sequences have additional mutations. The longest chain of muta-
tions appearing at least twice has length three (not counting the mutations composing the hap-
lotype A2a2a; see Fig 3).
Chain of mutations starting at C1302T. The Danish sequences with haplotype A2a2a
frequently show the mutation C1302T. It is non-synonymous and corresponds to amino acid
change T346I in Orf1a. We will argue that this mutation originated in Denmark and that it
mutated further in Denmark as well as spread to other countries. See Fig 4 for the phylogenetic
tree corresponding to this mutation.
In order to see that this mutation spread further from Denmark, note that worldwide there
are 115 sequences with the mutation C1302T co-occurrent with the haplotype A2a2a, 103 of
which are Danish. The remaining ones are Latvian (1), Icelandic (5) and Swedish (6). The
travel histories of the five Icelandic sequences show that two have traveled to Denmark (as first
reported in [27]), while the other cases do not contain travel information. Of the six Swedish
sequences, one is from Uppsala dated to March 12 while the five others are from Norrbotten
(in the north of Sweden) dated from March 24 until April 2. The earliest Danish sequence with
C1302T is from March 3. Whereas our analysis does not completely exclude that the virus
spread from Sweden or Latvia to Denmark, we believe that the earlier date of the Danish
sequence, together with the high abundance in Denmark, makes it very likely that it originated
in Denmark and further spread from Denmark. See also Fig 5(a) for an illustration of the inter-
national presence of the mutation.
In order to see that the strain A2a2a + C1302T further mutated in Denmark we inspect the
corresponding clade of the Danish tree in S1 Fig of S1 File (see also Fig 4). Ten of the sequences
have C11074T (a combination which is not found outside of Denmark. The eleventh sequence
in this clade has an N at 11074.). Of these, six have the mutation C29095T. Three of them
moreover have the mutation A9280G, whereas two have the mutation C619T (this is only visi-
ble in Fig 4 due to a threshold of three when displaying mutations in S1 Fig of S1 File). Of the
ones with mutation A9280G, two have a mutation at C7164T. Some of the sequences have
additional single mutations. We have thus identified the Danish chains of mutations in Fig
5(b).
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Discussion
We will start the discussion with the ratio of haplotypes over time before considering the differ-
ent types of transmission routes we have found. We will conclude the section with an outlook.
Haplotypes over time
During the initial period of the introduction of the virus to Denmark from different sources
the percentages of the different major haplotypes change: From a larger proportion of haplo-
type A2a1 associated to Italy to a 70% proportion A2a2a associated to Ischgl. After lockdown,
Fig 3. (a) Phylogenetic tree for sequences containing mutation C15842A. From the representation one can read of the chain
mutations starting at C15842A. The second mutation shown is C15842A, followed by C12781T. After that, it trifurcates into
G22103C, A23975G and C25499T. (b) Chain of mutations starting at C15842A.
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however, we do not observe a significant change in the proportions anymore. Therefore, we
find no evidence for different virality. We find no clear pattern in individual mutations of the
strains appearing in Denmark either. Therefore, we suspect that they are consistent with ran-
dom mutation events.
After the research on this study had been concluded, a possible difference in virality of the
occurrence/non-occurrence of mutation D614G in the spike protein has been discussed in
[36,37]. We point out that nearly all studied Danish sequences have this mutation (see S1
Table in S1 File).
Introduction to Denmark
We now discuss the question of how the virus came to Denmark. Our phylogenetic analysis
shows that around 70% of the Danish sequences have haplotype A2a2a. By comparing the
Fig 4. Phylogenetic tree for sequences containing mutation C1302T. From the representation one can read of the chain mutations starting at C1302T.
The second mutation is C11074T, followed by C29095T. Subsequently, the chain bifurcates into C619T and A9280G followed by C7164T.
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Fig 5. (a) Spread of the strain with haplotype C1302T. The figure shows the likely spreadof the strain with haplotype C1302T from
Denmark to other Northern European countries. Within Denmark, it also mutated further and gave rise to the chain of mutations
displayed in (b). (b) Chain of mutations starting at C1302T.
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distribution of haplotypes across different countries, by utilizing date information, and, for
some international sequences, also location data as well as travel histories, we conclude that
the majority of the Danish sequences with A2a2a originate directly or indirectly from Ischgl.
This is illustrated with examples of specific chains of mutations from Ischgl. Our observation
that a large proportion of Danish sequences originate in Ischgl is not unexpected given the
public knowledge of travel histories [38]. Our analysis, however, can be regarded as an inde-
pendent cross-check of this existing narrative.
The remaining portion of the sequences is consistent with multiple entries from other
countries, among them Italy, the UK and the Netherlands. We have illustrated this with exam-
ple chains of mutations which can be associated to those countries. In the case of Italy, this is
based on the haplotype A2a1, in the case of the UK, it is a specific mutation on top of haplotype
A2a2a and in the case of the Netherlands, it is a mutation in addition to a well-known triple
deletion. These conclusions are consistent with the testing results in mid-March [39].
From this point of view, our genomic analysis cross-validates the public statements and
supports findings in the Iceland study [27] that indicate that Ischgl was a hotspot earlier than
widely recognized.
Transmission routes inside Denmark
After its introduction to Denmark, the virus continued to mutate within the country. We have
listed all mutations that appear at least three times inside Denmark in S2 Table in S1 File and
also plotted them in S1 Fig of S1 File. We note that many more Danish chains of mutations
can be identified from S1 Fig of S1 File.
In the results, we discussed two particularly pronounced chains of mutations based on this
plot and Fig 3. For the two chains described in the results we conclude that they are chains of
mutations that happened inside Denmark. We have chosen these two since these mutation
chains only co-occur with the haplotype A2a2a in Denmark (except of the first mutation
C1302T). This shows clearly how one can track the virus mutating as it spreads inside Den-
mark. The longest chain that we conclude happened inside Denmark is five mutations long
and consists of the mutations [C1302T !C11074T !C29095T !A9280G !C7164T].
These mutations took place in a period from before March 15 to before April 14 based on the
dating of the sequences. The average mutation rate we obtain is consistent within error bars
with the 6 �10
−4
nucleotides/genome/year obtained in [19].
Transmission out of Denmark
Not only did the virus follow the travel routes into Denmark, it also spread from Denmark.
For the mutation C1302T, based on its high prevalence in Denmark compared to the rest of
the world together with the travel histories of the Icelandic cases, we conclude that it appeared
first in Denmark and spread from there to Sweden, Latvia and to Iceland. Some reservations
remain since the Swedish data in GISAID is very limited with only 163 sequences as of May
26. Further, the chain of mutations described shows how the virus has spread extensively
within Denmark and mutated at least four times after that.
Hence we see indications that the virus has mutated several times inside Denmark and
spread from Denmark, as illustrated in Fig 5. We have listed and discussed the most common
mutations. As we show in S1 File, some of the mutations we see seem to have occurred inde-
pendently elsewhere, in particular in the UK, which has a large number of sequences in
GISAID. An example of this is the mutation C7011T.
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SARS-CoV-2 transmission routes: Denmark
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Outlook
The conclusions above are based on a rather large number of high quality Danish sequences
with date information as well as on sequences from other countries some of which have more
metadata. Even though we do not have firm knowledge of the representativity of the Danish
sequences, we can assert that they cover the entire time from the first identified case up to May
9. In order to confirm the analysis of the proportion of haplotypes seen, it would be important
to supplement this with information about the representativity of the analysed data set or
obtain a more representative sample. At the same time, our analysis also shows how to effec-
tively incorporate metadata (date, country of origin or travel history) in such an analysis.
We have used the SARS-CoV-2 genomic data to identify transmission routes, thus
highlighting the potential of such methods for understanding the spread of the virus in a popu-
lation. Although here we present a case study for Denmark, a similar analysis could be carried
out for outbreaks in other countries, regions or even smaller units such as hospitals. If suffi-
cient data is available, such methods can also be used to identify transmission chains between
individuals as done e.g. in [27]. If the genomic data is available in real-time, such an analysis
can inform mitigation measures even during an ongoing outbreak, for instance supplementing
traditional methods such as contact tracing.
Supporting information
S1 File. Discussion of additional Danish mutations and supplementary tables and phyloge-
netic trees.
(PDF)
S2 File. GISAID acknowledgements. List of sequences from GISAID used and their submit-
ting laboratories.
(PDF)
Acknowledgments
We thank Judith Gottwein, Anders Krogh, Jakob Sture Madsen and Carsten Wiuf for valuable
comments. We would like to thank everyone submitting sequenced genome data to GISAID,
in particular Statens Serum Institut, with whom we shared an earlier version of this manu-
script, and Mads Albertsen’s lab. A full list of the contributors can be found in S2 File.
Note
During compilation of this work, we became aware of concurrent work, which was
announced here: TV Avisen, DR. Ny genforskning afsører: Sa¨dan endte Midt-og Vestjylland
med at blive hotspot for corona; 2020 May 28 9pm. Available from: https://www.dr.dk/
nyheder/indland/ny-genforskning-afsloerer-saadan-endte-midt-og-vestjylland-med-blive-
hotspot-corona#! [cited 2020 May 29].
Author Contributions
Conceptualization: Andreas Bluhm, Matthias Christandl, Frederik Ravn Klausen, Laura
Mančinska, Daniel Stilck Franc¸a, Albert H. Werner.
Data curation: Fulvio Gesmundo.
Investigation: Frederik Ravn Klausen, Laura Mančinska.
Methodology: Andreas Bluhm, Daniel Stilck Franc¸a, Albert H. Werner.
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SARS-CoV-2 transmission routes: Denmark
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Software: Fulvio Gesmundo, Vincent Steffan.
Supervision: Matthias Christandl.
Visualization: Vincent Steffan.
Writing – original draft: Andreas Bluhm, Matthias Christandl, Fulvio Gesmundo, Frederik
Ravn Klausen, Laura Mančinska, Vincent Steffan, Daniel Stilck Franc¸a, Albert H. Werner.
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