Evidence map›Paper›PMID 39610653›Full record

ArticleVirus evolution2024

Community-level variability in Bronx COVID-19 hospitalizations associated with differing population immunity during the second year of the pandemic.

Ryan Forster, Anthony Griffen, Johanna P Daily, Libusha Kelly

Abstract read
In one paragraph

Article in Virus evolution, 2024. 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

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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

4 authors.

Ryan ForsterDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY 10461, United States.ORCID https://orcid.org/0009-0007-7099-4660
Anthony GriffenDepartment of Cell Biology, Albert Einstein College of Medicine, Bronx, NY 10461, United States.
Johanna P DailyDepartment of Microbiology & Immunology, Albert Einstein College of Medicine, Bronx, NY 10461, United States.
Libusha KellyDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY 10461, United States.

Funding

Characterizing Persistent Subclinical Neurobehavioral Effects of COVID-19 in a Diverse Urban PopulationR01NS123445 · NINDS · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI Johanna Patricia Daily, Michael Lawrence Lipton · 2022 to 2026
$3.4M
NINDS NIH HHS R01 NS123445
6 · The paper itself

Abstract

The Bronx, New York, exhibited unique peaks in the number of coronavirus disease 2019 (COVID-19) cases and hospitalizations compared to national trends. To determine which features of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus might underpin this local disease epidemiology, we conducted a comprehensive analysis of the genomic epidemiology of the four dominant strains of SARS-CoV-2 (Alpha, Iota, Delta, and Omicron) responsible for COVID-19 cases in the Bronx between March 2020 and January 2023. Genomic analysis revealed similar viral fitness for Alpha and Iota variants in the Bronx despite nationwide data showing higher cases of Alpha. However, Delta and Omicron variants had increased fitness within the borough. While the transmission dynamics of most variants in the Bronx corresponded with mutational fitness-based predictions of transmissibility, the Delta variant presented as an exception. Epidemiological modeling confirms Delta's advantages of higher transmissibility in Manhattan and Queens, but not the Bronx; wastewater analysis suggests underdetection of cases in the Bronx. The Alpha variant had slightly faster growth but a lower carrying capacity compared to Iota and Delta in all four boroughs, suggesting stronger limitations on Alpha's growth in New York City (NYC). The founder effect of Iota varied between higher vaccinated and lower vaccinated boroughs with longer delay, shorter duration, and lower fitness of the Alpha variant in lower vaccinated boroughs. Amino acid changes in T-cell and antibody epitopes revealed Delta and Iota having larger antigenic variability and antigenic profiles distant from local previously circulating lineages compared to Alpha. In concert with transmission modeling, our data suggest that the limited spread of Alpha may be due to a lack of adaptation to immunity in NYC. Overall, our study demonstrates that localized analyses and integration of orthogonal community-level datasets can provide key insights into the mechanisms of transmission and immunity patterns associated with regional COVID-19 incidence and disease severity that may be missed when analyzing broader datasets.

Indexed as

epidemiologygenomicsimmunity and localmodelingtransmission

Identifiers

PMID39610653
PMCPMC11604118

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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.