Defining the Pandemic at the State Level: Sequence-Based Epidemiology of the SARS-CoV-2 virus by the Arizona COVID-19 Genomics Union (ACGU)

Ladner, Jason T.; Larsen, Brendan B.; Bowers, Jolene R.; Hepp, Crystal M.; Bolyen, Evan; Folkerts, Megan; Sheridan, Krystal; Pfeiffer, Ashlyn; Yaglom, Hayley; Lemmer, Darrin; Sahl, Jason W.; Kaelin, Emily A; Maqsood, Rabia; Bokulich, Nicholas A.; Quirk, Grace; Watt, Thomas D; Komatsu, Kenneth; Waddell, Victor; Lim, Efrem S.; Caporaso, J. Gregory; Engelthaler, David M.; Worobey, Michael; Keim, Paul

doi:10.1101/2020.05.08.20095935

Cited by 6 publications

(5 citation statements)

References 36 publications

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“…Our approach infers that the European B.1 clade (emanating from the green node labeled 0.86 in Fig. 5), the same one that dominates in New York City (14) and Arizona (23), had an origin in Italy, as might be expected from the epidemiological evidence. Both travel history and unsampled diversity contribute to this inference.…”

Section: Early Establishment Of Sars-cov-2 In Europementioning

confidence: 71%

The emergence of SARS-CoV-2 in Europe and North America

Worobey

Pekar

Larsen

et al. 2020

Science

Self Cite

356

355

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Accurate understanding of the global spread of emerging viruses is critically important for public health responses and for anticipating and preventing future outbreaks. Here, we elucidate when, where and how the earliest sustained SARS-CoV-2 transmission networks became established in Europe and North America. Our results suggest that rapid early interventions successfully prevented early introductions of the virus into Germany and the US from taking hold. Other, later introductions of the virus from China to both Italy and to Washington State founded the earliest sustained European and North America transmission networks. Our analyses demonstrate the effectiveness of public health measures in preventing onward transmission and show that intensive testing and contact tracing could have prevented SARS-CoV-2 from becoming established.

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Section: Early Establishment Of Sars-cov-2 In Europementioning

confidence: 71%

The emergence of SARS-CoV-2 in Europe and North America

Worobey

Pekar

Larsen

et al. 2020

Science

Self Cite

356

355

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“…However, the disease was spreading in increasing intensity waves in both states. Recent results on the introduction and spread of the virus in Arizona [19], based on sequencing viral genomes from clinical samples, revealed a minimum of 9 distinct introductions throughout February and March 2020. Since there is no clear trend as of June 11, 2020, of each state getting over its intensity peak, the single-wave fit predicts a linear increase of the total number of expected cases.…”

Section: Resultsmentioning

confidence: 99%

“…Recent results on the introduction and spread of the virus in Arizona [19], based on sequencing viral genomes from clinical samples, collected as part of community surveillance projects and particular phylogenetic analysis of genomes, reveal a minimum of 9 distinct introductions throughout February and March 2020. Furthermore, it was shown that the first reported case of community transmission in Arizona descended from the Washington state outbreak discovered in late February 2020, but none of the observed transmission clusters were found to be epidemiologically linked to the original travel-related cases in the state, suggesting early isolation and quarantine effects.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Covid-19 Pandemic Response of the US States

Neofotistos

Kaxiras

2020

Preprint

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Background: The United States of America (USA) has been the country worst affected, in absolute terms, by the Covid-19 pandemic. The country comprises 50 states under a federal system. The impact of the pandemic has resulted in different responses at the state level, which are driven by differing intervention policies, demographics, connectedness and other factors. Understanding the dynamics of the Covid-19 pandemic at the state level is essential in predicting its future evolution. Objective: Our objective is to identify and characterize multiple waves of the pandemic by analyzing the reported infected population curve in each of the 50 US states. Based on the intensity of the waves, characterized by declining, stationary, or increasing strengths, each state's response can be inferred and quantified. Methods: We apply a recently proposed multiple-wave model to fit the infected population data for each state in USA, and use the proposed Pandemic Response Index to quantify their response to the Covid-19 pandemic. Results: We have analyzed reported infected cases from each one of the 50 USA states and the District of Columbia, based on the multiple-wave model, and present the relevant parameters. Multiple waves have been identified and this model is found to describe the data better. Each of the states can be classified into one of three distinct classes characterized by declining, increasing, or stationary strength of the waves following the initial one. The effectiveness of intervention measures can be inferred by the peak intensities of the waves, and states with similar population characteristics can be directly compared. We estimate how much lower the number of infections might have been, if early and strict intervention measures had been imposed to stop the disease spread at the first wave, as was the case for certain states. Based on our model's results, we compute the value of the Pandemic Response Index, a recently introduced metric for quantifying in an objective manner the response to the pandemic. Conclusions: Our results reveal a series of epidemic waves, characterizing USA's pandemic response at the state level, and also infer to what extent the imposition of early intervention measures could have had on the spread and impact of the disease. As of June 11, 2020, only 19 states and the District of Columbia (40% of the total) clearly exhibit declining trends in the numbers of reported infected cases, while 13 states exhibit stationary and 18 states increasing trends in the numbers of reported cases.

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“…Community transmission of unknown origin was first detected in California on February 26, followed quickly by Washington State (Chu et al, 2020b), Illinois and Florida, but only on March 7 in New York City. Retrospective genomic analyses have demonstrated that case-tracing and self-quarantine efforts were effective in preventing most known imported cases from propagating (Ladner et al, 2020; Gonzalez-Reiche et al, 2020; Worobey et al, 2020), but that the eventual outbreaks on the West Coast (Worobey et al, 2020; Chu et al, 2020b; Deng et al, 2020) and New York (Gonzalez-Reiche et al, 2020) were likely seeded by unknown imports in mid-February. By early March, cross-country spread was primarily due to interstate travel rather than international imports (Fauver et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Diverse local epidemics reveal the distinct effects of population density, demographics, climate, depletion of susceptibles, and intervention in the first wave of COVID-19 in the United States

Afshordi

Holder

Bahrami

et al. 2020

Preprint

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The SARS-CoV-2 pandemic has caused significant mortality and morbidity worldwide, sparing almost no community. As the disease will likely remain a threat for years to come, an understanding of the precise influences of human demographics and settlement, as well as the dynamic factors of climate, susceptible depletion, and intervention, on the spread of localized epidemics will be vital for mounting an effective response. We consider the entire set of local epidemics in the United States; a broad selection of demographic, population density, and climate factors; and local mobility data, tracking social distancing interventions, to determine the key factors driving the spread and containment of the virus. Assuming first a linear model for the rate of exponential growth (or decay) in cases/mortality, we find that population-weighted density, humidity, and median age dominate the dynamics of growth and decline, once interventions are accounted for. A focus on distinct metropolitan areas suggests that some locales benefited from the timing of a nearly simultaneous nationwide shutdown, and/or the regional climate conditions in mid-March; while others suffered significant outbreaks prior to intervention. Using a first-principles model of the infection spread, we then develop predictions for the impact of the relaxation of social distancing and local climate conditions. A few regions, where a significant fraction of the population was infected, show evidence that the epidemic has partially resolved via depletion of the susceptible population (i.e., "herd immunity"), while most regions in the United States remain overwhelmingly susceptible. These results will be important for optimal management of intervention strategies, which can be facilitated using our online dashboard.

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Defining the Pandemic at the State Level: Sequence-Based Epidemiology of the SARS-CoV-2 virus by the Arizona COVID-19 Genomics Union (ACGU)

Cited by 6 publications

References 36 publications

The emergence of SARS-CoV-2 in Europe and North America

The emergence of SARS-CoV-2 in Europe and North America

Modeling the Covid-19 Pandemic Response of the US States

Diverse local epidemics reveal the distinct effects of population density, demographics, climate, depletion of susceptibles, and intervention in the first wave of COVID-19 in the United States

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