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使用机理网络模型对2022年猴痘疫情进行建模。

Modeling the 2022 Mpox Outbreak with a Mechanistic Network Model.

作者信息

Crenshaw Emma G, Onnela Jukka-Pekka

机构信息

Department of Biostatistics, Harvard TH Chan School of Public Health, 677 Huntington Avenue, Boston, 02115, MA, USA.

出版信息

ArXiv. 2025 May 8:arXiv:2505.05534v1.


DOI:
PMID:40386571
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12083702/
Abstract

BACKGROUND: The 2022 outbreak of mpox affected more than 80,000 individuals worldwide, most of whom were men who have sex with men (MSM) who likely contracted the disease through close contact during sex. Given the unprecedented number of mpox infections and the new route of infection, there was substantial uncertainty about how best to manage the outbreak. METHODS: We implemented a dynamic agent-based network model to simulate the spread of mpox in a United States-based MSM population. This model allowed us to implement data-informed dynamic network evolution to simulate realistic disease spreading and behavioral adaptations. RESULTS: We found that behavior change, the reduction in one-time partnerships, and widespread vaccination are effective in preventing the transmission of mpox and that earlier intervention has a greater effect, even when only a high-risk portion of the population participates. With no intervention, 16% of the population was infected (25th percentile, 75th percentiles of simulations: 15.3%, 16.6%). With vaccination and behavior change in only the 25% of individuals most likely to have a one-time partner, cumulative infections were reduced by 30%, or a total reduction in nearly 500 infections (mean: 11.3%, and : 9.6%, 13.5%). Earlier intervention further reduces cumulative infections; beginning vaccination a year before the outbreak results in only 5.5% of men being infected, averting 950 infections or nearly 10% of the total population in our model. We also show that sustained partnerships drive the early outbreak, while one-time partnerships drive transmission after the first initial weeks. The median effective reproductive number, , at days is 1.30 for casual partnerships, 1.00 for main, and 0.6 for one-time. By , the median for one-time partnerships has more than doubled to 1.48, while it decreased for casual and main partnerships: 0.46 and 0.29, respectively. CONCLUSION: With the ability to model individuals' behavior, mechanistic networks are particularly well suited to studying sexually transmitted infections, the spread and control of which are often governed by individual-level action. Our results contribute valuable insights into the role of different interventions and relationship types in mpox transmission dynamics.

摘要

背景:2022年猴痘疫情在全球感染了8万多人,其中大多数是男男性行为者(MSM),他们可能在性行为期间通过密切接触感染了这种疾病。鉴于猴痘感染数量空前以及新的感染途径,对于如何最好地应对此次疫情存在很大的不确定性。 方法:我们实施了一个基于主体的动态网络模型,以模拟猴痘在美国男男性行为者群体中的传播。该模型使我们能够实施基于数据的动态网络演化,以模拟现实的疾病传播和行为适应。 结果:我们发现行为改变、减少一次性性伴侣关系以及广泛接种疫苗在预防猴痘传播方面是有效的,而且早期干预效果更佳,即便只有高风险人群参与。在没有干预的情况下,16%的人口被感染(模拟的第25百分位数、第75百分位数:15.3%,16.6%)。仅对最有可能有一次性性伴侣的25%的个体进行疫苗接种和行为改变,累积感染减少了30%,即总共减少了近500例感染(平均值:11.3%,第25百分位数:9.6%,第75百分位数:13.5%)。早期干预进一步减少累积感染;在疫情爆发前一年开始接种疫苗,只有5.5%的男性被感染,避免了950例感染,占我们模型中总人口的近10%。我们还表明,稳定的性伴侣关系推动了早期疫情爆发,而一次性性伴侣关系在最初几周后推动传播。在第50天,随意性伴侣关系的有效繁殖数中位数R̂为1.30,主要性伴侣关系为1.00,一次性性伴侣关系为0.6。到第100天,一次性性伴侣关系的中位数R̂增加了一倍多,达到1.48,而随意性和主要性伴侣关系的R̂则下降,分别为0.46和0.29。 结论:由于能够对个体行为进行建模,机制网络特别适合研究性传播感染,其传播和控制通常受个体层面行为的影响。我们的结果为不同干预措施和关系类型在猴痘传播动力学中的作用提供了有价值的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/61a690a558e7/nihpp-2505.05534v1-f0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/b78ea0feb183/nihpp-2505.05534v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/972cd56d269b/nihpp-2505.05534v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/40482264014a/nihpp-2505.05534v1-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/474a14ca2745/nihpp-2505.05534v1-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/a1055518fad7/nihpp-2505.05534v1-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/58e95c70440d/nihpp-2505.05534v1-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/ebf8af9618fc/nihpp-2505.05534v1-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/61a690a558e7/nihpp-2505.05534v1-f0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/b78ea0feb183/nihpp-2505.05534v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/972cd56d269b/nihpp-2505.05534v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/40482264014a/nihpp-2505.05534v1-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/474a14ca2745/nihpp-2505.05534v1-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/a1055518fad7/nihpp-2505.05534v1-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/58e95c70440d/nihpp-2505.05534v1-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/ebf8af9618fc/nihpp-2505.05534v1-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6728/12083702/61a690a558e7/nihpp-2505.05534v1-f0008.jpg

相似文献

[1]
Modeling the 2022 Mpox Outbreak with a Mechanistic Network Model.

ArXiv. 2025-5-8

[2]
Understanding the impact of HIV on mpox transmission in the MSM population: A mathematical modeling study.

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[3]
Transmission dynamics and effect of control measures on the 2022 outbreak of mpox among gay, bisexual, and other men who have sex with men in England: a mathematical modelling study.

Lancet Infect Dis. 2024-1

[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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本文引用的文献

[1]
A Review of Network Models for HIV Spread.

J Acquir Immune Defic Syndr. 2025-4-1

[2]
Estimating the relative importance of epidemiological and behavioural parameters for epidemic mpox transmission: a modelling study.

BMC Med. 2024-7-18

[3]
Incubation Period and Serial Interval of Mpox in 2022 Global Outbreak Compared with Historical Estimates.

Emerg Infect Dis. 2024-6

[4]
Nowcasting and forecasting the 2022 U.S. mpox outbreak: Support for public health decision making and lessons learned.

Epidemics. 2024-6

[5]
Modelling the impact of vaccination and sexual behaviour adaptations on mpox cases in the USA during the 2022 outbreak.

Sex Transm Infect. 2024-2-19

[6]
Transmission dynamics and effect of control measures on the 2022 outbreak of mpox among gay, bisexual, and other men who have sex with men in England: a mathematical modelling study.

Lancet Infect Dis. 2024-1

[7]
CROI 2023: Epidemiology, Diagnosis, and Management of MPox.

Top Antivir Med. 2023-5

[8]
Monkeypox: a review of epidemiological modelling studies and how modelling has led to mechanistic insight.

Epidemiol Infect. 2023-5-23

[9]
Estimated Effectiveness of JYNNEOS Vaccine in Preventing Mpox: A Multijurisdictional Case-Control Study - United States, August 19, 2022-March 31, 2023.

MMWR Morb Mortal Wkly Rep. 2023-5-19

[10]
Vaccine Effectiveness of JYNNEOS against Mpox Disease in the United States.

N Engl J Med. 2023-6-29

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