Lives and Costs Saved by Expanding and Expediting Coronavirus Disease 2019 Vaccination.
COVID-19
coronavirus
coverage
rate
vaccination
Journal
The Journal of infectious diseases
ISSN: 1537-6613
Titre abrégé: J Infect Dis
Pays: United States
ID NLM: 0413675
Informations de publication
Date de publication:
17 09 2021
17 09 2021
Historique:
received:
25
01
2021
accepted:
28
04
2021
pubmed:
7
5
2021
medline:
30
9
2021
entrez:
6
5
2021
Statut:
ppublish
Résumé
With multiple coronavirus disease 2019 (COVID-19) vaccines available, understanding the epidemiologic, clinical, and economic value of increasing coverage levels and expediting vaccination is important. We developed a computational model (transmission and age-stratified clinical and economics outcome model) representing the United States population, COVID-19 coronavirus spread (February 2020-December 2022), and vaccination to determine the impact of increasing coverage and expediting time to achieve coverage. When achieving a given vaccination coverage in 270 days (70% vaccine efficacy), every 1% increase in coverage can avert an average of 876 800 (217 000-2 398 000) cases, varying with the number of people already vaccinated. For example, each 1% increase between 40% and 50% coverage can prevent 1.5 million cases, 56 240 hospitalizations, and 6660 deaths; gain 77 590 quality-adjusted life-years (QALYs); and save $602.8 million in direct medical costs and $1.3 billion in productivity losses. Expediting to 180 days could save an additional 5.8 million cases, 215 790 hospitalizations, 26 370 deaths, 206 520 QALYs, $3.5 billion in direct medical costs, and $4.3 billion in productivity losses. Our study quantifies the potential value of decreasing vaccine hesitancy and increasing vaccination coverage and how this value may decrease with the time it takes to achieve coverage, emphasizing the need to reach high coverage levels as soon as possible, especially before the fall/winter.
Sections du résumé
BACKGROUND
With multiple coronavirus disease 2019 (COVID-19) vaccines available, understanding the epidemiologic, clinical, and economic value of increasing coverage levels and expediting vaccination is important.
METHODS
We developed a computational model (transmission and age-stratified clinical and economics outcome model) representing the United States population, COVID-19 coronavirus spread (February 2020-December 2022), and vaccination to determine the impact of increasing coverage and expediting time to achieve coverage.
RESULTS
When achieving a given vaccination coverage in 270 days (70% vaccine efficacy), every 1% increase in coverage can avert an average of 876 800 (217 000-2 398 000) cases, varying with the number of people already vaccinated. For example, each 1% increase between 40% and 50% coverage can prevent 1.5 million cases, 56 240 hospitalizations, and 6660 deaths; gain 77 590 quality-adjusted life-years (QALYs); and save $602.8 million in direct medical costs and $1.3 billion in productivity losses. Expediting to 180 days could save an additional 5.8 million cases, 215 790 hospitalizations, 26 370 deaths, 206 520 QALYs, $3.5 billion in direct medical costs, and $4.3 billion in productivity losses.
CONCLUSIONS
Our study quantifies the potential value of decreasing vaccine hesitancy and increasing vaccination coverage and how this value may decrease with the time it takes to achieve coverage, emphasizing the need to reach high coverage levels as soon as possible, especially before the fall/winter.
Identifiants
pubmed: 33954775
pii: 6267841
doi: 10.1093/infdis/jiab233
pmc: PMC8136017
doi:
Substances chimiques
COVID-19 Vaccines
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
938-948Subventions
Organisme : NIGMS NIH HHS
ID : R01 GM127512
Pays : United States
Organisme : AHRQ HHS
ID : R01 HS028165
Pays : United States
Organisme : Models of Infectious Disease Agent Study
ID : R01GM127512
Organisme : City University of New York Graduate School of Public Health and Health Policy
ID : 1R01HS028165-01)
Commentaires et corrections
Type : CommentIn
Informations de copyright
© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.
Références
Proc Natl Acad Sci U S A. 2020 Nov 3;117(44):27456-27464
pubmed: 33051302
Lancet. 2020 May 16;395(10236):1527-1529
pubmed: 32353328
Lancet Infect Dis. 2020 Sep;20(9):e245-e249
pubmed: 32687805
PLoS Comput Biol. 2021 Jan 7;17(1):e1008470
pubmed: 33411742
Am J Prev Med. 2021 May;60(5):605-613
pubmed: 33632650
N Engl J Med. 2020 Dec 31;383(27):2684-2686
pubmed: 33326716
JAMA. 2021 Mar 2;325(9):883-885
pubmed: 33480971
Nature. 2020 Jun;582(7811):230-233
pubmed: 32499650
MMWR Morb Mortal Wkly Rep. 2021 Mar 12;70(10):350-354
pubmed: 33705364
JAMA. 2021 Apr 6;325(13):1241-1243
pubmed: 33729423
MMWR Morb Mortal Wkly Rep. 2021 Apr 02;70(13):495-500
pubmed: 33793460
N Engl J Med. 2021 Apr 15;384(15):1412-1423
pubmed: 33626250
EClinicalMedicine. 2020 Sep;26:100495
pubmed: 32838242
Microbes Infect. 2020 May - Jun;22(4-5):162-164
pubmed: 32442682
Am J Prev Med. 2020 Oct;59(4):493-503
pubmed: 32778354
Lancet. 2021 May 8;397(10286):1725-1735
pubmed: 33901423
Infect Control Hosp Epidemiol. 2021 Jan 11;:1-9
pubmed: 33427134
N Engl J Med. 2021 Mar 8;384(15):1466-1468
pubmed: 33684280
PLoS Med. 2018 Jun 12;15(6):e1002578
pubmed: 29894470
J Clin Invest. 2021 Apr 1;131(7):
pubmed: 33630759