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Vaccine Efficacy Needed for a COVID-19 Coronavirus Vaccine to Prevent or Stop an Epidemic as the Sole Intervention.
Bartsch, Sarah M; O'Shea, Kelly J; Ferguson, Marie C; Bottazzi, Maria Elena; Wedlock, Patrick T; Strych, Ulrich; McKinnell, James A; Siegmund, Sheryl S; Cox, Sarah N; Hotez, Peter J; Lee, Bruce Y.
  • Bartsch SM; Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York.
  • O'Shea KJ; Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York.
  • Ferguson MC; Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York.
  • Bottazzi ME; National School of Tropical Medicine, Baylor College of Medicine, Houston, Texas; Department of Pediatrics, Baylor College of Medicine, Houston, Texas; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas.
  • Wedlock PT; Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York.
  • Strych U; National School of Tropical Medicine, Baylor College of Medicine, Houston, Texas; Department of Pediatrics, Baylor College of Medicine, Houston, Texas; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas.
  • McKinnell JA; Infectious Disease Clinical Outcomes Research Unit (ID-CORE), Lundquist Institute, Harbor-UCLA Medical Center, Torrance, California; Torrance Memorial Medical Center, Torrance, California.
  • Siegmund SS; Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York.
  • Cox SN; Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York.
  • Hotez PJ; National School of Tropical Medicine, Baylor College of Medicine, Houston, Texas; Department of Pediatrics, Baylor College of Medicine, Houston, Texas; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas.
  • Lee BY; Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York. Electronic address: bruceleemdmba@gmail.com.
Am J Prev Med ; 59(4): 493-503, 2020 10.
Article in English | MEDLINE | ID: covidwho-645862
ABSTRACT

INTRODUCTION:

Given the continuing COVID-19 pandemic and much of the U.S. implementing social distancing owing to the lack of alternatives, there has been a push to develop a vaccine to eliminate the need for social distancing.

METHODS:

In 2020, the team developed a computational model of the U.S. simulating the spread of COVID-19 coronavirus and vaccination.

RESULTS:

Simulation experiments revealed that to prevent an epidemic (reduce the peak by >99%), the vaccine efficacy has to be at least 60% when vaccination coverage is 100% (reproduction number=2.5-3.5). This vaccine efficacy threshold rises to 70% when coverage drops to 75% and up to 80% when coverage drops to 60% when reproduction number is 2.5, rising to 80% when coverage drops to 75% when the reproduction number is 3.5. To extinguish an ongoing epidemic, the vaccine efficacy has to be at least 60% when coverage is 100% and at least 80% when coverage drops to 75% to reduce the peak by 85%-86%, 61%-62%, and 32% when vaccination occurs after 5%, 15%, and 30% of the population, respectively, have already been exposed to COVID-19 coronavirus. A vaccine with an efficacy between 60% and 80% could still obviate the need for other measures under certain circumstances such as much higher, and in some cases, potentially unachievable, vaccination coverages.

CONCLUSIONS:

This study found that the vaccine has to have an efficacy of at least 70% to prevent an epidemic and of at least 80% to largely extinguish an epidemic without any other measures (e.g., social distancing).
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Computer Simulation / Viral Vaccines / Communicable Disease Control / Vaccination / Coronavirus Infections / Pandemics Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines Limits: Humans Country/Region as subject: North America Language: English Journal: Am J Prev Med Journal subject: Public Health Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Computer Simulation / Viral Vaccines / Communicable Disease Control / Vaccination / Coronavirus Infections / Pandemics Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines Limits: Humans Country/Region as subject: North America Language: English Journal: Am J Prev Med Journal subject: Public Health Year: 2020 Document Type: Article