Accommodating individual travel history, global mobility, and unsampled diversity in phylogeography: a SARS-CoV-2 case study

Abstract

Spatiotemporal bias in genome sequence sampling can severely confound phylogeographic inference based on discrete trait ancestral reconstruction. This has impeded our ability to accurately track the emergence and spread of SARS-CoV-2, the virus responsible for the COVID-19 pandemic. Despite the availability of unprecedented numbers of SARS-CoV-2 genomes on a global scale, evolutionary reconstructions are hindered by the slow accumulation of sequence divergence over its relatively short transmission history. When confronted with these issues, incorporating additional contextual data may critically inform phylodynamic reconstructions . Here, we present a new approach to integrate individual travel history data in Bayesian phylogeographic inference and apply it to the early spread of SARS-CoV-2, while also including global air transportation data. We demonstrate that including travel history data for each SARS-CoV-2 genome yields more realistic reconstructions of virus spread, particularly when travelers from undersampled locations are included to mitigate sampling bias. We further explore methods to ameliorate the impact of sampling bias by augmenting the phylogeographic analysis with lineages from undersampled locations in the analyses. Our reconstructions reinforce specific transmission hypotheses suggested by the inclusion of travel history data, but also suggest alternative routes of virus migration that are plausible within the epidemiological context but are not apparent with current sampling efforts. Although further research is needed to fully examine the performance of our travel-aware phylogeographic analyses with unsampled diversity and to further improve them, they represent multiple new avenues for directly addressing the colossal issue of sample bias in phylogeographic inference.

Genomic Epidemiology of the First Wave of SARS-CoV-2 in Italy

“…The genome sequence hCoV-19/Wuhan/WH04/2020|EPI_ISL_406801|2020-01-05 was used as an outgroup, as it falls in a basal position with respect to lineages A and B and it results in a reasonable estimate of the time of emergence (time to the most recent common ancestor, tMRCA). The tMRCA for the global data was between mid-November to late December, which is consistent with other studies and the first reported cases in Wuhan, China [ 2 , 24 , 25 ]. Only clusters with sufficient branch support (SH-aLTR >0.9 or bootstrap >70%) were considered for their tMRCA [ 26 ].…”

Genomic epidemiology of SARS-CoV-2 reveals multiple lineages and early spread of SARS-CoV-2 infections in Lombardy, Italy

“…43 ), using the GTR+I substitution model with an exponential population growth tree prior and strict molecular clock, under a noninformative continuous-time Markov chain (CTMC) reference prior 44 . The information regarding location and recent travel history (less than 1 month before the SARS-CoV-2 diagnosis) of the most informative sequences for virus spread and clustering identified in the first Bayesian tree were incorporated in a second Bayesian tree interference 45 , in order to yield more robust reconstructions of virus spread.…”

Assessing Uncertainty in the Rooting of the SARS-CoV-2 Phylogeny

“…Previous analyses have reached different conclusions about the rooting of the phylogeny. Although analyses that used an outgroup reached one placement ( Shen et al 2020 ; Tang et al 2020 ; Yu et al 2020 ; Zhang et al 2020 ), analyses that used midpoint rooting reached another placement ( Li, Zai, Zhao, et al 2020 ; Li, Zai, Wang, et al 2020 ; Nie et al 2020 ), and yet other analyses using a Bayesian molecular clock have reached a different placement of the root ( Benvenuto et al 2020 ; Giovanetti et al 2020 ; Lemey et al 2020 ; Li, Li, et al 2020 ).…”

“…Furthermore, hypermutation in a few sites, not accounted for in standard models of molecular evolution, might be able to explain the signal in the outgroup rooting toward a root in Clade A. For that reason we consider the rooting in Clade B, as estimated in molecular clock analyses, and implied in standard phylodynamic analyses (e.g., Lemey et al 2020 ), to be the most plausible rooting. However, as a root in Clade B cannot be excluded based on the phylogenetic evidence alone, it might be prudent to avoid strong inferences regarding the early divergence of SARS-CoV-2 based on a fixed rooting in either the A or the B clade, and analyses based on the outgroup rooting should be avoided until outgroups more closely related to SARS-CoV-2 have been discovered.…”