Evidence map›Paper›PMID 33442712›Full record

ArticlemedRxiv : the preprint server for health sciences2021

The Joint Impact of COVID-19 Vaccination and Non-Pharmaceutical Interventions on Infections, Hospitalizations, and Mortality: An Agent-Based Simulation.

Mehul D Patel, Erik Rosenstrom, Julie S Ivy, Maria E Mayorga, Pinar Keskinocak, Ross M Boyce, Kristen Hassmiller Lich, Raymond L Smith, Karl T Johnson, Julie L Swann

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 31 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Mehul D PatelDepartment of Emergency Medicine, School of Medicine, University of North Carolina at Chapel Hill.
Erik RosenstromDepartment of Industrial and Systems Engineering, North Carolina State University.
Julie S IvyDepartment of Industrial and Systems Engineering, North Carolina State University.
Maria E MayorgaDepartment of Industrial and Systems Engineering, North Carolina State University.
Pinar KeskinocakDepartment of Industrial and Systems Engineering, Georgia Institute of Technology.
Ross M BoyceDivision of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill.
Kristen Hassmiller LichDepartment of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill.
Raymond L SmithDepartment of Engineering, College of Engineering and Technology, East Carolina University.
Karl T JohnsonDepartment of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill.
Julie L SwannDepartment of Industrial and Systems Engineering, North Carolina State University.
North Carolina State University · USUniversity of North Carolina at Chapel Hill · USEast Carolina University · USGeorgia Institute of Technology · US

Funding

Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
North Carolina Translational and Clinical Science Institute (NC TraCS) KL2KL2TR002490 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WEINBERGER, MORRIS · 2018 to 2022
$11.0M
NCATS NIH HHS KL2 TR002490NCATS NIH HHS UL1 TR002489
6 · The paper itself

Abstract

Background: Vaccination against SARS-CoV-2 has the potential to significantly reduce transmission and morbidity and mortality due to COVID-19. This modeling study simulated the comparative and joint impact of COVID-19 vaccine efficacy and coverage with and without non-pharmaceutical interventions (NPIs) on total infections, hospitalizations, and deaths. Methods: An agent-based simulation model was employed to estimate incident SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths over 18 months for the State of North Carolina, a population of roughly 10.5 million. Vaccine efficacy of 50% and 90% and vaccine coverage of 25%, 50%, and 75% (at the end of a 6-month distribution period) were evaluated. Six vaccination scenarios were simulated with NPIs (i.e., reduced mobility, school closings, face mask usage) maintained and removed during the period of vaccine distribution. Results: In the worst-case vaccination scenario (50% efficacy and 25% coverage), 2,231,134 new SARS-CoV-2 infections occurred with NPIs removed and 799,949 infections with NPIs maintained. In contrast, in the best-case scenario (90% efficacy and 75% coverage), there were 450,575 new infections with NPIs maintained and 527,409 with NPIs removed. When NPIs were removed, lower efficacy (50%) and higher coverage (75%) reduced infection risk by a greater magnitude than higher efficacy (90%) and lower coverage (25%) compared to the worst-case scenario (absolute risk reduction 13% and 8%, respectively). Conclusion: Simulation results suggest that premature lifting of NPIs while vaccines are distributed may result in substantial increases in infections, hospitalizations, and deaths. Furthermore, as NPIs are removed, higher vaccination coverage with less efficacious vaccines can contribute to a larger reduction in risk of SARS-CoV-2 infection compared to more efficacious vaccines at lower coverage. Our findings highlight the need for well-resourced and coordinated efforts to achieve high vaccine coverage and continued adherence to NPIs before many pre-pandemic activities can be resumed.

Identifiers

PMID33442712
PMCPMC7805476
OpenAlexW3115140435

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.