Application of Phylodynamic Tools to Inform the Public Health Response to COVID-19: Qualitative Analysis of Expert Opinions

Background In the wake of the SARS-CoV-2 pandemic, scientists have scrambled to collect and analyze SARS-CoV-2 genomic data to inform public health responses to COVID-19 in real time. Open source phylogenetic and data visualization platforms for monitoring SARS-CoV-2 genomic epidemiology have rapidly gained popularity for their ability to illuminate spatial-temporal transmission patterns worldwide. However, the utility of such tools to inform public health decision-making for COVID-19 in real time remains to be explored. Objective The aim of this study is to convene experts in public health, infectious diseases, virology, and bioinformatics—many of whom were actively engaged in the COVID-19 response—to discuss and report on the application of phylodynamic tools to inform pandemic responses. Methods In total, 4 focus groups (FGs) occurred between June 2020 and June 2021, covering both the pre- and postvariant strain emergence and vaccination eras of the ongoing COVID-19 crisis. Participants included national and international academic and government researchers, clinicians, public health practitioners, and other stakeholders recruited through purposive and convenience sampling by the study team. Open-ended questions were developed to prompt discussion. FGs I and II concentrated on phylodynamics for the public health practitioner, while FGs III and IV discussed the methodological nuances of phylodynamic inference. Two FGs per topic area to increase data saturation. An iterative, thematic qualitative framework was used for data analysis. Results We invited 41 experts to the FGs, and 23 (56%) agreed to participate. Across all the FG sessions, 15 (65%) of the participants were female, 17 (74%) were White, and 5 (22%) were Black. Participants were described as molecular epidemiologists (MEs; n=9, 39%), clinician-researchers (n=3, 13%), infectious disease experts (IDs; n=4, 17%), and public health professionals at the local (PHs; n=4, 17%), state (n=2, 9%), and federal (n=1, 4%) levels. They represented multiple countries in Europe, the United States, and the Caribbean. Nine major themes arose from the discussions: (1) translational/implementation science, (2) precision public health, (3) fundamental unknowns, (4) proper scientific communication, (5) methods of epidemiological investigation, (6) sampling bias, (7) interoperability standards, (8) academic/public health partnerships, and (9) resources. Collectively, participants felt that successful uptake of phylodynamic tools to inform the public health response relies on the strength of academic and public health partnerships. They called for interoperability standards in sequence data sharing, urged careful reporting to prevent misinterpretations, imagined that public health responses could be tailored to specific variants, and cited resource issues that would need to be addressed by policy makers in future outbreaks. Conclusions This study is the first to detail the viewpoints of public health practitioners and molecular epidemiology experts on the use of viral genomic data to inform the response to the COVID-19 pandemic. The data gathered during this study provide important information from experts to help streamline the functionality and use of phylodynamic tools for pandemic responses.


Introduction
SARS-CoV-2, the cause of COVID-19, has rapidly spread worldwide since its emergence in Wuhan, China, in December 2019 [1]. As of January 2022, the virus had contributed to more than 366 million infections and 5.6 million deaths worldwide [2]. The first genomic sequence of SARS-CoV-2 was published in record time in January 2020, formally establishing COVID-19 as a novel disease [3]. In the intervening 2 years, over 7 million SARS-CoV-2 genome sequences have been deposited in the Global Initiative on Sharing All Influenza Data (GISAID) repository [4], which has served as the primary open access sequence archive for sharing SARS-CoV-2 sequence data since the start of the COVID-19 pandemic. The collection of SARS-CoV-2 viral genomes enables genomic surveillance of genetic variation over time and the discovery of new and consequential mutations in key regions of the virus' genome.
Genomic surveillance of emergent pathogens, such as SARS-CoV-2, informs our understanding of their origins [5,6], transmission dynamics [7], spatial spread [8], and the emergence of variants [9], particularly when viral genome data can be coupled to standard surveillance data [10]. Given the widespread transmission of SARS-CoV-2 and the severity of COVID-19, researchers worldwide have worked swiftly to investigate SARS-CoV-2 sequence evolution and spread through molecular epidemiology methods [11]. Bioinformatics and data visualization tools that use phylogenetic trees, such as Nextstrain [12], COVID-19 CoV Genetics (COVID-19 CG) [13], and Ultrafast Sample placement on Existing tRees (UShER) [14], have rapidly gained popularity. Since the beginning of the pandemic, the Nextstrain tool has traced SARS-CoV-2 by adding sequences in real time to a global epidemic tree, aiding with the localization of new infections within existing clusters. For example, heavily subsampled, custom Nextstrain analyses have been used to investigate the possible patient 0 in Italy [15] and undetected transmission at the beginning of the pandemic in the United States [16]. Aside from COVID-19, the platform has also been used to forecast influenza A strains for vaccine predictions [17] and to create situation reports for the Ebola outbreak in the Democratic Republic of the Congo in 2018 [18]. However, these tools are less equipped to forecast the growth of viral clusters and their reliability is heavily affected by sampling bias [19][20][21][22]. Even Bayesian phylogeography, which integrates spatial and epidemiological data and is more computationally expensive than the tree-building algorithms used in online tools, only provides a reconstruction of past dynamics [23].
Although the existing mainstream phylogenetic tools are useful to provide insights into the molecular epidemiology of SARS-CoV-2, their utility in informing the ongoing response to COVID-19 among public health practitioners on the ground needs to be explored. Additionally, consumer-level input regarding what features are desired is unknown. Qualitative research methods are a useful approach to explore the perceptions and opinions of complex topics and engage stakeholder buy-in and are increasingly being performed in public health research [24,25]. Focus groups (FGs) are 1 type of qualitative method in which participants, who are homogeneous with respect to a shared area of expertise or experience, are guided through a structured discussion by a trained moderator [25]. The group dynamics elicited by this strategy can serve as a proxy informant for the community [25].
The objective of this study was to convene experts in public health, infectious diseases, virology, bioinformatics, and molecular epidemiology-many of whom were actively working on the COVID-19 response at the time of their participation-into FGs to discuss and report on the application of phylodynamic tools to inform the ongoing public health response to COVID-19. In total, 4 FGs occurred between June 2020 and June 2021, covering both the pre-and postvariant strain emergence and vaccination eras of the ongoing COVID-19 crisis.

Study Population
Participants included national and international academic and government researchers, clinicians, public health practitioners, and other stakeholders recruited through purposive and convenience sampling by the study team and expanded through snowballing (ie, in which invited participants could suggest others). The study team contacted professionals in the field whose contact information (eg, email address) is publicly available on their respective institutions' websites.

Ethical Considerations
The study was approved by the University of Florida Institutional Review Board (reference number: IRB202000840). The FG participants provided written informed consent prior to participation. No compensation was provided.

Study Instrument
Open-ended questions were developed to prompt discussion (Table 1). Questions were created to guide the discussion of specific topics and to gather diverse insight from a range of experts. The moderator was free to probe with additional questions to seek clarity or depth in participants' responses [25]. FGs I and II concentrated on phylodynamics for the public health practitioner, while FGs III and IV discussed the methodological nuances of phylodynamic inference. We conducted 2 FGs per topic area to increase data saturation (ie, the point in data collection at which no new insights are added to the discussion [24]). Ten days before each FG, the facilitators circulated the study materials (eg, agenda, papers) and prearranged questions.

Study Procedures
The FGs were conducted remotely via University of Florida's Zoom [26]. There was a primary moderator whose role was to pose the questions, facilitate discussion, and ensure each participant had an equal chance to participate. A secondary moderator took notes, audio recorded each session, and monitored the chat window for written responses. Participants were encouraged not to include identifying information during the discussions. Audio recordings were transcribed verbatim by the professional transcription service Rev [27]. Transcripts were screened for accuracy by a member of the research team, and all identifying information was removed before analysis.

Data Analysis
Data analysis occurred iteratively using a thematic qualitative inductive content analysis process [28]. This approach was selected to allow novel themes to emerge from the data independent from any preconceived categories. The knowledge generated was based on the FG participants' unique viewpoints grounded in the qualitative data. Two reviewers from the research team read through the FG transcripts separately to identify provisional themes and then convened to discuss the findings and arrive at definitions for the agreed-upon themes. The researchers then separately coded all FG transcripts according to the identified themes, after which they met to discuss and resolve any discrepancies. Coding was accomplished using NVivo (QSR International) [29].

Methods of epidemiological investigation
Bias in the way the samples were collected, or sequence data were shared, and resulting implications Sampling bias Having consistent rules for storing, publishing, and sharing sequence data between stakeholders and researchers Interoperability standards Building relationships and assigning complementary/noncompeting roles between academic and public health partners Academic/public health partnerships Funding, equipment, and ability and availability of personnel to conduct molecular epidemiology investigations

Translational and Implementation Science
The application of phylodynamic research findings into policy and public health practice, labeled as "translational and implementation science" in the qualitative analysis, emerged as a common theme from the FG discussions. Many of the participants felt that phylogenetic data are important for evaluating public health policies: In contrast, a minority of the participants felt that the relative impact of phylodynamic analyses to inform an ongoing public health response was low due to precedent:

Precision Public Health
Another theme to emerge was the notion of tailoring public health interventions toward specific populations (or "clusters"), which we termed "precision public health." The participants remarked that having the phylogenetic information allows one to evaluate the role that any 1 outbreak might play in the larger spread, which can inform mitigation strategies. Participants imagined a reality where interventions could be tailored to the dominant strains circulating in a community: Other reflections considered the value of using phylogenetics to resolve transmission events and distinguish between probable transmission settings to aid with setting-specific accountability and prevention.
If you have 6 cases, let's say, at a meatpacking plant, and then you have family members in the household also testing positive, is the focus of transmission actually the work setting, or are people becoming infected by their household members who are also going to school or working in frontline industries. I think that's going to be important, as employers try to be accountable or dodge that accountability. [FG2, ME researcher] Participants additionally discussed variant tracking to understand the proportions of certain variants circulating in the community at any given time:

Using phylogenetics to follow the trend of variants of interest and variants of concern to see which proportion of infection at a particular time [is] a particular variant and how variants are competing with each other and taking over. [FG3, ME researcher]
The participants also considered how phylodynamic tools can aid with investigating pockets of outbreaks as the disease transitions from an epidemic to an endemic state: If it was to establish itself as an endemic disease, then phylogenetics will be very important in aiding public health departments to investigate pockets of outbreaks. It can answer whether transmission occurred some time ago or if it was imported from another region. That will be very important to investigate. [FG1, ID researcher]

Fundamental Unknowns
Many of the participants discussed the problem of fundamental unknowns or the lack of knowledge due to the nature of an emerging infectious disease and how this may impact transmission chain analyses and variant tracking: In addition to citing conceptual concerns about the technologies' capabilities, participants also expressed difficulty in convincing decision makers to act now to prevent an outcome that is not yet certain: It's really difficult to get decision makers to properly understand what's coming in the next months. They think, why do they have to make decisions now for something that is only going to become clear after a few months? [FG3, ME researcher] Other participants felt that the collection and analysis of genomic sequence data will be invaluable for answering many fundamental unknown questions. Participants discussed how genomic analyses can provide insight into the immunologically important epitopes of the SARS-CoV-2 spike protein, including the receptor-binding domain, and other critical motifs for neutralization to help preserve the efficacy of currently available vaccines.

Proper Scientific Communication
Another theme to emerge across most of the discussions was related to proper scientific communication. Many of the participants urged the importance of disseminating proper interpretations of SARS-CoV-2 molecular data and phylodynamic analyses: We need to be careful to not make grandiose conclusions about why an outbreak happens or give too much weight to it. It's one of many types of data that can be blown out of proportion or interpreted incorrectly. [FG2, ID researcher] This idea of toning down conclusions and putting findings into perspective to prevent incorrect interpretations was echoed by many participants. One participant further expanded to consider the implications of how easily accessible some phylodynamic tools have become, giving people access to more phylogenetic data than ever before: It's not just the tool that is important; it's also the people using the tool and how they make sense of the tool in a public forum. Journalists see all these nice graphs from Nextstrain, and they make their own conclusions, but they are not epidemiologists. They just want a headline for their newspaper. These are all becoming very democratic tools, and everyone has access to them, but you need to put things in context and warn for misinterpretations of the data.

Methods of Epidemiological Investigation
Another theme that emerged was related to participants' experiences with traditional epidemiological investigations, that is, tracking transmission through case investigations and contact tracing to molecular approaches to investigation, as well as the methodological nuances of phylogenetic/phylodynamic studies: We have a lot of people who don't want to be forthcoming. They feel like they're protecting their friends. They don't want to talk about where they've been, different parties they've been to, because of certain policies and just social desirability bias. So, having a more objective tool for evaluating transmission would be really powerful. There is, I think, a lot of fear of retaliation, more perceived than real, but we do need to collect this information, and this is another way to go about it without having to rely on them to be entirely forthcoming.

Sampling Bias
Sampling bias, or bias in the way samples were collected or sequence data were shared, and the resulting implications of this, was another emergent theme. Most of the participants acknowledged sampling bias as 1 of the major causes of data misinterpretation in phylodynamic analyses: The participants discussed issues related to big data and the need to downsample (ie, removing sequences) to subset or condense their background/reference data sets to run many types of phylodynamic analyses. They imagined having a tool that allows one to tailor the sample selection process would be useful: The participants discussed other ways to address sampling bias in the discussions, including to homogenize the data set before the analysis, to make sure it is adequately representative of the epidemic and through post hoc approaches to assess to what extent sampling bias had an impact on the outcome of the analysis:

In the era of SARS-CoV
Let's say that you have heterogeneous sampling and, before starting the analysis, you subsample your data sets according to local incidence. Then, you want to have a number of sequences per locality that is proportional to the relative importance of the epidemic at that location. So, 1 way to deal with that is to relate local incidence with the number of sequences that you subsample by location. Or try to homogenize your data set prior to the analysis. So, you have to obtain a subsampling that is related to the relative importance of the incidence in true space and time. [FG4, ME researcher]

Interoperability Standards
When considering many of the obstacles for storing, publishing, and sharing sequence data between stakeholders and researchers, the FG participants discussed the desire for having consistent rules and even a centralized system. This theme was coded as "interoperability standards." Participants believed that the lack of uniform and routine collection of SARS-CoV-2 genomic sequences is a missed opportunity. They argued that a centralized system for specimen collection and reporting of sequences could help avoid duplicity in data entry and harmonize phylogenetic data with clinical, epidemiological, and demographic data. They also reasoned that this could improve relations between the different levels of public health: I think there's a desire to build a system at the federal level that the states can access, improving that interconnectivity both between local health departments and states, and states into the federal level. [FG1, PH state] As discussed within the theme of sampling bias, when choosing reference sequences from public data repositories, knowing the reason for sequencing is critical but rarely known. Interoperability standards for sequence data submission could help ameliorate this: Again, this is really going to have to be at the point of GISAID or GenBank or any other place that has a repository, but with set definitions, there could be a metadata field that has a dropdown menu perhaps that allows you to say "outbreak investigation," "vaccine breakthrough," etc. Whenever you are targeting samples for sequencing, aside from just general surveillance, you could indicate the justification for outside groups who may be interested in pulling your [sequence] data for use in their own analyses. [FG3, ME researcher] Some of the participants imagined where this system could be housed: Maybe it's housed at the NIH or somewhere else within [the] DHHS and where the epi data and the genomic data are all housed. And that when a researcher is trying to go in and get a data set, you could have collision prevention. You only want at most 2 sequences from 1 outbreak scenario or 5 sequences within a week from a particular college campus so that the researcher isn't or the public health person isn't actually looking at the very specific metadata that's housed, but can prevent this overrepresenting one group over another, if that's the goal. [FG3, ME researcher] The centralized system could generate custom reports and data extracts based on filtering criteria selected by the user. It could also host genomic assembly information: It's important to tie genomic assembly information to the genomic data as well, in terms of what types of tools were used to assemble the genome, whether it's a minor variant or a consensus level call or all of those things, because those are actually really important parts of the analysis. When that gets lost, it really impacts the usability of the data more generally. [FG2, ME researcher] Although a centralized system could solve many of the issues identified, some of the participants added that building such a system would require a lot of organizational work and cooperation across different groups. Additionally, legislation, regulatory frameworks, or a multitude of contractual agreements would need to be put in place to facilitate data sharing and communication with public health authorities across states and territories.

Academic and Public Health Partnerships
Academic and public health partnerships were another theme to emerge, which we defined as building relationships and assigning complementary/noncompeting roles between academic and public health partners. Many of the participants were actively involved with generating regular reports for the local health departments, tribal nations, universities, and other external partners and emphasized the importance of forming strong relationships with these entities: We can think of infrastructure, not in terms of who's doing what where, but the relationships between academia and the health department. [FG1, ID researcher] When discussing who should be responsible for conducting routine molecular surveillance, many of the participants felt that it depends on who has the skillset. They thought that it is easier to recruit the type of talent that you need to universities rather than to health departments:

I think it's unrealistic to expect the health departments to have and maintain that level of [phylogenetic]
expertise. You're going to have regional versus county versus state issues. And maintaining that capacity is going to be difficult. And then also, this will be a rapidly evolving field, and it'll be a lot easier to recruit the type of talent that you need to universities, rather than to health departments. And then also, you get the infrastructure that health departments desperately need, and that infrastructure is better relationships with the academic centers. [FG1, clinician-researcher] Others cited issues with the adoption of existing phylodynamic tools within the public health sector due to the limited infrastructure for computational power. Overall, the participants felt that having strong public health-academic partnerships is essential to accomplish this type of work. The applied public health sector should be identifying the questions that need answers, while the academics should focus on the methodological nuances of the analyses and the bigger picture: I think in terms of the academic and public health joint participation in these issues, they have to come together to focus on the public health questions of importance. And I say sometimes academics have an important contribution to make to that discussion because sometimes people so involved in their fieldwork don't think about the other things that could be important. [FG1, ID researcher] The consensus of the groups was that contracting the work out to academics may be the best approach to maintaining expertise and staying on the "bleeding edge of the technology" (FG1, PH federal).

Resources
A recurring theme related to funding needs, equipment requirements, and the ability and availability of personnel to conduct molecular epidemiology investigations-collectively termed "resources"-was debated throughout many of the FG discussions. Some participants doubted the need for phylogenetics when performing mitigation testing. Others considered the limitations of the current infrastructure to run these types of analyses at public health departments: I think that in terms of the infrastructure at the health departments, obviously personnel and expertise are needed. Epidemiologists are pretty few and far between right now, and so having persons who understand these data and how they can be used is paramount, because it's no point in having all of these data and these analyses if we don't understand how to use them. Secondly, I would say that it depends on whether or not the expectation for the sampling is to be on the public health system or if it is on the health care system is something else too, and maybe increasing the capacity at the public health labs to do these analyses is also needed. [FG2, PH state] I have to say that because of constraints with manpower, very few of us working on this, we really have been restricted to just looking for lineage assignments and seeing whether we have variants of concern, mutations of concern. All the other types of analyses that we would really love to do

Principal Findings
Amid the global public health crisis presented by COVID-19, researchers and scientists have strived to collect and analyze genomic data to inform public health decision-making in real time. Open source phylogenetic and data visualization platforms for monitoring SARS-CoV-2 genomic epidemiology, such as Nextstrain [12], have rapidly gained popularity for their ability to illuminate spatial-temporal transmission patterns worldwide. However, the utility of such tools to inform public health decision-making for COVID-19 in real time remains to be explored. In this study, we detailed the perspectives of experts in both academic and public health settings regarding the utility of phylodynamic tools for the public health response to COVID-19. Discussions were hosted across the pre-and postvariant and vaccination eras of the crisis. The overall participation rate was 56%, which is comparable to previous FG studies that recruited stakeholders and professionals across health disciplines [30,31]. The diverse group of participants represented a wide variety of expertise on the topic, including experts involved in the COVID-19 response at the time of their participation.
A variety of themes emerged during the FG discussions. Participants were optimistic about the ability of phylodynamic tools to track the spatial spread of the virus and to resolve the transmission patterns. Using these types of data to evaluate policy, such as the impact of border closures on transmission, was an important feature cited by many participants. A prior phylogeographic analysis of the origin and spread of SARS-CoV-2 in Europe revealed that the virus had already spread to several European countries (ie, France, Germany, and Italy) prior to border closures [32], while another analysis conducted using data from Russia revealed that early border closures helped delay virus introductions from China [33].
The translation of phylodynamic analyses into public health action was another theme discussed at length. There were some differences in the responses of public health practitioners by level of public health. County public health practitioners were generally enthusiastic about the use of sequence data to aid in their investigations of local outbreaks. In contrast, state public health officials, while acknowledging the potential utility of phylogenetic studies, were concerned about the resources needed to conduct the analyses and which entity (eg, academic institutions vs public health departments) should be responsible. The participants emphasized the need for strong academic and public health partnerships to enable the highest-level science available at academic centers to conduct analyses requested by stakeholders. Participants also mentioned the key types of data that would ideally be attached to the genomic sequences to permit more in-depth analyses. The majority of participants agreed that phylodynamics will remain critical to answer key fundamental questions about virus transmissibility and immune evasion. They also imagined that public health responses could be tailored to a specific variant and that phylodynamic tools could be used to monitor pockets of outbreaks as the disease transitions from an epidemic to an endemic state. There are a few instances of phylogenetic data being used to inform COVID-19 public health decisions in real time that are documented in the published literature. A study in Wales used phylogeographic methods to demonstrate the impact of travel restrictions on SARS-CoV-2 transmission, subsequently leading to their reinstatement [34]. In the United States, a molecular epidemiology study revealed the introduction of the highly transmissible B.1.1.529 (Omicron) variant into several states [35]. This led to a reduction in the recommended isolation period for infected individuals to blunt the societal impact of the virus [36].
The causes and effects of sampling bias were another theme thoroughly discussed. Nonrepresentative samples have been an ongoing issue for SARS-CoV-2 analyses as they can directly influence phylodynamic inference and lead to inaccurate conclusions about virus dispersion dynamics, as previously reported by our group [37,38]. Recent examples of emergent SARS-CoV-2 variants, such as the identification of the Alpha variant in the United Kingdom and the Omicron variant in South Africa, highlight key issues with sampling bias (and associated surveillance bias) as the first location of detection is often blamed for the origin despite reports of previous cryptic circulation in other countries [39]. These examples also emphasize the importance of proper scientific communication, another key theme to arise during the FG discussions. Proper scientific communication was emphasized by several of the participants who were disappointed by the media's reporting of SARS-CoV-2 variants. We believe that the use of molecular epidemiology for public health decision-making, using a transdisciplinary approach that involves policy maker input, will be an important area for future training.
The desire for interoperability standards was a unique theme to emerge from the FGs. The participants discussed the need for standard operating procedures for sequence storage and sharing to reduce biases with background sequence data sets and improve many of the resource issues identified in the "resources" theme. Challenges with the storage and analysis of the enormous amount of SARS-CoV-2 genome sequence data available were a major topic of discussion among the FG participants, echoing similar calls for collective resolution by other groups [40]. There were some topics discussed only briefly or not brought up at all during the FGs. For instance, the security and privacy of traditional epidemiology data types (eg, clinical, demographic, and social contacts) versus pathogen genomic data was a topic of limited discussion. Additionally, there was no discussion of the burden placed on individuals during traditional contact tracing to construct transmission chains, which can be avoided with genomic epidemiology approaches.
In summary, the data gathered during this study provide important information from leading experts in phylogenetic inference, as well as public health practitioners, to help streamline the functionality and use of phylodynamic tools for pandemic responses. As stated by the participants, successful uptake of these tools will require strong academic and public health partnerships. Among their many recommendations was the development of interoperability standards in sequence data sharing to ensure consistency in reporting and to reduce oversampling of nonrandom persons. They also urged responsible reporting of results to prevent misinterpretation by the media and the public. In addition to these recommendations, the participants highlighted key resource issues, including timeliness and cost, that will need to be addressed by policy makers in future epidemics.

Limitations
This study had some limitations. The sample was relatively small and is not representative of all key experts involved in the COVID-19 response. We had minimal participation of individuals from low-income countries. These limitations may explain the limited discussion of certain issues, such as privacy preservation and the individual burden of contact tracing, that we anticipated. Participants were, however, diverse in their expertise, having served in many different capacities throughout the pandemic. Further, the methods of participant recruitment used are prone to bias, which may limit the generalizability of the study, though these methods of recruitment are common and often necessary to recruit experts for qualitative FGs [41]. Discussion prompts were shared with participants 10 days prior to the FGs, which may have resulted in bias caused by outside consultation with peers; however, this is unlikely as the conversations were driven by group discussion. Although an interrater reliability score was not calculated, coding was conducted by 2 researchers using an iterative and systematic process that involved independently coding prior to comparison, minimizing subjectivity [42]. Codes were discussed until 100% agreement was reached.

Conclusion
To the best of our knowledge, this is the first qualitative study to characterize the perspectives of key experts regarding the utility of phylodynamic tools for the public health response to COVID-19. The data gathered during this study provide important information to guide the development of phylodynamic tools for pandemic responses. This information is critical to both policy makers and developers as they consider how to handle existing and emerging SARS-CoV-2 variants during the ongoing crisis.