The Principles of SARS-CoV-2 Intervariant Competition Are Exemplified in the Pre-Omicron Era of the Colombian Epidemic.

The first 18 months of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in Colombia were characterized by three epidemic waves. During the third wave, from March through August 2021, intervariant competition resulted in Mu replacing Alpha and Gamma. We employed Bayesian phylodynamic inference and epidemiological modeling to characterize the variants in the country during this period of competition. Phylogeographic analysis indicated that Mu did not emerge in Colombia but acquired increased fitness there through local transmission and diversification, contributing to its export to North America and Europe. Despite not having the highest transmissibility, Mu's genetic composition and ability to evade preexisting immunity facilitated its domination of the Colombian epidemic landscape. Our results support previous modeling studies demonstrating that both intrinsic factors (transmissibility and genetic diversity) and extrinsic factors (time of introduction and acquired immunity) influence the outcome of intervariant competition. This analysis will help set practical expectations about the inevitable emergences of new variants and their trajectories. IMPORTANCE Before the appearance of the Omicron variant in late 2021, numerous SARS-CoV-2 variants emerged, were established, and declined, often with different outcomes in different geographic areas. In this study, we considered the trajectory of the Mu variant, which only successfully dominated the epidemic landscape of a single country: Colombia. We demonstrate that Mu competed successfully there due to its early and opportune introduction time in late 2020, combined with its ability to evade immunity granted by prior infection or the first generation of vaccines. Mu likely did not effectively spread outside of Colombia because other immune-evading variants, such as Delta, had arrived in those locales and established themselves first. On the other hand, Mu's early spread within Colombia may have prevented the successful establishment of Delta there. Our analysis highlights the geographic heterogeneity of early SARS-CoV-2 variant spread and helps to reframe the expectations for the competition behaviors of future variants.

Impact and mitigation of sampling bias to determine viral spread: Evaluating discrete phylogeography through CTMC modeling and structured coalescent model approximations.

Bayesian phylogeographic inference is a powerful tool in molecular epidemiological studies, which enables reconstruction of the origin and subsequent geographic spread of pathogens. Such inference is, however, potentially affected by geographic sampling bias. Here, we investigated the impact of sampling bias on the spatiotemporal reconstruction of viral epidemics using Bayesian discrete phylogeographic models and explored different operational strategies to mitigate this impact. We considered the continuous-time Markov chain (CTMC) model and two structured coalescent approximations (Bayesian structured coalescent approximation [BASTA] and marginal approximation of the structured coalescent [MASCOT]). For each approach, we compared the estimated and simulated spatiotemporal histories in biased and unbiased conditions based on the simulated epidemics of rabies virus (RABV) in dogs in Morocco. While the reconstructed spatiotemporal histories were impacted by sampling bias for the three approaches, BASTA and MASCOT reconstructions were also biased when employing unbiased samples. Increasing the number of analyzed genomes led to more robust estimates at low sampling bias for the CTMC model. Alternative sampling strategies that maximize the spatiotemporal coverage greatly improved the inference at intermediate sampling bias for the CTMC model, and to a lesser extent, for BASTA and MASCOT. In contrast, allowing for time-varying population sizes in MASCOT resulted in robust inference. We further applied these approaches to two empirical datasets: a RABV dataset from the Philippines and a SARS-CoV-2 dataset describing its early spread across the world. In conclusion, sampling biases are ubiquitous in phylogeographic analyses but may be accommodated by increasing the sample size, balancing spatial and temporal composition in the samples, and informing structured coalescent models with reliable case count data.

Subregional origins of emerging SARS-CoV-2 variants during the second pandemic wave in Côte d'Ivoire.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with increased transmissibility, virulence and immune escape abilities have heavily altered the COVID-19 pandemic's course. Deciphering local and global transmission patterns of those variants is thus key in building a profound understanding of the virus' spread around the globe. In the present study, we investigate SARS-CoV-2 variant epidemiology in Côte d'Ivoire, Western sub-Saharan Africa. We therefore generated 234 full SARS-CoV-2 genomes stemming from Central and Northern Côte d'Ivoire. Covering the first and second pandemic wave the country had been facing, we identified 20 viral lineages and showed that in Côte d'Ivoire the second pandemic wave in 2021 was driven by the spread of the Alpha (B.1.1.7) and Eta (B.1.525) variant. Our analyses are consistent with a limited number of international introductions of Alpha and Eta into Côte d'Ivoire, and those introduction events mostly stemmed from within the West African subregion. This suggests that subregional travel to Côte d'Ivoire had more impact on local pandemic waves than direct intercontinental travel.

Evaluating Data Sharing of SARS-CoV-2 Genomes for Molecular Epidemiology across the COVID-19 Pandemic.

Following the emergence of COVID-19 in December 2019, caused by the coronavirus SARS-CoV-2, the disease spread dramatically worldwide. The use of genomics to trace the dissemination of the virus and the identification of novel variants was essential in defining measures for containing the disease. We aim to evaluate the global effort to genomically characterize the circulating lineages of SARS-CoV-2, considering the data deposited in GISAID, the major platform for data sharing in a massive worldwide collaborative undertaking. We contextualize data for nearly three years (January 2020-October 2022) for the major contributing countries, percentage of characterized isolates and time for data processing in the context of the global pandemic. Within this collaborative effort, we also evaluated the early detection of seven major SARS-CoV-2 lineages, G, GR, GH, GK, GV, GRY and GRA. While Europe and the USA, following an initial period, showed positive results across time in terms of cases sequenced and time for data deposition, this effort is heterogeneous worldwide. Given the current immunization the major threat is the appearance of variants that evade the acquired immunity. In that scenario, the monitoring of those hypothetical variants will still play an essential role.

Reintroduction of highly pathogenic avian influenza A H7N9 virus in southwestern China.

Highly pathogenic (HP) avian influenza A H7N9 virus has emerged in China since 2016. In recent years, it has been most prevalent in northern China. However, several strains of HP H7N9 reappeared in southwestern China (Yunnan Province) in 2021. As a result, we are wondering if these viruses have re-emerged in situ or been reintroduced. Here, we present phylogenetic evidence that the HP H7N9 viruses isolated in Yunnan emigrated from northern to southwestern China in 2020. The northern subregion of China has become a novel epicenter in HP H7N9 dissemination. Meanwhile, a cleavage motif re-emerged due to the T341I mutation, implying a parallel evolution. This cross-region transmission, which originated in non-adjacent provinces and traveled a great geographic distance in an unknown way, indicates that HP H7N9 dissemination did not halt in 2020, even under the shadow of the COVID-19 pandemic. Additional surveillance studies in poultry are required to determine the HP H7N9 virus's geographic distribution and spread.

Summarizing Global SARS-CoV-2 Geographical Spread by Phylogenetic Multitype Branching Models

Using available phylogeographical data of 3585 SARS–CoV–2 genomes we attempt at providing a global picture of the virus's dynamics in terms of directly interpretable parameters. To this end we fit a hidden state multistate speciation and extinction model to a pre-estimated phylogenetic tree with information on the place of sampling of each strain. We find that even with such coarse–grained data the dominating transition rates exhibit weak similarities with the most popular, continent–level aggregated, airline passenger flight routes. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Investigation of cross-regional spread and evolution of equine influenza H3N8 at US and global scales using Bayesian phylogeography based on balanced subsampling.

Equine influenza virus (EIV) is a highly contagious pathogen of equids, and a well-known burden in global equine health. EIV H3N8 variants seasonally emerged and resulted in EIV outbreaks in the United States and worldwide. The present study evaluated the pattern of cross-regional EIV H3N8 spread and evolutionary characteristics at US and global scales using Bayesian phylogeography with balanced subsampling based on regional horse population size. A total of 297 haemagglutinin (HA) sequences of global EIV H3N8 were collected from 1963 to 2019 and subsampled to global subset (n = 67), raw US sequences (n = 100) and US subset (n = 44) datasets. Discrete trait phylogeography analysis was used to estimate the transmission history of EIV using four global and US genome datasets. The North American lineage was the major source of globally dominant EIV variants and spread to other global regions. The US EIV strains generally spread from the southern and midwestern regions to other regions. The EIV H3N8 accumulated approximately three nucleotide substitutions per year in the HA gene under heterogeneous local positive selection. Our findings will guide better decision making of target intervention strategies of EIV H3N8 infection and provide the better scheme of genomic surveillance in the United States and global equine health.

Phylogeography and genomic analysis of SARS-CoV-2 delta variant in Morocco.

INTRODUCTION: Since the COVID-19 pandemic began in December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continuously evolved with many variants of concern emerging across the world. METHODOLOGY: In order to monitor the evolution of these variants in Morocco, we analyzed a total of 2130 genomes of the delta variant circulating around the world. We also included 164 Moroccan delta variant sequences in our analysis. RESULTS: Our findings suggest at least four introductions from multiple international sources and a rise of a dominant delta sub-lineage AY.33 in Morocco. Moreover, we report three mutations in the N-terminal domain of the S protein specific to the Moroccan AY.33 isolates, T29A, T250I and T299I. The effect of these mutations on the secondary structure and the dynamic behavior of the S protein N-terminal domain was further determined. CONCLUSIONS: We conclude that these mutations might have functional consequences on the S protein of SARS-CoV-2.

Phylodynamic analysis of SARS-CoV-2 spread in Rio de Janeiro, Brazil, highlights how metropolitan areas act as dispersal hubs for new variants.

During the first semester of 2021, all of Brazil has suffered an intense wave of COVID-19 associated with the Gamma variant. In July, the first cases of Delta variant were detected in the state of Rio de Janeiro. In this work, we have employed phylodynamic methods to analyse more than 1 600 genomic sequences of Delta variant collected until September in Rio de Janeiro to reconstruct how this variant has surpassed Gamma and dispersed throughout the state. After the introduction of Delta, it has initially spread mostly in the homonymous city of Rio de Janeiro, the most populous of the state. In a second stage, dispersal occurred to mid- and long-range cities, which acted as new close-range hubs for spread. We observed that the substitution of Gamma by Delta was possibly caused by its higher viral load, a proxy for transmissibility. This variant turnover prompted a new surge in cases, but with lower lethality than was observed during the peak caused by Gamma. We reason that high vaccination rates in the state of Rio de Janeiro were possibly what prevented a higher number of deaths.

Historical Evolutionary Dynamics and Phylogeography Analysis of Transmissible Gastroenteritis Virus and Porcine Deltacoronavirus: Findings from 59 Suspected Swine Viral Samples from China.

Since the beginning of the 21st century, humans have experienced three coronavirus pandemics, all of which were transmitted to humans via animals. Recent studies have found that porcine deltacoronavirus (PDCoV) can infect humans, so swine enteric coronavirus (SeCoV) may cause harm through cross-species transmission. Transmissible gastroenteritis virus (TGEV) and PDCoV have caused tremendous damage and loss to the pig industry around the world. Therefore, we analyzed the genome sequence data of these two SeCoVs by evolutionary dynamics and phylogeography, revealing the genetic diversity and spatiotemporal distribution characteristics. Maximum likelihood and Bayesian inference analysis showed that TGEV could be divided into two different genotypes, and PDCoV could be divided into four main lineages. Based on the analysis results inferred by phylogeography, we inferred that TGEV might originate from America, PDCoV might originate from Asia, and different migration events had different migration rates. In addition, we also identified positive selection sites of spike protein in TGEV and PDCoV, indicating that the above sites play an essential role in promoting membrane fusion to achieve adaptive evolution. In a word, TGEV and PDCoV are the past and future of SeCoV, and the relatively smooth transmission rate of TGEV and the increasing transmission events of PDCoV are their respective transmission characteristics. Our results provide new insights into the evolutionary characteristics and transmission diversity of these SeCoVs, highlighting the potential for cross-species transmission of SeCoV and the importance of enhanced surveillance and biosecurity measures for SeCoV in the context of the COVID-19 epidemic.

Tracking the turnover of SARS-CoV-2 VOCs Gamma to Delta in a Brazilian state (Minas Gerais) with a high-vaccination status.

The emergence and global dissemination of Severe Acute Respiratory Syndrome virus 2 (SARS-CoV-2) variants of concern (VOCs) have been described as the main factor driving the Coronavirus Disease 2019 pandemic. In Brazil, the Gamma variant dominated the epidemiological scenario during the first period of 2021. Many Brazilian regions detected the Delta variant after its first description and documented its spread. To monitor the introduction and spread of VOC Delta, we performed Polymerase Chain Reaction (PCR) genotyping and genome sequencing in ten regional sentinel units from June to October 2021 in the State of Minas Gerais (MG). We documented the introduction and spread of Delta, comprising 70 per cent of the cases 8 weeks later. Comparing the viral loads of the Gamma and Delta dominance periods, we provide additional evidence that the latter is more transmissible. The spread and dominance of Delta did not culminate in the increase in cases and deaths, suggesting that the vaccination may have restrained the epidemic growth. Analysis of 224 novel Delta genomes revealed that Rio de Janeiro state was the primary source for disseminating this variant in the state of MG. We present the establishment of Delta, providing evidence of its enhanced transmissibility and showing that this variant shift did not aggravate the epidemiological scenario in a high immunity setting.

Identifying SARS-CoV-2 regional introductions and transmission clusters in real time.

The unprecedented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) global sequencing effort has suffered from an analytical bottleneck. Many existing methods for phylogenetic analysis are designed for sparse, static datasets and are too computationally expensive to apply to densely sampled, rapidly expanding datasets when results are needed immediately to inform public health action. For example, public health is often concerned with identifying clusters of closely related samples, but the sheer scale of the data prevents manual inspection and the current computational models are often too expensive in time and resources. Even when results are available, intuitive data exploration tools are of critical importance to effective public health interpretation and action. To help address this need, we present a phylogenetic heuristic that quickly and efficiently identifies newly introduced strains in a region, resulting in clusters of infected individuals, and their putative geographic origins. We show that this approach performs well on simulated data and yields results largely congruent with more sophisticated Bayesian phylogeographic modeling approaches. We also introduce Cluster-Tracker (https://clustertracker.gi.ucsc.edu/), a novel interactive web-based tool to facilitate effective and intuitive SARS-CoV-2 geographic data exploration and visualization across the USA. Cluster-Tracker is updated daily and automatically identifies and highlights groups of closely related SARS-CoV-2 infections resulting from the transmission of the virus between two geographic areas by travelers, streamlining public health tracking of local viral diversity and emerging infection clusters. The site is open-source and designed to be easily configured to analyze any chosen region, making it a useful resource globally. The combination of these open-source tools will empower detailed investigations of the geographic origins and spread of SARS-CoV-2 and other densely sampled pathogens.

Genomic epidemiology of seasonal influenza circulation in China during prolonged border closure from 2020 to 2021.

China experienced a resurgence of seasonal influenza activity throughout 2021 despite intermittent control measures and prolonged international border closure. We show genomic evidence for multiple A(H3N2), A(H1N1), and B/Victoria transmission lineages circulating over 3 years, with the 2021 resurgence mainly driven by two B/Victoria clades. Phylodynamic analysis revealed unsampled ancestry prior to widespread outbreaks in December 2020, showing that influenza lineages can circulate cryptically under non-pharmaceutical interventions enacted against COVID-19. Novel haemagglutinin gene mutations and altered age profiles of infected individuals were observed, and Jiangxi province was identified as a major source for nationwide outbreaks. Following major holiday periods, fluctuations in the effective reproduction number were observed, underscoring the importance of influenza vaccination prior to holiday periods or travel. Extensive heterogeneity in seasonal influenza circulation patterns in China determined by historical strain circulation indicates that a better understanding of demographic patterns is needed for improving effective controls.

New Phylogenetic Models Incorporating Interval-Specific Dispersal Dynamics Improve Inference of Disease Spread.

Phylodynamic methods reveal the spatial and temporal dynamics of viral geographic spread, and have featured prominently in studies of the COVID-19 pandemic. Virtually all such studies are based on phylodynamic models that assume-despite direct and compelling evidence to the contrary-that rates of viral geographic dispersal are constant through time. Here, we: (1) extend phylodynamic models to allow both the average and relative rates of viral dispersal to vary independently between pre-specified time intervals; (2) implement methods to infer the number and timing of viral dispersal events between areas; and (3) develop statistics to assess the absolute fit of discrete-geographic phylodynamic models to empirical datasets. We first validate our new methods using simulations, and then apply them to a SARS-CoV-2 dataset from the early phase of the COVID-19 pandemic. We show that: (1) under simulation, failure to accommodate interval-specific variation in the study data will severely bias parameter estimates; (2) in practice, our interval-specific discrete-geographic phylodynamic models can significantly improve the relative and absolute fit to empirical data; and (3) the increased realism of our interval-specific models provides qualitatively different inferences regarding key aspects of the COVID-19 pandemic-revealing significant temporal variation in global viral dispersal rates, viral dispersal routes, and the number of viral dispersal events between areas-and alters interpretations regarding the efficacy of intervention measures to mitigate the pandemic.

Comparative Dynamics of Delta and Omicron SARS-CoV-2 Variants across and between California and Mexico.

Evolutionary analysis using viral sequence data can elucidate the epidemiology of transmission. Using publicly available SARS-CoV-2 sequence and epidemiological data, we developed discrete phylogeographic models to interrogate the emergence and dispersal of the Delta and Omicron variants in 2021 between and across California and Mexico. External introductions of Delta and Omicron in the region peaked in early July (2021-07-10 [95% CI: 2021-04-20, 2021-11-01]) and mid-December (2021-12-15 [95% CI: 2021-11-14, 2022-01-09]), respectively, 3 months and 2 weeks after first detection. These repeated introductions coincided with domestic migration events with no evidence of a unique transmission hub. The spread of Omicron was most consistent with gravity centric patterns within Mexico. While cross-border events accounted for only 5.1% [95% CI: 4.3-6] of all Delta migration events, they accounted for 20.6% [95% CI: 12.4-29] of Omicron movements, paralleling the increase in international travel observed in late 2021. Our investigations of the Delta and Omicron epidemics in the California/Mexico region illustrate the complex interplay and the multiplicity of viral and structural factors that need to be considered to limit viral spread, even as vaccination is reducing disease burden. Understanding viral transmission patterns may help intra-governmental responses to viral epidemics.

Comparative phylodynamics reveals the evolutionary history of SARS-CoV-2 emerging variants in the Arabian Peninsula.

Emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to be responsible for an unprecedented worldwide public health and economic catastrophe. Accurate understanding and comparison of global and regional evolutionary epidemiology of novel SARS-CoV-2 variants are critical to guide current and future interventions. Here, we utilized a Bayesian phylodynamic pipeline to trace and compare the evolutionary dynamics, spatiotemporal origins, and spread of five variants (Alpha, Beta, Delta, Kappa, and Eta) across the Arabian Peninsula. We found variant-specific signatures of evolution and spread that are likely linked to air travel and disease control interventions in the region. Alpha, Beta, and Delta variants went through sequential periods of growth and decline, whereas we inferred inconclusive population growth patterns for the Kappa and Eta variants due to their sporadic introductions in the region. Non-pharmaceutical interventions imposed between mid-2020 and early 2021 likely played a role in reducing the epidemic progression of the Beta and the Alpha variants. In comparison, the combination of the non-pharmaceutical interventions and the rapid rollout of vaccination might have shaped Delta variant dynamics. We found that the Alpha and Beta variants were frequently introduced into the Arab peninsula between mid-2020 and early 2021 from Europe and Africa, respectively, whereas the Delta variant was frequently introduced between early 2021 and mid-2021 from East Asia. For these three variants, we also revealed significant and intense dispersal routes between the Arab region and Africa, Europe, Asia, and Oceania. In contrast, the restricted spread and stable effective population size of the Kappa and the Eta variants suggest that they no longer need to be targeted in genomic surveillance activities in the region. In contrast, the evolutionary characteristics of the Alpha, Beta, and Delta variants confirm the dominance of these variants in the recent outbreaks. Our study highlights the urgent need to establish regional molecular surveillance programs to ensure effective decision making related to the allocation of intervention activities targeted toward the most relevant variants.

Reconstruction of the Evolutionary Origin, Phylodynamics, and Phylogeography of the Porcine Circovirus Type 3.

Porcine circovirus type 3 (PCV3) is a newly identified virus associated with porcine dermatitis and nephropathy syndrome (PDNS) and multisystemic inflammatory responses in pigs. Recent studies suggests that PCV3 originated from bat circoviruses; however, the origin time, mode of spread, and geographic distribution of PCV3 remain unclear. In this study, the evolutionary origin, phylodynamics, and phylogeography of PCV3 were reconstructed based on the available complete genome sequences. PCV3 showed a closer relationship with bird circovirus than with bat circovirus, but their common ancestor was bat circovirus, indicating that birds may be intermediate hosts for the spread of circoviruses in pigs. Using the BEAST and phylogenetic analyses, three different clades of PCV3 (PCV3a, PCV3b, and PCV3c) were identified, with PCV3a being the most prevalent PCV3 clade. Further studies indicated that the earliest origin of PCV3 can be traced back to 1907.53-1923.44, with a substitution rate of 3.104 × 10-4 to 6.8524 × 10-4 substitution/site/year. A phylogeographic analysis highlighted Malaysia as the earliest location of the original PCV3, which migrated to Asia, America, and Europe. Overall, this study provides novel insights into the evolutionary origin, spread mode, and geographic distribution of PCV3, which will facilitate the prevention and control of PCV3 epidemics in the future.

SARS-CoV-2 Lineage A.27: New Data from African Countries and Dynamics in the Context of the COVID-19 Pandemic.

SARS-CoV-2 is constantly evolving with lineages emerging and others eclipsing. Some lineages have an important epidemiological impact and are known as variants of interest (VOIs), variants under monitoring (VUMs) or variants of concern (VOCs). Lineage A.27 was first defined as a VUM since it holds mutations of concern. Here, we report additional lineage A.27 data and sequences from five African countries and describe the molecular characteristics, and the genetic history of this lineage worldwide. Based on the new sequences investigated, the most recent ancestor (tMRCA) of lineage A.27 was estimated to be from April 2020 from Niger. It then spread to Europe and other parts of the world with a peak observed between February and April 2021. The detection rate of A.27 then decreased with only a few cases reported during summer 2021. The phylogenetic analysis revealed many sub-lineages. Among them, one was defined by the substitution Q677H in the spike (S) gene, one was defined by the substitution D358N in the nucleoprotein (N) gene and one was defined by the substitution A2143V in the ORF1b gene. This work highlights the importance of molecular characterization and the timely submission of sequences to correctly describe the circulation of particular strains in order to be proactive in monitoring the pandemic.

Phylodynamic Dispersal of SARS-CoV-2 Lineages Circulating across Polish-German Border Provinces.

INTRODUCTION: The emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has evolved into a worldwide outbreak, with significant molecular evolution over time. Large-scale phylodynamic studies allow to map the virus spread and inform preventive strategies. AIM: This study investigates the extent of binational dispersal and dynamics of SARS-CoV-2 lineages between seven border provinces of the adjacent countries of Poland and Germany to reconstruct SARS-CoV-2 transmission networks. METHODS: Following three pandemic waves from March 2020 to the end of May 2021, we analysed a dataset of 19,994 sequences divided into B.1.1.7|Alpha and non-Alpha lineage groups. We performed phylogeographic analyses using the discrete diffusion models to identify the pathways of virus spread. RESULTS: Based on population dynamics inferences, in total, 673 lineage introductions (95% HPD interval 641-712) for non-Alpha and 618 (95% HPD interval 599-639) for B.1.1.7|Alpha were identified in the area. For non-Alpha lineages, 5.05% binational, 86.63% exclusively German, and 8.32% Polish clusters were found, with a higher frequency of international clustering observed for B.1.1.7|Alpha (13.11% for binational, 68.44% German and 18.45% Polish, p < 0.001). We identified key transmission hubs for the analysed lineages, namely Saxony, West Pomerania and Lower Silesia. CONCLUSIONS: Clustering patterns between Poland and Germany reflect the viral variant transmission dynamics at the international level in the borderline area. Tracing the spread of the virus between two adjacent large European countries may provide a basis for future intervention policies in cross-border cooperation efforts against the spread of the pandemics.

The early SARS-CoV-2 epidemic in Senegal was driven by the local emergence of B.1.416 and the introduction of B.1.1.420 from Europe.

Molecular surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is growing in west Africa, especially in the Republic of Senegal. Here, we present a molecular epidemiology study of the early waves of SARS-CoV-2 infections in this country based on Bayesian phylogeographic approaches. Whereas the first wave in mid-2020 was characterized by a significant diversification of lineages and predominance of B.1.416, the second wave in late 2020 was composed primarily of B.1.1.420. Our results indicate that B.1.416 originated in Senegal and was exported mainly to Europe. In contrast, B.1.1.420 was introduced from Italy, gained fitness in Senegal, and then spread worldwide. Since both B.1.416 and B.1.1.420 lineages carry several positive selected mutations in the spike and nucleocapsid genes, each of which may explain their local dominance, their mutation profiles should be carefully monitored. As the pandemic continues to evolve, molecular surveillance in all regions of Africa will play a key role in stemming its spread.