Computational discovery of effective hepatitis C intervention strategies
Computational discovery of effective hepatitis C intervention strategies
批准号:
9383459
负责人:
Basmattee Boodram
金额:
$42.33万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-08-15 至 2022-07-31
关键词:
AddressAdherenceAntiviral AgentsBehavioralCaringCharacteristicsChicagoChronicClinical TrialsCommunitiesComplexComputer SimulationCost Effectiveness AnalysisCounselingDataData SetDevelopmentDevelopment PlansDiagnosisDirect CostsDisease ProgressionDrug usageEventExposure toFundingGeneral PopulationGeographic FactorGeographic LocationsGeographyGoalsGroupingHarm ReductionHealthHealth ServicesHepatitis CHepatitis C IncidenceHepatitis C PrevalenceHepatitis C TransmissionIllinoisImmune System DiseasesIncidenceIndividualInfectionInjecting drug userInjection of therapeutic agentInterventionKineticsLeadLife StyleLiver diseasesMeta-AnalysisMethodologyMethodsModelingNeedle-Exchange ProgramsNetwork-basedOpioid RotationOralPhasePolicy DevelopmentsPolicy MakerPopulationPrevalencePreventionPrisonsPublic HealthReportingResearchResearch PersonnelResourcesRiskRisk BehaviorsScienceSocial InteractionStrategic PlanningSystemTimeUnited States Dept. of Health and Human ServicesViralViral hepatitisWorkWorld HealthWorld Health Organizationbasechronic liver diseasedesigneffective interventionepidemiologic dataepidemiological modelimprovedlarge scale simulationmethicillin resistant Staphylococcus aureusmodels and simulationmortalitypathogenpreventprognosticprogramsscale upsocialtransmission processvaccine trial
中文摘要
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英文摘要
7. PROJECT SUMMARY/ABSTRACT
Hepatitis C (HCV) is a leading cause of chronic liver disease and mortality worldwide. The World Health
Organization (WHO) has recently recognized the need to prevent and control HCV infection, and proposed that
HCV elimination is feasible by 2030 by reducing new chronic infections by 90% and HCV-related mortality by
65%. In the U.S., elimination strategies are urgently needed that focus on persons who inject drugs (PWID), the
group at most risk for acquiring and transmitting HCV infection. Despite the long-term availability of harm
reduction strategies such as syringe exchange programs (SEP), opioid substitution therapies (OSTs), and
behavioral counseling, HCV incidence in the U.S. is on the rise among PWID. The recent availability of all oral
direct-acting antivirals (DAAs) with high reported cure rates (e.g., >90%) that can prevent liver disease
progression and HCV transmission, combined with prevention and harm reduction strategies, make HCV
elimination an attainable goal. However, given considerable barriers (e.g., cost of DAAs, poor linkage to care
and adherence, possible reinfection, PWID lifestyle), it is essential for policy development and strategic planning
to understand the factors that would most effectively promote HCV elimination among PWID. Understanding the
dynamic and complex interplay of factors at the individual (e.g., risk behaviors), social (e.g., injection networks),
structural (e.g., access to syringe exchange programs and opioid substitution therapies), and geographic (e.g.,
non-urban residence) levels is essential to improve understanding and development of HCV elimination
strategies. Current models cannot account for such dynamic and complex interactions. As such we propose to
develop a comprehensive, data-driven agent-based model for Hepatitis C Elimination in PWID (HepCEP) using
the Chicago PWID population as a template and proof of concept that would enable policy makers to identify the
most effective intervention strategies for elimination of HCV by 2030 based on the aforementioned WHO's
proposed reduction estimates. The long term significance of these efforts would be to adapt the HepCEP
framework to (i) model HCV transmission in the general population of Chicago and in Illinois prisons, (ii) forecast
the spread of HCV in other U.S. urban and non-urban PWID populations (e.g., Albuquerque, NM), (iii) perform
cost-effectiveness analyses, and (iv) assist vaccine-trial sponsors in designing and evaluating clinical trials.
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Computational modeling for HCV vaccine trial design and optimal vaccine-based combination interventions
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批准号:10514625
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项目类别:
-
资助金额:$70.81万
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财政年份:2021
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负责人:Basmattee Boodram
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依托单位:
Computational modeling for HCV vaccine trial design and optimal vaccine-based combination interventions
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批准号:10367717
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项目类别:
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资助金额:$75.97万
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财政年份:2021
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负责人:Basmattee Boodram
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依托单位:
Contextual risk factors for hepatitis C among young persons who inject drugs
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批准号:10179349
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项目类别:
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资助金额:$52.6万
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财政年份:2017
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负责人:Basmattee Boodram
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依托单位:
Contextual risk factors for hepatitis C among young persons who inject drugs
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批准号:9926034
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项目类别:
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资助金额:$0.79万
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财政年份:2017
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负责人:Basmattee Boodram
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依托单位:
Computational discovery of effective hepatitis C intervention strategies
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批准号:10226066
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项目类别:
-
资助金额:$39.86万
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财政年份:2017
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负责人:Basmattee Boodram
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依托单位:
Case Management and Linkage to Care Among Persons Who Inject Drugs
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批准号:8511081
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项目类别:
-
资助金额:$14.79万
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财政年份:2012
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负责人:Basmattee Boodram
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依托单位:
Case Management and Linkage to Care Among Persons Who Inject Drugs
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批准号:8703331
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项目类别:
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资助金额:$15.18万
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财政年份:2012
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负责人:Basmattee Boodram
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依托单位:
海外基金