Impacts of vaccination and asymptomatic testing on SARS-CoV-2 transmission dynamics in a university setting

Nixon, Emily; Thomas, Amy; Stocks, Daniel; Barreaux, Antoine M. G.; Hemani, Gibran; Trickey, Adam; Kwiatkowska, Rachel; Walker, Josephine G.; Ellis, David; Danon, León; Relton, Caroline L; Christensen, Hannah; Pollock, Ellen Brooks

doi:10.1101/2021.11.22.21266565

Cited by 2 publications

(1 citation statement)

References 24 publications

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“…While rapid implementation of SARS-CoV-2 genome sequencing has proven useful in the investigation of COVID-19 dynamics in other institutional settings like healthcare, few studies have been conducted on university campuses [15][16][17][18][19][20][21][22][23]. Some studies in the university setting have evaluated testing programs to understand control of SARS-CoV-2 transmission, while others used modeling approaches to infer SARS-CoV-2 transmission or estimate the introduction and growth rate of particular variants [17,[24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Genomic surveillance of SARS-CoV-2 in a university community: insights into tracking variants, transmission, and spread of Gamma (P.1) variant

Ciubotariu

Dorman

Gorenstein

et al. 2022

Preprint

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Using a combination of data from routine surveillance, genomic sequencing, and phylogeographic analysis we tracked the spread and introduction events of SARS-CoV-2 variants focusing on a large university community. Here, we sequenced and analyzed 677 high-quality SARS-CoV-2 genomes from positive RNA samples collected from Purdue University students, faculty, and staff who tested positive for the virus between January 2021 and May 2021, comprising an average of 32% of weekly cases across the time frame. Our analysis of circulating SARS-CoV-2 variants over time revealed periods when Variant of Concern (VOC) Alpha (B.1.1.7) and Iota (B.1.526) reached rapid dominance and documented that VOC Gamma (P.1) was increasing in frequency as campus surveillance was ending. Phylodynamic analysis of Gamma genomes from campus alongside a subsampling of >20,000 previously published P.1 genomes revealed ten independent introductions of this variant into the Purdue community, predominantly from elsewhere in the United States, with introductions from within the state of Indiana and from Illinois, and possibly Washington and New York, suggesting a degree of domestic spread. We conclude that a robust and sustained active and passive surveillance program coupled with genomic sequencing during a pandemic offers important insights into the dynamics of pathogen arrival and spread in a campus community and can help guide mitigation measures.

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Section: Introductionmentioning

confidence: 99%

Genomic surveillance of SARS-CoV-2 in a university community: insights into tracking variants, transmission, and spread of Gamma (P.1) variant

Ciubotariu

Dorman

Gorenstein

et al. 2022

Preprint

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Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review

Espinosa,

Mora,

Sanabria

et al. 2024

Syst Rev

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Background The interaction between modelers and policymakers is becoming more common due to the increase in computing speed seen in recent decades. The recent pandemic caused by the SARS-CoV-2 virus was no exception. Thus, this study aims to identify and assess epidemiological mathematical models of SARS-CoV-2 applied to real-world data, including immunization for coronavirus 2019 (COVID-19). Methodology PubMed, JSTOR, medRxiv, LILACS, EconLit, and other databases were searched for studies employing epidemiological mathematical models of SARS-CoV-2 applied to real-world data. We summarized the information qualitatively, and each article included was assessed for bias risk using the Joanna Briggs Institute (JBI) and PROBAST checklist tool. The PROSPERO registration number is CRD42022344542. Findings In total, 5646 articles were retrieved, of which 411 were included. Most of the information was published in 2021. The countries with the highest number of studies were the United States, Canada, China, and the United Kingdom; no studies were found in low-income countries. The SEIR model (susceptible, exposed, infectious, and recovered) was the most frequently used approach, followed by agent-based modeling. Moreover, the most commonly used software were R, Matlab, and Python, with the most recurring health outcomes being death and recovery. According to the JBI assessment, 61.4% of articles were considered to have a low risk of bias. Interpretation The utilization of mathematical models increased following the onset of the SARS-CoV-2 pandemic. Stakeholders have begun to incorporate these analytical tools more extensively into public policy, enabling the construction of various scenarios for public health. This contribution adds value to informed decision-making. Therefore, understanding their advancements, strengths, and limitations is essential.

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Impacts of vaccination and asymptomatic testing on SARS-CoV-2 transmission dynamics in a university setting

Cited by 2 publications

References 24 publications

Genomic surveillance of SARS-CoV-2 in a university community: insights into tracking variants, transmission, and spread of Gamma (P.1) variant

Genomic surveillance of SARS-CoV-2 in a university community: insights into tracking variants, transmission, and spread of Gamma (P.1) variant

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review

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