Deconvolution and reconstruction of immune histories to enhance infectious disease prevention and vaccination strategies and optimize surveillance efforts
Deconvolution and reconstruction of immune histories to enhance infectious disease prevention and vaccination strategies and optimize surveillance efforts
批准号:
10018944
负责人:
Michael J. Mina
金额:
$39.88万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-16 至 2024-08-31
关键词:
AgeAntibodiesAntibody RepertoireAppointmentBacteriaBiologyBirthBloodBlood donorClinicalClinical PathologyCollaborationsCommunicable DiseasesComputing MethodologiesCoupledCulicidaeDataData AnalysesDengueDetectionDevelopmentDisciplineDisease SurveillanceDoctor of PhilosophyEarly DiagnosisEducational process of instructingElderlyEpidemicEpidemiologyEpitopesExposure toFacultyFrequenciesFundingFutureGenderGeographyGoalsGrowthHealthHospitalsHumanImmuneImmunologicsImmunologyImprove AccessIndividualInfectionInterdisciplinary StudyInvestigationJournalsLaboratoriesLaboratory TechniciansLeadershipLinkLongevityLongitudinal cohortMaternal antibodyMathematicsMeaslesMeasurementMeasuresMedicalMentorsMethodsMolecular BiologyMolecular ComputationsNicaraguaOutputParasitesPathologyPhage DisplayPhysician ExecutivesPopulationPopulation SurveillancePositioning AttributePostdoctoral FellowPrevention MeasuresPrevention strategyPropertyPublic HealthPublic Health SchoolsPublicationsRecording of previous eventsReportingResearchResearch PersonnelResourcesRunningSalivaSamplingSeriesSerologicalSpecimenSpottingsStatistical ModelsStructureStudentsSystemTechnologyTimeTrainingTravelVaccinationVaccinesVascular blood supplyWagesWaterWomanWorkZIKAbaseclinically relevantco-infectioncomputerized toolscostenvironmental changeepidemiological modelexperiencegraduate studenthuman pathogenimprovedinfluenza virus vaccineinterdisciplinary approachlife historymathematical modelmedical schoolsmembermortalitymultidisciplinarynovelpathogenpathogen exposureprofessorprogramsreconstructionrecruitskillssuccesstenure tracktoolvaccination strategyvector mosquitovirtual
中文摘要
点击翻译按钮获取中文摘要
英文摘要
PROJECT SUMMARY
Infectious diseases remain among the greatest threats to human health. Novel epidemics occur with increasing
frequency as ease of travel facilitates spread, and environmental changes alter underlying dynamics in
unpredictable ways. At the same time, vaccines are increasingly controlling many major human pathogens. Yet,
the potential of these advances can only be fully realized with a means to accurately measure and quantify the
landscape of infectious diseases across many pathogens and scales, from the individual to the global population,
and encompassing interactions and potential unintended consequences across related or unrelated pathogens.
The overall objectives are to bridge novel developments in molecular biology and computational tools to
fundamentally improve infectious disease surveillance and research. Aim 1 will build on a previously reported
phage display system, and optimize it for infectious disease surveillance. PADERNS (Phage display for Antibody
repertoire Detection and profiling via pathogen Epitope RecognitioN for infectious disease and public health
Surveillance) will: enable serological surveillance for exposures to all human pathogens, including bacteria,
parasites and mosquitos vectors, simultaneously, from accessible samples, i.e. saliva and dried blood spots;
will discriminate exposures from closely related pathogens (i.e. Zika and Dengue) and estimate time since
infection or vaccination. Importantly, it will be optimized for use in low resource settings and at a fraction of the
cost of current technologies. Aim 2 will improve epidemic detection with development of Epi-TRACER (Epitope
based TRacking of Anonymous samples via Comprehensive Epitope Recogntion). Epi-TRACER will use
PADERNS repertoires from (1) to extract and construct epidemiologically powerful ‘virtual longitudinal cohorts’
from cross-sectional sample sets that contain ‘hidden’ serial samples (i.e. 80% of the US blood supply comes
from repeat donors). Because Epi-TRACER runs on PADERNS data, it will simultaneously enable reconstruction
of past, and early detection of current epidemics. Aim 3 will elucidate the life-histories of pathogen exposures
across ages (pre-birth to elderly), time, genders and geographies to: quantify in unprecedented detail pathogen
attack rates, heterologous effects of vaccines on off-target pathogens, and measure the longevity and waning of
antibodies, including maternally derived antibodies, to improving vaccination and control strategies.
These aims will be accomplished through a multi-disciplinary approach involving molecular biology and
phage-display systems, robust longitudinal sample curation through collaborations, and, crucially, careful
development of mathematical and statistical models to link the biology to individual and population level
inference. Once complete, the tools, methods and data will be available to public health agencies and infectious
disease researchers, opening the way to a step change in detection or control of existing and novel pathogens.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Deconvolution and reconstruction of immune histories to enhance infectious disease prevention and vaccination strategies and optimize surveillance efforts
-
批准号:9794872
-
项目类别:
-
资助金额:$39.88万
-
财政年份:2019
-
负责人:Michael J. Mina
-
依托单位:
海外基金