Network Models for Evaluating HIV-associated MDR TB transmission and control
Network Models for Evaluating HIV-associated MDR TB transmission and control
批准号:
8466080
负责人:
Jason Randolph Andrews
金额:
$5.0万
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-08-22 至 2014-01-31
关键词:
AIDS clinical trial groupAccountingAfricanAgeApplied ResearchChemoprophylaxisClinicalClinical TreatmentClinical TrialsCollaborationsCommunicable DiseasesCommunitiesCommunity HealthcareCost Effectiveness AnalysisCountryDataDatabasesDevelopmentDiseaseDoctor of MedicineDrug Resistant TuberculosisDrug resistanceDrug resistance in tuberculosisEngineeringEpidemicEpidemiologyEvaluationExtreme drug resistant tuberculosisFoundationsGeneral HospitalsGoalsHIVHealth PolicyHouseholdImpact evaluationIncidenceIncomeIndividualInfectionInterventionInvestigationK-Series Research Career ProgramsLifeLife ExpectancyMassachusettsMathematicsMeasuresMentored Research Scientist Development AwardMentorsMentorshipMeta-AnalysisMethodsModelingMorbidity - disease rateMulti-Drug ResistanceNIH Office of AIDS ResearchNational Institute of Allergy and Infectious DiseaseNatural HistoryOutcomePathway AnalysisPatientsPatternPharmaceutical PreparationsPoliciesPopulationPostdoctoral FellowPrevalencePreventionPrevention strategyPreventivePublic HealthPublic Health SchoolsRecurrenceRegimenResearchResearch PersonnelResearch TrainingResourcesRifampicin resistanceSchoolsSouth AfricaStructureSystemTestingTrainingTreatment ProtocolsTuberculosisUniversitiesWorkantiretroviral therapycareercase findingcostcost effectivenessdesignexperiencehigh riskimprovedinterestmathematical modelmembermortalitynetwork modelsprophylacticpublic health relevancerespiratoryscreeningsocialsuccesstransmission processtuberculosis drugstuberculosis treatment
中文摘要
描述(申请人提供):南非出现多药耐药(MDR)和广泛耐药(XDR)结核病疫情,有可能破坏在艾滋病毒抗逆转录病毒疗法(ART)推广方面取得的进展。尽管对耐多药或广泛耐药结核病患者家庭成员的接触调查具有实际吸引力,但这一战略在结核病高发地区控制耐药结核病方面的潜在好处尚不清楚。评估结核病控制的数学模型没有考虑到呼吸道传播中实际的接触结构,从而排除了对接触调查战略的评估。这个K01应用程序建议利用南非密切接触率的年龄结构数据来模拟结核病传播。利用这一框架,提出了以下具体目标:1)利用经验的社会接触数据,设计和建立艾滋病毒高流行环境下结核病自然病史和传播的网络模型;2)评估社会接触率和网络结构对结核病发病率预测的影响,以及加强病例发现和治疗成功的影响;3)预测结核病筛查的临床影响和成本效益,并为艾滋病毒高流行环境中耐多药和广泛耐药结核病患者的接触者提供预防性治疗。这项工作将为公共卫生政策以及开发耐多药/广泛耐药结核病化学预防的临床试验提供信息,这是NIAID耐多药和广泛耐药结核病研究议程的一个关键目标。候选人Jason Andrews,M.D.,S.M.,DTM&H是马萨诸塞州总医院传染病方面的博士后研究员,他将受益于在数学建模、网络分析和统计推理方面拥有广泛专业知识的研究人员的指导。这项研究将与开普敦大学Desmond Tutu艾滋病毒中心的研究人员合作进行,该中心拥有关于艾滋病毒和结核病自然病史和流行病学的广泛临床和社区数据。应聘者将通过在哈佛公共卫生学院和哈佛工程与应用科学学院应用数学系的课程工作,获得动态系统的数学建模、网络分析和统计推断方面的先进方法方面的专业知识。拟议的培训和研究经验将为独立调查员的职业生涯奠定基础。
英文摘要
DESCRIPTION (provided by applicant): The emergence of an epidemic of multidrug resistant (MDR) and extensively drug-resistant (XDR) TB in South Africa threatens to undermine the advances made in the antiretroviral therapy (ART) rollout for HIV. While contact investigations for household members of individuals with MDR or XDR TB holds practical appeal, the potential benefit of this strategy in the control of drug-resistant tuberculosis in a high TB prevalence setting is not known. Mathematical models evaluating the control of TB have not accounted for the realistic contact structure in respiratory transmission, precluding the evaluation of contact investigation strategies. This K01 application proposes to draw upon age-structured data on close contact rates from a South African in order to model tuberculosis transmission. Using this framework, the following specific aims are proposed: 1) To design and populate a network model of tuberculosis natural history and transmission and in a high HIV prevalence setting using empirical social contact data; 2)To evaluate the effect of social contact rates and network structure on the projections of tuberculosis incidence and on the impact of enhanced case-finding and treatment success; 3) To project the clinical impact and cost-effectiveness of tuberculosis screening and provision of preventive therapy for contacts of individuals with multidrug-resistant and extensively drug- resistant tuberculosis in a high HIV prevalence setting. This work will inform public health policy as well as clinical trials for development of chemoprophylaxis for MDR/XDR TB, which is a key aim of the NIAID Research Agenda for Multidrug-Resistant and Extensively Drug-Resistant Tuberculosis. The candidate, Jason Andrews, M.D., S.M.,DTM&H is a postdoctoral fellow in infectious diseases at Massachusetts General Hospital and will benefit from the mentorship of investigators with extensive expertise in mathematical modeling, network analysis, and statistical inference. This research will be conducted in collaboration with investigators at the Desmond Tutu HIV Centre at the University of Cape Town, where extensive clinical and community-based data on HIV and TB natural history and epidemiology are available. The Candidate will gain expertise in advanced methods for mathematical modeling, network analysis and statistical inference of dynamic systems through coursework at the Harvard School of Public Health and the Applied Mathematics Department at the Harvard School of Engineering and Applied Sciences. The proposed training and research experience will provide the foundation for a career as an independent investigator.
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会议论文
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依托单位:
海外基金