ABSTRACT
STUDY OBJECTIVES: To discover if continuous computerised collection of morbidity data through a medical practice based sentinel network can be used to monitor influenza-like illness (ILI) epidemics. To obtain rough estimates of influenza vaccine effectiveness. DESIGN: Continuous passive surveillance of ILI through a computerised network of voluntary sentinel general practitioners (SGPs) in France (Sentinelle system). SETTING: Five hundred SGPs practices. PARTICIPANTS: Since 1984, SGPs updated a database with information on eight communicable diseases including ILI, via videotext terminals. Each ILI case is defined by the association of a sudden fever of 39 degrees C or above, respiratory symptoms, and myalgias. An ILI epidemic is detected when the national weekly incidence rate exceeds a seasonal threshold for two successive weeks. MAIN RESULTS: An ILI epidemic was reported from November 1995 to January 1996. In total, 13,951 individual cases were reported by SGPs during the epidemic period. The size of the epidemic (number of patients consulting a GP) was estimated to be 2,370,000 subjects. Maps of the epidemic showed that all regions have reported a high level ILI activity. The attack rate was the highest in school age children (13.5/100) and decreased as the age rose. Nearly 6% of the reported ILI cases among adults and elderly were vaccinated. The flu vaccine effectiveness against ILI was estimated to be 66% (95% CI 73%, 92%), ranging between 83% (95% CI 73%, 92%) among the subjects aged 15 to 24 years old to 16% (95% CI -12%, 44%) among the subjects aged 75 years or older. CONCLUSIONS: The Sentinelle system demonstrated adequate sensitivity and timeliness regarding ILI epidemic. Moreover, results of the monitoring were made available on the internet to increase the dissemination of information. Also, estimates of influenza vaccine effectiveness have been easily obtained. Altogether, they represent key points for the control of crisis situation such as ILI epidemics or pandemics.
Subject(s)
Disease Outbreaks , Family Practice/statistics & numerical data , Influenza, Human/epidemiology , Sentinel Surveillance , Adolescent , Adult , Aged , Child , Child, Preschool , Computer Storage Devices/statistics & numerical data , Disease Outbreaks/prevention & control , Disease Outbreaks/statistics & numerical data , Female , France/epidemiology , Humans , Infant , Infant, Newborn , Influenza Vaccines/therapeutic use , Influenza, Human/prevention & control , Longitudinal Studies , Male , Middle AgedABSTRACT
A neuron can respond to periodic inhibitory input with a variety of complex behaviors, periodic and aperiodic. We present a succession of models to test hypotheses for mechanisms underlying complex behavior generation. Model comparison using non-linear dynamics techniques indicates that long-duration IPSP aftereffects and spiking behavior are necessary for most of the basic response properties, though not sufficient for some of their more subtle aspects.
Subject(s)
Biological Clocks/physiology , Neurons/physiology , Action Potentials , Animals , Astacoidea , Models, Biological , Nonlinear DynamicsABSTRACT
XNBC is a software package for simulating biological neural networks. Two neuron models are available, a leaky integrator model and an ion-conductance model. Inputs to the simulated neurons can be provided by experimental data stored in files, allowing the creation of 'hybrid' networks. Graphic tools are used to describe the modeled neurons as well as the network. Neuron and network parameters can be modified during the simulation, to mimic electrical stimulations and drugs action. The temporal evolution of the network and of selected neurons can be visualized. A point process, frequency or dynamic analysis of the simulator output can be performed. The successive stages of the creation of a hybrid network are explained.
Subject(s)
Computer Simulation , Neural Networks, Computer , Software , Computer GraphicsSubject(s)
Communicable Disease Control , Computer Communication Networks , Confidentiality , France , HumansABSTRACT
Return of information is one of the main goals of any public health information system. About 25,000 maps and 10,000 graphs may be obtained from the time-series collected in the database of the French Communicable Diseases Network (FCDN). Furthermore, this huge epidemiological atlas is updated each week. What is the optimal way of returning such information? This report discloses the strategies used for enhancing the access facilities to the FCDN database for any users, particularly those without specific training in epidemiology or database query language. The technical options implemented in the SentiWeb server (http:/(/)www.b3e.jussieu.fr) are discussed.