Publication | Open Access
<b>amei</b>: An<i>R</i>Package for the Adaptive Management of Epidemiological Interventions
158
Citations
21
References
2010
Year
Bayesian Decision TheoryEpidemiological DynamicComputational EpidemiologyFlexible Statistical FrameworkInfectious Disease ModellingPreventive MedicineUncertainty QuantificationClinical EpidemiologyBayesian MethodsPublic HealthEpidemiological PrincipleStatisticsGeneral EpidemiologyInfectious Disease EpidemiologyEpidemiological OutcomeDisease PreventionIntervention StrategiesEpidemiologyVaccinationAdaptive ManagementBayesian StatisticsEpidemic IntelligenceEmerging Infectious DiseasesUnderlying Disease ParametersBayesian Posterior InferenceStatistical InferenceMedicine
The <b>amei</b> package for <b>R</b> is a tool that provides a flexible statistical framework for generating optimal epidemiological interventions that are designed to minimize the total expected cost of an emerging epidemic. Uncertainty regarding the underlying disease parameters is propagated through to the decision process via Bayesian posterior inference. The strategies produced through this framework are adaptive: vaccination schedules are iteratively adjusted to reflect the anticipated trajectory of the epidemic given the current population state and updated parameter estimates. This document briefly covers the background and methodology underpinning the implementation provided by the package and contains extensive examples showing the functions and methods in action.
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