Opportunities for HIV PrEP engagement using interconnected social and molecular network data through the characterization of high-risk Neisseria gonorrhoeae clusters
通过高风险淋病奈瑟菌群的特征分析,利用相互关联的社会和分子网络数据进行艾滋病毒接触预防的机会
基本信息
- 批准号:10611506
- 负责人:
- 金额:$ 19.75万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-04-19 至 2025-03-31
- 项目状态:未结题
- 来源:
- 关键词:AIDS preventionAdherenceAgeAreaBehavioralCaliforniaCharacteristicsChlamydiaClinicClinicalClinical DataCollectionCommunitiesCountyDataData SourcesDiagnosisDiseaseEligibility DeterminationEpidemiologyFrequenciesFutureGeneticGoalsHIVHIV InfectionsHIV SeronegativityHIV SeropositivityIndividualInfectionInfectious AgentInterdisciplinary StudyInterventionLinkMetadataMethodologyMethodsMolecularNamesNeisseria gonorrhoeaeOrganismParticipantPatientsPersonsPopulations at RiskPreventionPrevention strategyProphylactic treatmentPublic HealthResearchResearch PersonnelResearch PriorityResolutionResourcesRiskRisk AssessmentSamplingServicesSexual HealthSexual TransmissionSexually Transmitted DiseasesSocial NetworkStrategic PlanningStructureSyphilis SerodiagnosisTechnologyTest ResultTestingUnited States National Institutes of HealthUniversitiesWorkcandidate identificationepidemic responseepidemiology studygenome sequencinggenomic datahigh riskimprovedinnovationinsightmen who have sex with mennovelpre-exposure prophylaxispreventpreventive interventionprogramspublic health interventionsocialsocial contactsocial structuretooltransmission processwhole genome
项目摘要
Project Summary/Abstract
Sexual and social networks impact the spread of HIV and STIs and can be used as a tool for public health
prevention efforts. The impact of HIV prevention strategies, such as PrEP, and prevention interventions for
STIs depend on the characteristics of these sexual and social networks. Within sexual and social networks,
people are linked by their sexual or social ties to form clusters. Genomic data from infectious organisms can be
used to construct transmission networks which, in the case of sexually transmitted organisms, can provide
information about the sexual network. Neisseria gonorrhoeae (NG) infection is one of the most common STIs
in the world, and a potential driver of HIV acquisition. NG transmission may represent a more recent contact
than the HIV transmission network. NG sequence data have been successfully used to study transmission and
can be used to reveal insights into sexual networks.
In Aim 1, we will characterize NG transmission networks using whole genome sequencing data from the
bacterial isolates which will be merged with detailed patient metadata and social network data from a sample of
participants accessing STI testing at the largest San Diego Public Health clinic. We will construct combined
social and transmission networks using named social contacts and NG genetic distances and collection dates
of NG isolates. We will then assess bridging of HIV positive and HIV negative groups in the social-molecular
network to evaluate HIV transmission risk. In Aim 2, we will identify correlates of being in a cluster with at least
one person living with HIV and will assess risk of HIV acquisition to identify candidates for PrEP. By combining
connections from each network to create a more complete picture of contact, we can identify those who may
be at risk for both STIs and HIV. These results will provide evidence for public health researchers and
practitioners on how best to prioritize HIV PrEP and other services.
The proposed study will be carried out as an extension of work that the PI conducted as part of a K01 project
at the University of California San Diego, which aimed to combine HIV transmission network data and NG
transmission network data. That project was conducted in a different clinical setting as the present proposal,
however the methodology developed and piloted through that project provides a basis for the current proposal,
which now also includes social networks. The present proposed study will be the first to simultaneously
examine NG transmission networks combined with social networks. The results from this study will contribute
to improved strategies to curb the spread of HIV and STIs.
项目总结/摘要
性网络和社交网络影响艾滋病毒和性传播感染的传播,可用作公共卫生工具
预防工作。艾滋病毒预防战略(如PrEP)和预防干预措施的影响
性传播感染取决于这些性和社交网络的特点。在性和社交网络中,
人们通过他们的性或社会联系而形成集群。来自传染性生物体的基因组数据可以
用于构建传播网络,在性传播生物体的情况下,
关于性网络的信息淋球菌感染是最常见的性传播感染之一
也是艾滋病毒感染的潜在驱动因素。NG传输可能代表最近的接触
艾滋病传播网络。NG序列数据已成功地用于研究传输,
可以用来揭示性关系网。
在目标1中,我们将使用来自美国的全基因组测序数据来表征NG传输网络。
细菌分离株,将与来自以下样本的详细患者元数据和社交网络数据合并:
参与者在圣地亚哥最大的公共卫生诊所接受性病检测。我们将结合
使用命名的社会联系人和NG遗传距离和收集日期的社会和传播网络
NG隔离物。然后,我们将评估社会分子中HIV阳性和HIV阴性群体的桥接,
评估艾滋病毒传播风险。在目标2中,我们将确定在一个集群中的相关性,
一个人感染艾滋病毒,并将评估艾滋病毒感染的风险,以确定候选人的准备。
从每个网络的连接,以创建一个更完整的图片的联系,我们可以确定那些谁可能
有感染性病和艾滋病的风险。这些结果将为公共卫生研究人员提供证据,
如何最好地优先考虑艾滋病毒PrEP和其他服务。
拟定研究将作为主要研究者作为K 01项目一部分开展的工作的延伸
该研究旨在联合收割机艾滋病毒传播网络数据和NG
传输网络数据。该项目是在与本提案不同的临床环境中进行的,
然而,通过该项目制定和试行的方法为目前的提议提供了基础,
其现在还包括社交网络。目前拟议的研究将是第一个同时
结合社交网络研究NG传输网络。这项研究的结果将有助于
改进战略,遏制艾滋病毒和性传播感染的蔓延。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Britt Skaathun其他文献
Britt Skaathun的其他文献
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{{ truncateString('Britt Skaathun', 18)}}的其他基金
Opportunities for HIV PrEP engagement using interconnected social and molecular network data through the characterization of high-risk Neisseria gonorrhoeae clusters
通过高风险淋病奈瑟菌群的特征分析,利用相互关联的社会和分子网络数据进行艾滋病毒接触预防的机会
- 批准号:
10403393 - 财政年份:2022
- 资助金额:
$ 19.75万 - 项目类别:
Social networks and STIs as an indicator of potential HIV transmission and acquisition among PWID
社交网络和性传播感染是吸毒者中潜在艾滋病毒传播和感染的指标
- 批准号:
10548693 - 财政年份:2022
- 资助金额:
$ 19.75万 - 项目类别:
Social networks and STIs as an indicator of potential HIV transmission and acquisition among PWID
社交网络和性传播感染是吸毒者中潜在艾滋病毒传播和感染的指标
- 批准号:
10682480 - 财政年份:2022
- 资助金额:
$ 19.75万 - 项目类别:
Leveraging Networks, Epidemiology, and Epidemic Modeling: Creative Approaches for HIV Elimination
利用网络、流行病学和流行病模型:消除艾滋病毒的创造性方法
- 批准号:
10673665 - 财政年份:2019
- 资助金额:
$ 19.75万 - 项目类别:
Leveraging Networks, Epidemiology, and Epidemic Modeling: Creative Approaches for HIV Elimination
利用网络、流行病学和流行病模型:消除艾滋病毒的创造性方法
- 批准号:
10213684 - 财政年份:2019
- 资助金额:
$ 19.75万 - 项目类别:
Leveraging Networks, Epidemiology, and Epidemic Modeling: Creative Approaches for HIV Elimination
利用网络、流行病学和流行病模型:消除艾滋病毒的创造性方法
- 批准号:
10450822 - 财政年份:2019
- 资助金额:
$ 19.75万 - 项目类别:
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