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Real-time Outbreak And Disease Surveillance
Real-time outbreak and disease surveillance system (RODS) is a syndromic surveillance system developed by the University of Pittsburgh, Department of Biomedical Informatics. It is "prototype developed at the University of Pittsburgh where real-time clinical data from emergency departments within a geographic region can be integrated to provide an instantaneous picture of symptom patterns and early detection of epidemic events."''Public Health-Related Activities'' at thUS HHS government website Accessed December 2, 2010. RODS uses a combination of various monitoring tools. # The first tool is a moving average with a 120-day sliding phase-I-window. # The second tool is a nonstandard combination of CUSUM and EWMA, where an EWMA is used to predict next-day counts, and a CuSum monitors the residuals from these predictions. # The third monitoring tool in RODS is a recursive least squares (RLS) algorithm, which fits an autoregressive model to the counts and updates estimates continuous ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Syndromic Surveillance
Public health surveillance (also epidemiological surveillance, clinical surveillance or syndromic surveillance) is, according to the World Health Organization (WHO), "the continuous, systematic collection, analysis and interpretation of health-related data needed for the planning, implementation, and evaluation of public health practice."Public health surveillance (accessed January 14, 2016). Public health surveillance may be used to track emerging health-related issues at an early stage and find active solutions in a timely manner. Surveillance systems are generally called upon to provide information regarding when and where h ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Prediction Error
In statistics the mean squared prediction error (MSPE), also known as mean squared error of the predictions, of a smoothing, curve fitting, or regression procedure is the expected value of the squared prediction errors (PE), the square difference between the fitted values implied by the predictive function \widehat and the values of the (unobservable) true value ''g''. It is an inverse measure of the ''explanatory power'' of \widehat, and can be used in the process of cross-validation of an estimated model. Knowledge of ''g'' would be required in order to calculate the MSPE exactly; in practice, MSPE is estimated. Formulation If the smoothing or fitting procedure has projection matrix (i.e., hat matrix) ''L'', which maps the observed values vector y to predicted values vector \hat=Ly, then PE and MSPE are formulated as: :\operatorname=g(x_i)-\widehat(x_i), :\operatorname=\operatorname\left operatorname_i^2\right\sum_^n \operatorname_i^2/n. The MSPE can be decomposed into two ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Medical Statistics
Medical statistics (also health statistics) deals with applications of statistics to medicine and the health sciences, including epidemiology, public health, forensic medicine, and clinical research. Medical statistics has been a recognized branch of statistics in the United Kingdom for more than 40 years, but the term has not come into general use in North America, where the wider term 'biostatistics' is more commonly used.Dodge, Y. (2003) ''The Oxford Dictionary of Statistical Terms'', OUP. However, "biostatistics" more commonly connotes all applications of statistics to biology. Medical statistics is a subdiscipline of statistics. It is the science of summarizing, collecting, presenting and interpreting data in medical practice, and using them to estimate the magnitude of associations and test hypotheses. It has a central role in medical investigations. It not only provides a way of organizing information on a wider and more formal basis than relying on the exchange of anecdot ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Epidemics
An epidemic (from Ancient Greek, Greek ἐπί ''epi'' "upon or above" and δῆμος ''demos'' "people") is the rapid spread of disease to a large number of Host (biology), hosts in a given population within a short period of time. For example, in meningococcal infections, an attack rate in excess of 15 cases per 100,000 people for two consecutive weeks is considered an epidemic. Epidemics of infectious disease are generally caused by several factors including a change in the ecology of the host population (e.g., increased stress or increase in the density of a vector species), a genetic change in the pathogen reservoir or the introduction of an emerging pathogen to a host population (by movement of pathogen or host). Generally, an epidemic occurs when host Immunity (medicine), immunity to either an established pathogen or newly emerging novel pathogen is suddenly reduced below that found in the Endemic (epidemiology), endemic equilibrium and the transmission threshold is excee ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Public Health
Public health is "the science and art of preventing disease, prolonging life and promoting health through the organized efforts and informed choices of society, organizations, public and private, communities and individuals". Analyzing the determinants of health of a population and the threats it faces is the basis for public health. The ''public'' can be as small as a handful of people or as large as a village or an entire city; in the case of a pandemic it may encompass several continents. The concept of ''health'' takes into account physical, psychological, and Well-being, social well-being, among other factors.What is the WHO definition of health? from the Preamble to the Constitution of WHO as adopted by the Internationa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Haar Wavelet
In mathematics, the Haar wavelet is a sequence of rescaled "square-shaped" functions which together form a wavelet family or basis. Wavelet analysis is similar to Fourier analysis in that it allows a target function over an interval to be represented in terms of an orthonormal basis. The Haar sequence is now recognised as the first known wavelet basis and is extensively used as a teaching example. The Haar sequence was proposed in 1909 by Alfréd Haar. Haar used these functions to give an example of an orthonormal system for the space of square-integrable functions on the unit interval , 1 The study of wavelets, and even the term "wavelet", did not come until much later. As a special case of the Daubechies wavelet, the Haar wavelet is also known as Db1. The Haar wavelet is also the simplest possible wavelet. The technical disadvantage of the Haar wavelet is that it is not continuous, and therefore not differentiable. This property can, however, be an advantage ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Wavelet
A wavelet is a wave-like oscillation with an amplitude that begins at zero, increases or decreases, and then returns to zero one or more times. Wavelets are termed a "brief oscillation". A taxonomy of wavelets has been established, based on the number and direction of its pulses. Wavelets are imbued with specific properties that make them useful for signal processing. For example, a wavelet could be created to have a frequency of middle C and a short duration of roughly one tenth of a second. If this wavelet were to be convolved with a signal created from the recording of a melody, then the resulting signal would be useful for determining when the middle C note appeared in the song. Mathematically, a wavelet correlates with a signal if a portion of the signal is similar. Correlation is at the core of many practical wavelet applications. As a mathematical tool, wavelets can be used to extract information from many kinds of data, including audio signals and images. Sets of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Standard Deviations
In statistics, the standard deviation is a measure of the amount of variation of the values of a variable about its mean. A low standard deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range. The standard deviation is commonly used in the determination of what constitutes an outlier and what does not. Standard deviation may be abbreviated SD or std dev, and is most commonly represented in mathematical texts and equations by the lowercase Greek letter σ (sigma), for the population standard deviation, or the Latin letter '' s'', for the sample standard deviation. The standard deviation of a random variable, sample, statistical population, data set, or probability distribution is the square root of its variance. (For a finite population, variance is the average of the squared deviations from the mean.) A useful property of the sta ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Autoregressive Model
In statistics, econometrics, and signal processing, an autoregressive (AR) model is a representation of a type of random process; as such, it can be used to describe certain time-varying processes in nature, economics, behavior, etc. The autoregressive model specifies that the output variable depends linearly on its own previous values and on a stochastic term (an imperfectly predictable term); thus the model is in the form of a stochastic difference equation (or recurrence relation) which should not be confused with a differential equation. Together with the moving-average (MA) model, it is a special case and key component of the more general autoregressive–moving-average (ARMA) and autoregressive integrated moving average (ARIMA) models of time series, which have a more complicated stochastic structure; it is also a special case of the vector autoregressive model (VAR), which consists of a system of more than one interlocking stochastic difference equation in more than one e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
University Of Pittsburgh
The University of Pittsburgh (Pitt) is a Commonwealth System of Higher Education, state-related research university in Pittsburgh, Pennsylvania, United States. The university is composed of seventeen undergraduate and graduate schools and colleges at its Urban university, urban Pittsburgh campus, home to the university's central administration and around 28,000 undergraduate and graduate students. The 132-acre Pittsburgh campus includes various historic buildings that are part of the Schenley Farms Historic District, most notably its 42-story Gothic Revival architecture, Gothic revival centerpiece, the Cathedral of Learning. Pitt is a member of the Association of American Universities and is Carnegie Classification of Institutions of Higher Education, classified among "R1: Doctoral Universities – Very high research activity". Pitt traces its roots to the Pittsburgh Academy founded by Hugh Henry Brackenridge in 1787. While the city was still on the History of Pittsburgh#Gatewa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recursive Least Squares
Recursive least squares (RLS) is an adaptive filter algorithm that recursively finds the coefficients that minimize a Weighted least squares, weighted linear least squares Loss function, cost function relating to the input signals. This approach is in contrast to other algorithms such as the least mean squares (LMS) that aim to reduce the mean square error. In the derivation of the RLS, the input signals are considered deterministic system (mathematics), deterministic, while for the LMS and similar algorithms they are considered stochastic. Compared to most of its competitors, the RLS exhibits extremely fast convergence. However, this benefit comes at the cost of high computational complexity. Motivation RLS was discovered by Carl Friedrich Gauss, Gauss but lay unused or ignored until 1950 when Plackett rediscovered the original work of Gauss from 1821. In general, the RLS can be used to solve any problem that can be solved by adaptive filters. For example, suppose that a signal d( ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
EWMA
In statistics, a moving average (rolling average or running average or moving mean or rolling mean) is a calculation to analyze data points by creating a series of averages of different selections of the full data set. Variations include: simple, cumulative, or weighted forms. Mathematically, a moving average is a type of convolution. Thus in signal processing it is viewed as a low-pass finite impulse response filter. Because the boxcar function outlines its filter coefficients, it is called a boxcar filter. It is sometimes followed by downsampling. Given a series of numbers and a fixed subset size, the first element of the moving average is obtained by taking the average of the initial fixed subset of the number series. Then the subset is modified by "shifting forward"; that is, excluding the first number of the series and including the next value in the series. A moving average is commonly used with time series data to smooth out short-term fluctuations and highlight longer- ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
