996 resultados para Andersson, Johan Gunnar (1874-1960) -- Portraits


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Référence bibliographique : Rol, 60001

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Original image (attached to acidic board) was photographed and negative created by Lance Burghardt. Photographer of original print unknown

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--A further account of the province of Pennsylvania, by William Penn, 1685.--Letters of Doctor Nicholas More, and others, 1686.--A short description of Pennsylvania, by Richard Frame, 1692.--An historical and geographical account of Pennsylvania and West-New-Jersey, by Gabriel Thomas, 1698.--Circumstantial geographical description of Pennsylvania, by Francis Daniel Pastorius, 1700.--Letter of John Jones, 1725.

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Référence bibliographique : Rol, 58751

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Référence bibliographique : Rol, 58871

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Référence bibliographique : Rol, 59569

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In this work we propose the adoption of a statistical framework used in the evaluation of forensic evidence as a tool for evaluating and presenting circumstantial "evidence" of a disease outbreak from syndromic surveillance. The basic idea is to exploit the predicted distributions of reported cases to calculate the ratio of the likelihood of observing n cases given an ongoing outbreak over the likelihood of observing n cases given no outbreak. The likelihood ratio defines the Value of Evidence (V). Using Bayes' rule, the prior odds for an ongoing outbreak are multiplied by V to obtain the posterior odds. This approach was applied to time series on the number of horses showing clinical respiratory symptoms or neurological symptoms. The separation between prior beliefs about the probability of an outbreak and the strength of evidence from syndromic surveillance offers a transparent reasoning process suitable for supporting decision makers. The value of evidence can be translated into a verbal statement, as often done in forensics or used for the production of risk maps. Furthermore, a Bayesian approach offers seamless integration of data from syndromic surveillance with results from predictive modeling and with information from other sources such as disease introduction risk assessments.