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Incident COVID-19 and Hospitalizations by Variant Era Among Vaccinated Solid Organ Transplant Recipients
research-article
Author(s):
Teresa Po-Yu Chiang , MD, MPH
1 ,
Aura T. Abedon , BS
2 ,
Jennifer L. Alejo , MD
2 ,
Dorry L. Segev , MD, PhD
1 ,
Allan B. Massie , PhD
1 ,
William A. Werbel , MD, PhD
3
,
Publication date (Electronic):
18 August 2023
Journal:
JAMA Network Open
Publisher:
American Medical Association
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Abstract
This cohort study evaluates the incidence of COVID-19 and hospitalizations across variant eras in 2021 and 2022 among vaccinated solid organ transplant (SOT) recipients.
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Most cited references6
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An interactive web-based dashboard to track COVID-19 in real time
Ensheng Dong, Hongru Du, Lauren Gardner (2020)
In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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Attenuated fusogenicity and pathogenicity of SARS-CoV-2 Omicron variant
Rigel Suzuki, Daichi Yamasoba, Izumi Kimura … (2022)
The emergence of the Omicron variant of SARS-CoV-2 is an urgent global health concern 1 . In this study, our statistical modelling suggests that Omicron has spread more rapidly than the Delta variant in several countries including South Africa. Cell culture experiments showed Omicron to be less fusogenic than Delta and than an ancestral strain of SARS-CoV-2. Although the spike (S) protein of Delta is efficiently cleaved into two subunits, which facilitates cell–cell fusion 2,3 , the Omicron S protein was less efficiently cleaved compared to the S proteins of Delta and ancestral SARS-CoV-2. Furthermore, in a hamster model, Omicron showed decreased lung infectivity and was less pathogenic compared to Delta and ancestral SARS-CoV-2. Our multiscale investigations reveal the virological characteristics of Omicron, including rapid growth in the human population, lower fusogenicity and attenuated pathogenicity.
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COVID-19 in solid organ transplant: A multi-center cohort study
Olivia Kates, Brandy M Haydel, Sander Florman … (2020)
Abstract Background The COVID-19 pandemic has led to significant reductions in transplantation, motivated in part by concerns of disproportionately more severe disease among solid organ transplant (SOT) recipients. However, clinical features, outcomes, and predictors of mortality in SOT recipients are not well-described. Methods We performed a multi-center cohort study of SOT recipients with laboratory-confirmed COVID-19. Data were collected using standardized intake and 28-day follow-up electronic case report forms. Multivariable logistic regression was used to identify risk factors for the primary endpoint, 28-day mortality, among hospitalized patients. Results Four hundred eighty-two SOT recipients from >50 transplant centers were included: 318 (66%) kidney or kidney/pancreas, 73 (15.1%) liver, 57 (11.8%) heart, and 30 (6.2%) lung. Median age was 58 (IQR 46-57), median time post-transplant was 5 years (IQR 2-10), 61% were male, and 92% had ≥1 underlying comorbidity. Among those hospitalized (376 [78%]), 117 (31%) required mechanical ventilation, and 77 (20.5%) died by 28 days after diagnosis. Specific underlying comorbidities (age >65 [aOR 3.0, 95%CI 1.7-5.5, p<0.001], congestive heart failure [aOR 3.2, 95%CI 1.4-7.0, p=0.004], chronic lung disease [aOR 2.5, 95%CI 1.2-5.2, p=0.018], obesity [aOR 1.9, 95% CI 1.0-3.4, p=0.039]) and presenting findings (lymphopenia [aOR 1.9, 95%CI 1.1-3.5, p=0.033], abnormal chest imaging [aOR 2.9, 95%CI 1.1-7.5, p=0.027]) were independently associated with mortality. Multiple measures of immunosuppression intensity were not associated with mortality. Conclusions Mortality among SOT recipients hospitalized for COVID-19 was 20.5%. Age and underlying comorbidities rather than immunosuppression intensity-related measures were major drivers of mortality.
Author and article information
Journal
Journal ID (nlm-ta): JAMA Netw Open
Journal ID (iso-abbrev): JAMA Netw Open
Title:
JAMA Network Open
Publisher:
American Medical Association
ISSN
(Electronic):
2574-3805
Publication date
(Electronic):
18
August
2023
Publication date Collection:
August
2023
Publication date PMC-release: 18
August
2023
Volume: 6
Issue: 8
Electronic Location Identifier: e2329736
Affiliations
Author notes
Article Information
Open Access: This is an open access article distributed under the terms of the
CC-BY License. © 2023 Chiang TPY et al.
JAMA Network Open.
Corresponding Author: William A. Werbel, MD, PhD, Johns Hopkins School of Medicine, 2000 E Monument St,
Baltimore, MD 21205 (
wwerbel1@
123456jhmi.edu
).
Author Contributions: Drs Chiang and Werbel had full access to all of the data in the study and take responsibility
for the integrity of the data and the accuracy of the data analysis. Dr Chiang and
Ms Abedon contributed equally as first authors. Drs Werbel and Massie contributed
equally as senior authors.
Critical review of the manuscript for important intellectual content: Chiang, Alejo, Segev, Massie, Werbel.
Conflict of Interest Disclosures: Dr Segev reported receiving consulting and/or speaking honoraria from Sanofi, Novartis,
Veloxis, Mallinckrodt, Jazz Pharmaceuticals, CSL Behring, Thermo Fisher Scientific,
Caredx, Transmedics, Kamada, MediGO, Regeneron, AstraZeneca, Takeda/Shire, Novavax,
and Bridge to Life. Dr Werbel reported receiving personal fees from Novavax, AstraZeneca,
the Infectious Diseases Society of America COVID-19 Real Time Learning Network, and
GlobalData and receiving grants from the National Institutes of Health outside the
submitted work. No other disclosures were reported.
Funding/Support: This work was supported by the Ben-Dov family, the Trokhan Patterson family, grants
T32DK007713 (Dr Alejo) and R01DK132395 (Dr Massie) from the National Institute of
Diabetes and Digestive and Kidney Diseases, and grants U01AI138897-S04 and K24AI144954
(Dr Segev) and K23AI157893 (Dr Werbel) from the National Institute of Allergy and
Infectious Diseases.
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management,
analysis, and interpretation of the data; preparation, review, or approval of the
manuscript; and decision to submit the manuscript for publication.
Data Sharing Statement: See
Supplement 2.
Additional Contributions: We thank the participants and household contacts of the Johns Hopkins COVID-19 Transplant
Vaccine Study and the members of the study team: Rivka R. Abedon, AA, Nicole Fortune
Hernandez, BS, Alexa A. Jefferis, BS, Letitia Thomas, Jake D. Kim, BS, Mayan Teles,
BS, and Brian J. Boyarsky, MD, PhD (Department of Surgery, Johns Hopkins University
School of Medicine), and Michael T. Ou, MD (Department of Surgery, University of California,
San Francisco), assisted with data collection and administrative assistance; Chunyi
Xia, MHS, Alex Philip, Juhi Patel, Roni Shanoada, BSc, MSc, and Nicolas Henriquez
(Department of Surgery, Johns Hopkins University School of Medicine) assisted with
data collection; and Diane Brown, RN, MSN, and Sarah Hussain, MBBS, MSHI (Department
of Medicine, Johns Hopkins University School of Medicine), Daniel S. Warren, PhD (Department
of Surgery, Johns Hopkins University School of Medicine), and Carolyn Sidoti, BS (Department
of Surgery, NYU Grossman School of Medicine), assisted with administrative assistance.
These individuals were not compensated outside their employment.
Article
Publisher ID: zld230156DOI: 10.1001/jamanetworkopen.2023.29736
PMC ID: 10439474
PubMed ID: 37594763
SO-VID: 805c0436-d05e-411f-a9ca-39bf6f92e4a8
Copyright © Copyright 2023 Chiang TPY et al.
JAMA Network Open.
License:
This is an open access article distributed under the terms of the CC-BY License.
History
Date
received
: 17
June
2023
Date
accepted
: 12
July
2023
Categories
Subject:
Research
Subject:
Research Letter
Subject:
Online Only
Subject:
Public Health
Data availability: