2020
Tracking and predicting U.S. influenza activity with a real-time surveillance network
Leuba SI, Yaesoubi R, Antillon M, Cohen T, Zimmer C. Tracking and predicting U.S. influenza activity with a real-time surveillance network. PLOS Computational Biology 2020, 16: e1008180. PMID: 33137088, PMCID: PMC7707518, DOI: 10.1371/journal.pcbi.1008180.Peer-Reviewed Original ResearchConceptsInfluenza test resultsInfluenza activityU.S. influenza activityPhysician visitsInfluenza trendsInfluenza-like illness activityNational surveillance networkSurveillance networkInfluenza seasonCurrent burdenU.S. CentersIllness activityDisease controlUnited StatesLinear logistic modelVisitsLogistic modelValid estimatesProportion
2017
A Likelihood Approach for Real-Time Calibration of Stochastic Compartmental Epidemic Models
Zimmer C, Yaesoubi R, Cohen T. A Likelihood Approach for Real-Time Calibration of Stochastic Compartmental Epidemic Models. PLOS Computational Biology 2017, 13: e1005257. PMID: 28095403, PMCID: PMC5240920, DOI: 10.1371/journal.pcbi.1005257.Peer-Reviewed Original ResearchConceptsParameter estimationStochastic modelLinear noise approximationStochastic transmission-dynamic modelEnsemble Kalman filter methodReal-time parameter estimationKey epidemic parametersParticle filtering methodInfectious individualsStochastic systemsCompartmental epidemic modelLikelihood approximationMultiple shootingNoise approximationBenchmark methodsEpidemic modelPoisson observationsKalman filter methodUnobserved numberAccurate estimatesEpidemic parametersLikelihood approachFiltering methodDynamic modelApproximation