Modeling the Impact of Vaccine Dose Prioritization Strategies During the 2022 Mpox Outbreak.
Supporting Files
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March 2025
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Available in CDC Stacks on July 31, 2025, 12:00 AM
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English
Details
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Alternative Title:American Journal of Epidemiology, 2025, v. 195, no. 4: Modeling the Impact of Vaccine Dose Prioritization Strategies During the 2022 Mpox Outbreak.
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Journal Article:American Journal of Epidemiology
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Personal Author:
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Description:Early in the 2022 mpox outbreak, the US recommendation was to administer two doses of the JYNNEOS vaccine 4 weeks apart. However, because of limited vaccine supply, New York City (NYC) prioritized single dose vaccination. We estimated mpox cases averted by this strategy compared to strategies that prioritized 2-dose vaccination for a smaller portion of the population. We fit a network transmission model to incident mpox cases in NYC. Model output consisted of predicted cases over time when vaccine doses were administered with the "first-dose priority" strategy, compared with counterfactual simulations, where doses were administered to those eligible for a second dose ahead of those waiting for a first dose ("intermediate" strategy), or where individuals were preallocated full courses of the vaccine ("second-dose priority" strategy). We estimate that NYC's strategy averted 66% (IQR, 47%-78%) of potential mpox cases compared to no vaccination. This "first-dose priority" strategy averted 0.6% (IQR, -11% to 9.8%) more cases than the "intermediate" strategy, and 17% (IQR, 2.9%-38%) more cases than the "second-dose priority" strategy. Thus, for the 2022 mpox outbreak in NYC, preallocating vaccine doses to ensure full vaccination in a high-priority subset of the population would have increased the size of the outbreak.
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Content Notes:Author manuscript
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Source:American Journal of Epidemiology, 2025, v. 195, no. 4
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DOI:
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ISSN:0002-9262 ; 1476-6256
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Pubmed ID:40069944
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Pubmed Central ID:PMC12311848
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Pages in Document:948-955 (15 pdf pages)
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Volume:195
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Issue:4
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Main Document Checksum:urn:sha-512:89e1646f25a4b38f4c640fe545620e76aec7bf2b65384c86d13b417cd488de5e7a9a973cc1234836b530b3bcb3a8e53b6a80d9ea69d0e9bb88765fe06144fc40
Supporting Files
File Language:
English
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