Evidence map›Paper›PMID 40733636›Full record

ArticleViruses2025

Integrated Analysis of the 2022 SARS-CoV-2 Omicron Lineage Replacement Dynamics in Connecticut, US.

Nicholas F G Chen, Kien Pham, Chrispin Chaguza, Rafael Lopes, Fayette Klaassen, Chaney C Kalinich, Yale Sars-CoV-Genomic Surveillance Initiative, Nicholas Kerantzas, Sameer Pandya, David Ferguson and 6 more

Abstract read
In one paragraph

Article in Viruses, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Nicholas F G ChenDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA.
Kien PhamDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA.
Chrispin ChaguzaDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA.
Rafael LopesDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA.ORCID 0000-0002-9416-6145
Fayette KlaassenDepartment of Global Health & Population, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.
Chaney C KalinichDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA.ORCID 0000-0001-9675-0065
Yale Sars-CoV-Genomic Surveillance Initiative
Nicholas KerantzasDepartment of Laboratory Medicine, Yale School of Medicine, New Haven, CT 06510, USA.
Sameer PandyaDepartment of Laboratory Medicine, Yale School of Medicine, New Haven, CT 06510, USA.
David FergusonDepartment of Laboratory Medicine, Yale School of Medicine, New Haven, CT 06510, USA.
Wade SchulzDepartment of Laboratory Medicine, Yale School of Medicine, New Haven, CT 06510, USA.
Daniel M WeinbergerDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA.
Virginia E PitzerDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA.
Joshua L WarrenPublic Health Modeling Unit, Yale School of Public Health, New Haven, CT 06510, USA.ORCID 0000-0002-6274-6970
Nathan D GrubaughDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA.
Anne M HahnDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA.ORCID 0000-0003-0710-6775

Funding

Short-Term Reserch Training: Students in Health SchoolsT35HL007649 · NHLBI · YALE UNIVERSITY · PI Sarwat I Chaudhry, Erica L Herzog · 1987 to 2026
$5.7M
CDC Broad Agency Announcement Contracts 75D30121C10273CDC Broad Agency Announcement Contracts 75D30122C14697Connecticut Department of Public Health 21PSX0049NHLBI NIH HHS T35 HL007649
6 · The paper itself

Abstract

In 2022, consecutive sweeps of highly transmissible SARS-CoV-2 Omicron-derived lineages (B.1.1.529*) maintained viral transmission despite extensive antigen exposure from both vaccinations and infections. To better understand Omicron variant emergence in the context of the dynamic fitness landscape of 2022, we aimed to explore putative drivers behind SARS-CoV-2 lineage replacements. Variant fitness is determined through its ability to either outrun previously dominant lineages or more efficiently circumvent host immune responses to previous infections and vaccinations. By analyzing data collected through our local genomic surveillance program from Connecticut, USA, we compared emerging Omicron lineages' growth rates, estimated infections, effective reproductive rates, average viral copy numbers, and likelihood for causing infections in recently vaccinated individuals. We find that newly emerging Omicron lineages outcompeted dominant lineages through a combination of enhanced viral shedding or advanced immune escape depending on the population-level exposure state. This analysis integrates individual-level sequencing data with demographic, vaccination, laboratory, and epidemiological data and provides further insights into host-pathogen dynamics beyond public aggregate data.

Indexed as

COVID-19SARS-CoV-2ConnecticutGenome, ViralHumansVirus SheddingGenomic surveillancevariant fitnessviral evolution

Identifiers

PMID40733636
PMCPMC12299087

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.