An Early Pandemic Analysis of SARS-CoV-2 Population Structure and Dynamics in Arizona

Abstract

In December of 2019, a novel coronavirus, SARS-CoV-2, emerged in the city of Wuhan, China, causing severe morbidity and mortality. Since then, the virus has swept across the globe, causing millions of confirmed infections and hundreds of thousands of deaths. To better understand the nature of the pandemic and the introduction and spread of the virus in Arizona, we sequenced viral genomes from clinical samples tested at the TGen North Clinical Laboratory, the Arizona Department of Health Services, and those collected as part of community surveillance projects at Arizona State University and the University of Arizona. Phylogenetic analysis of 84 genomes from across Arizona revealed a minimum of 11 distinct introductions inferred to have occurred during February and March. We show that >80% of our sequences descend from strains that were initially circulating widely in Europe but have since dominated the outbreak in the United States. In addition, we show that the first reported case of community transmission in Arizona descended from the Washington state outbreak that was discovered in late February. Notably, none of the observed transmission clusters are epidemiologically linked to the original travel-related case in the state, suggesting successful early isolation and quarantine. Finally, we use molecular clock analyses to demonstrate a lack of identifiable, widespread cryptic transmission in Arizona prior to the middle of February 2020. IMPORTANCE As the COVID-19 pandemic swept across the United States, there was great differential impact on local and regional communities. One of the earliest and hardest hit regions was in New York, while at the same time Arizona (for example) had low incidence. That situation has changed dramatically, with Arizona now having the highest rate of disease increase in the country. Understanding the roots of the pandemic during the initial months is essential as the pandemic continues and reaches new heights. Genomic analysis and phylogenetic modeling of SARS-COV-2 in Arizona can help to reconstruct population composition and predict the earliest undetected introductions. This foundational work represents the basis for future analysis and understanding as the pandemic continues.

High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants

“…These 17 samples were from the states of Arizona, Kentucky and Massachusetts (Figure 4B). In wastewater-derived sequences from Arizona, which represents the greatest proportion of samples, the observed circulating lineages based on clinical-derived sequences are well represented (Ladner et al, 2020), with an additional nine possible circulating lineages identified.…”

Mitigating a COVID-19 Outbreak Among Major League Baseball Players — United States, 2020

“…SARS-CoV-2 RT-PCR testing was conducted at the Sports Medicine Research and Testing Laboratory (Utah) or the Rutgers Clinical Genomic Laboratory (New Jersey). Translational Genomics Research Institute (Arizona) completed whole genome sequencing on residual diagnostic samples using standard methods ( 3 ). Sequence reads were aligned and compared with a Wuhan reference strain; all variants were identified and compared with the global GISAID SARS-CoV-2 database (>80,000 genomes).…”

Sequencing the pandemic: rapid and high-throughput processing and analysis of COVID-19 clinical samples for 21st century public health

“…Only consensus genomes covering at least 90% of the reference genome with an average depth of ≥30X were used in subsequent analyses. Consensus genomes generated using these methods include those from Ladner et al 19 . Statistics reported for each sample included: total reads, number of reads aligned to reference, percent of reads aligned to reference, coverage breadth, average depth, and any SNPs and INDELs found in ≥10% of the reads at that position.…”

“…While rapid-turnaround genomics may prove essential for outbreak containment, retrospective studies will continue to be necessary to track pathogen evolution, gauge success of public health interventions, and to evaluate pathogen/host movement and behavior. With the recent SARS-CoV-2 pandemic, retrospective studies have so-far proven successful in identifying the timing and sources of outbreaks on a local 19 and global scale 5,20 , in evaluating the effectiveness of early interventions 5 , and in identifying super-spreader events 21 . Thus, in addition to real-time monitoring, high-throughput, costeffective sequencing and analysis are needed to gain a better understanding of pandemics.…”