COVID-19 in US – due to the large volume of daily domestic air travel – interstate transmission is now the most urgent threat


Interstate transmission of the novel coronavirus that causes COVID-19 is now a much greater public health threat in the United States than cases coming into the country via international travel, a new study led by researchers at the Yale School of Public Health finds.

“Domestic spread of the virus has serious policy implications,” said Assistant Professor Nathan Grubaugh, a genomic epidemiologist at the Yale School of Public Health and the study’s senior author.

“We must shift our focus to improving local disease surveillance rather than banning international travel. This is no longer a ‘foreign’ virus.”

The findings underscore a critical need for more widespread diagnostic testing for COVID-19 at the state level as well as more intense tracking of individuals who may have been exposed to SARS-CoV-2, the highly infectious virus that causes COVID-19.

Public health officials rely on these disease surveillance measures to determine exactly how and where the virus is spreading within the United States in order to target their efforts and prevent additional outbreaks.

“If interstate introductions (of the virus) are not curtailed in the U.S. with improved surveillance measures, more robust diagnostic capabilities, and proper clinical care, quelling local transmission between states will be a Sisyphean task,” the scientists wrote in their report.

The researchers based their findings on a genomic analysis of nine virus samples collected from some of Connecticut’s first COVID-19 patients in mid-March.

Using genomic epidemiology, they sequenced the unique genetic code or ‘signature’ for each sample.

They then compared that Connecticut data to the known signatures of 168 sequenced genomes for SARS-CoV-2 from the United States and around the world.

The study found that most of Connecticut’s virus samples were more closely linked to outbreaks in other states than international locations such as Europe and China.

Credit: Yale.

Most importantly, seven of the nine Connecticut samples were clustered with known virus genomes from Washington state. This provides evidence that transcontinental spread of the virus was already happening between the West Coast and East Coast as early as mid-March, despite federal international travel bans that were put in place starting in late January.

The researchers then coupled their genomic analysis with airline travel data from three major airports in the region (Bradley International, Logan International and JFK).

They used mathematical models and epidemiological dynamics to estimate the risks posed by both domestic and international travelers in spreading infection.

The study found that due to the large volume of daily domestic air travel and the rising number of COVID-19 cases in the United States, the dominant risk of virus importation into southern New England switched from international to domestic travel by mid-March.

“The large volumes of daily travel within the U.S. indicate that domestic spread of SARS-CoV-2 has become, and will likely continue to be, the primary source of new infections,” said Joseph Fauver and Mary Petrone, two researchers from Grubaugh’s lab who served as the study’s lead authors. “

We suspect that this transition from international to domestic dominance for risk will happen elsewhere in the country as more states start experiencing higher burdens of COVID-19 disease.”

Connecticut samples of SARS-CoV-2 (light blue) are closely associated with virus samples collected in Washington state (dark purple) indicating that transcontinental spread of the virus was occurring by mid-March. Credit: Grubaugh Lab.

Fauver, a post-doc, and Petrone, a doctoral student, point out that their analysis for infection risk only accounts for air travel.

If train and automobile travel were included—particularly in the highly populated corridor between Washington, D.C., New York City and Boston–it would likely heighten the risk of domestic transmission even more.

Given the findings, the researchers believe a unified effort to detect and prevent new COVID-19 cases is now absolutely essential for the United States to reduce the risk of future domestic outbreaks.

“If spread between states is now common, as our results indicate, the U.S. will struggle to control COVID-19 in absence of a unified surveillance strategy,” the study said.

A pre-print version of the study, which is currently undergoing peer review, can be found on MedRxIV.

The study involved a large collaborative effort featuring multiple groups across Yale including researchers from the Yale School of Medicine, and the departments of molecular biophysics and biochemistry, ecology & evolutionary biology, immunobiology, pediatrics and internal medicine.

Scientists from the Yale School of Nursing and the Yale Institute of Global Health also contributed as well as researchers from labs in Washington state, Maryland, Switzerland, Canada and the United Kingdom.

Funding: This research was funded by the generous support from the Yale Institute for Global Health and the Yale School of Public Health start-up package provided to NDG. CBFV is supported by NWO Rubicon 019.181EN.004. VEP is funded by NIH/NIAID R01 AI112970 and R01 AI137093. NJL is funded by a Medical Research Council fellowship as part of the CLIMB project. The ARTIC resources were funded by a Wellcome Trust Collaborative Award project number 206298/A/17/Z. JQ is funded by a UKRI Future Leaders Fellowship. KMN is funded by NIH R01 GM112766. IIB is funded by a COVID-2019 grant through the Canadian Institutes of Health Research.

A novel coronavirus, known as SARS-CoV-2, was identified as the cause of an outbreak of pneumonia in Wuhan, China, in December 2019 (Gorbalenya et al., 2020; Wu et al., 2020; Zhou et al., 2020).

Travel-associated cases of the disease COVID-19 were reported outside of China as early as January 13, 2020 and the virus has subsequently spread to nearly all nations (World Health Organization, 2020a, 2020b).

The first detection of SARS-CoV-2 in the United States was a travel-associated case from Washington state on January 19, 2020 (Centers for Disease Control and Prevention, 2020a).

The majority of the early COVID-19 cases in the U.S. were either i) associated with travel to a “high-risk” country or ii) close contacts of previously identified cases, per the testing criteria adopted by the Centers for Disease Control and Prevention (CDC) (Centers for Disease Control and Prevention, 2020b).

In response to the risk of more travel-associated cases, the U.S. placed travel restrictions on multiple countries with SARS-CoV-2 transmission, including China on January 31, Iran on February 29, and Europe on March 11 (Taylor, 2020).

However, community transmission of SARS-CoV-2 was detected in the U.S. in late February when a California resident contracted the virus despite meeting neither testing criteria (Moon et al., 2020).

From March 1 to 19, 2020, the number of reported COVID-19 cases in the U.S. rapidly increased from 74 to 13,677, and the virus was detected in all 50 U.S. states (Dong et al., 2020).

It was recently estimated that the true number of COVID-19 cases in the U.S. is likely in the tens of thousands (Perkins et al., 2020), suggesting substantial undetected infections and spread within the country.

We hypothesized that, with the growing number of COVID-19 cases in the U.S. and the large volume of domestic travel, new U.S. outbreaks are now more likely to result from interstate rather than international spread.

Due to its proximity to several high-volume airports, southern Connecticut is a suitable location in which to test this hypothesis.

By sequencing SARS-CoV-2 from local cases and comparing their relatedness to virus genome sequences from other locations, we used ‘genomic epidemiology’ (Grubaugh et al., 2019a) to identify the likely sources of SARS-CoV-2 in Connecticut.

We supplemented our viral genomic analysis with airline travel data from major airports in southern New England to estimate the risk of domestic and international importation therein.

Our data suggest that the risk of domestic importation of SARS-CoV-2 into this region far outweighs that of international introductions regardless of federal travel restrictions, and find evidence for coast-to-coast U.S. SARS-CoV-2 spread.


Phylogenetic clustering of Connecticut SARS-CoV-2 genomes demonstrates interstate spread

To delineate the roles of domestic and international virus spread in the emergence of new U.S. COVID-19 outbreaks, we sequenced SARS-CoV-2 viruses collected from cases identified in Connecticut.

Our phylogenetic analyses showed that the outbreak in Connecticut was caused by multiple virus introductions and that most of these viruses were related to those sequenced from other U.S. states rather than international locations (Figure 1).

We sequenced SARS-CoV-2 genomes from nine of the first COVID-19 cases reported in Connecticut (CT), with sample collection dating from March 6-14, 2020 (Data S1). These individuals are residents of eight different cities in Connecticut. According to the Connecticut State Department of Public Health, none of the cases were associated with international travel.

Using our amplicon sequencing approach, ‘PrimalSeq’ (Grubaugh et al., 2019b; Quick et al., 2017), with the portable Oxford Nanopore Technologies (ONT) MinION platform, we generated the first SARS-CoV-2 genome approximately 14 hours after receiving the sample (CT-Yale-006), demonstrating our ability to perform near real-time clinical sequencing and bioinformatics.

Our complete workflow included RNA extraction, PCR testing, validation of PCR results, library preparation, sequencing, and live base calling and read mapping. We shared the genomes of these viruses publicly as we generated them (GISAID EPI_ISL_416416-416424).

We combined our genomes with other publicly available sequences for a final dataset of 168 SARS-CoV-2 genomes (Figure 1, Data S2). The dataset can be visualized on our ‘community’ Nextstrain page (

We built phylogenetic trees using a maximum likelihood reconstruction approach, and we used shared nucleotide substitutions to assess clade support (Figure 1).

Our first nine SARS-CoV-2 genomes clustered into three distinct phylogenetic clades, indicating multiple independent virus introductions into Connecticut. Two of the genomes, CT-Yale-001 and CT-Yale-006, clustered primarily with viruses from China and Europe, respectively (Figure 1A).

However, neither of the corresponding COVID-19 cases were travel-associated, which indicates that these patients were part of domestic transmission chains that stemmed from recent international virus introductions.

The other seven SARS-CoV-2 genomes clustered with a large, primarily U.S. clade, within which the majority of genomes were sequenced from cases in Washington state (Figure 1B).

Due to a paucity of SARS-CoV-2 genomes from other regions within the U.S., we could not determine the exact domestic origin of these viruses in Connecticut. We also cannot yet determine whether the higher number of substitutions observed in CT-Yale-007 and CT-Yale-008 (Figure 1B) compared to the other Connecticut virus genomes within this clade was the result of multiple introductions or of significant undersampling.

Importantly, however, our data indicate that by early to mid March there had already been interstate spread during the early COVID-19 epidemic in the U.S. ancestor. We included clade-defining nucleotide substitutions to directly show the evidence supporting phylogenetic clustering. (B) We enlarged the U.S. clade consisting primarily of SARS-CoV-2 sequences from Washington state and Connecticut.

The MinION sequencing statistics are enumerated in Data S1, and the SARS-CoV-2 sequences used and author acknowledgements can be found in Data S2.

The genomic data can be visualized and interacted with at:

Figure 1. The COVID-19 outbreak in Connecticut is phylogenetically linked to SARS-CoV-2 from
Washington. ( A ) We constructed a maximum-likelihood tree using 168 global SARS-CoV-2 protein coding
sequences, including 9 sequences from COVID-19 patients identified in Connecticut from March 6-14, 2020. The
total number of nucleotide differences from the root of the tree quantifies evolution since the putative SARS-CoV-2

Travel and epidemiological patterns reveal significant domestic importation risk
Our phylogenetic analysis shows that the COVID-19 outbreak in Connecticut was driven, in part, by domestic virus introductions.

To compare the roles of interstate and international SARS-CoV-2 spread in the U.S., we used airline travel data and the epidemiological dynamics in regions where travel routes originated to evaluate importation risk.

We found that, due to the large volume of daily domestic air passengers, the dominant importation risk into the Connecticut region switched from international to domestic by early to mid March (Figure 2).

We first estimated daily passenger volumes arriving in the region from the five countries (China, Italy, Iran, Spain, and Germany) and out-of-region states (Washington, California, Florida, Illinois, and Louisiana) that have reported the most COVID-19 cases to date (Figure 2A-D).

To this end, we collected passenger volumes arriving in three major airports in southern New England: Bradley International Airport (BDL; Hartford, Connecticut), General Edward Lawrence Logan International Airport (BOS; Boston, Massachusetts), and John F. Kennedy International Airport (JFK; New York, New York; Figure 2B).

As travel data for 2020 are not yet available, we calculated the total passenger volume from each origin and destination pair between January and March, 2019, and estimated the number of daily passengers.

We found that the daily domestic passenger volumes were ~100 times greater than international in Hartford, ~10 times greater in Boston, and ~4 times greater in New York in our dataset (Figure 2B).

By combining daily passenger volumes (Figure 2B) with COVID-19 prevalence at the travel route origin (Figure 2C-D) and accounting for differences in reporting rates, we found that both domestic and international SARS-CoV-2 importation started to increase dramatically at the beginning of March, 2020 (Figure 2E).

Without accounting for the effects of international travel restrictions, our estimated domestic importation risk from the selected five U.S. states surpassed international importation risk by March 10.

Using previous assumptions around travel restrictions (Chinazzi et al., 2020), we also modeled two scenarios where federal travel restrictions reduced passenger volume by 40% and by 90% from the restricted countries (Figure 2E).

Due to the overall low prevalence of COVID-19 in China, we did not find any significant effects of travel restrictions from China that were enacted on February 1st (Data S3).

Also, we did not find significant changes to the importation risk following travel restrictions from Iran on March 1, likely due to the relatively small number of passengers arriving from that country (Data S3).

While we did find a dramatic decrease in international importation risk following the restrictions on travel from Europe (March 13), this decrease occurred after our estimates of domestic travel importation risk had already surpassed that of international importation (Figure 3E).

The dramatic rises in both domestic and international importation risk preceded the state-wide COVID-19 outbreak in Connecticut (Figure 3E), and the recent increase in risk of domestic importation may give rise to new outbreaks in the region.

Figure 2. Domestic outbreaks and travel are a rising source of SARS-CoV-2 importations. ( A ) To compare
the relative risks of SARS-CoV-2 importations from domestic and international sources, we selected five
international (China, Italy, Iran, Spain, and Germany) and out-of-region U.S. states (Washington, California, Florida,
Illinois, and Louisiana) with the highest number of reported COVID-19 cases as of March 19, 2020. ( B ) We selected
three international airports in the region that are commonly used by Connecticut residents: Hartford (BDL), Boston
(BOS), and New York (JFK). We used data from January to March, 2019, to estimate relative differences in daily air
passenger volumes from the selected origins to the airport destinations. These daily estimates were then combined
by either international or domestic travel. ( C-D ) The cumulative number of daily COVID-19 cases were divided by
100,000 population to calculate normalized disease prevalence for each location. ( E ) We calculated importation risk
by modelling the number of daily prevalent COVID-19 cases in each potential importation source and then
estimating the number of infected travelers using the daily air travel volume from each location. Data, criteria, and
analyses used to create this figure can be found in Data S3 .



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