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On estimation the relative risk of small area and visualization spatio-temporal map

Disease mapping is a method used to descript the geographical variation in risk (heterogeneity of risk) and to provide the potential reason (factors or confounders) to explain the distribution. Possibly the most famous uses of disease mapping in epidemiology were the studies by John Snow of the cholera epidemics in London. Accurate estimation relative risk of small areas such as mortality and morbidity, by different age, ethnic group, interval and regions, is important for government agencies to identify hazards and mitigate disease burden.

June 18, 2019

Visualization the dynamic interactive maps for results of spatio-temporal scanning

Scan statistics is one of the most widely used method for detecting and locating the clusters of disease or health-related events through the space-time dimension. Although the Specific software of SatScan is available for free and easier to use graphical user interface (GUI) interface, the click way and the resulting text format have became obstacles in biosurveillance since automated or reproduction operation and the fast communicate information tool appeared.

January 25, 2018

Modeling spatial and temporal variability by Bayesian multilevel model

The early detection of outbreaks of diseases is one of the most challenging objectives of epidemiological surveillance systems. In order to achieve this goal, the primary foundation is using those big surveillance data for understanding and controlling the spatiotemporal variability of disease through populations. Typically, public health’s surveillance system would generate data with the big data characteristics of high volume, velocity, and variety.

July 16, 2017

Spatial Clustering of ILI in Yunnan Province, China, Based on a Geographical Information System

Influenza is a highly contagious, acute respiratory disease that causes periodic seasonal epidemics and global pandemics[1]. Yunnan Province is characterized by poverty, multi-ethnic, and cross-border movement, which maybe be susceptible of influenza (Fig-1). Finding from spatial patter of ILI will promote to control and prevent the respiratory diseases epidemic

Objective

November 27, 2017

Modeling Spatial Heterogeneity with Excess Zeroes from School Absenteeism dSata

Absenteeism has been considered as a potential indicator for the early detection of infectious disease outbreaks in population, especially in primary schools. However, in practice this data are often characterized by an excess of zeros and spatial heterogeneity. In a project on integrated syndromic surveillance system (ISSC) in rural China, Random effect zero-inflated Poisson (RE-ZIP) model was applied to simultaneously quantify the spatial heterogeneity for “occurrence” and “intensity” on school absenteeism data.

Objective

November 22, 2017

Real-time Warning and Signal Verification for Infectious Disease Outbreaks using Syndromic Surveillance System in Rural Jiangxi Province, China

Despite the global emergence of syndromic surveillance systems and theories in recent years, the practical performance of this surveillance method under real circumstances had been rarely evaluated, especially in resource-limited areas. Since April 2012, a syndromic surveillance system named 'ISSC' has been established among health care facilities, pharmacies and primary schools in two rural counties (County A & B) of Jiangxi Province, China.

Objective

May 02, 2019

The Growth and Variation of Symptoms of Influenza-like Illness: An Application of the Linear Growth Curve Model in Syndromic Surveillance in Rural China

Symptoms of influenza-like illness (ILI) were reported daily by health workers via the integrated syndromic surveillance system in rural China (ISSC)(1).

Objective

To analyze the growth and variation of ILI reports using individual growth curve model.

May 02, 2019

Applying Zero-inflated Mixed Model to School Absenteeism Surveillance in Rural China

Absenteeism has great advantages in promoting the early detection of epidemics1. Since August 2011, an integrated syndromic surveillance project (ISSC) has been implemented in China2. Distribution of the absenteeism generally are asymmetry, zero inflation, truncation and non-independence3. For handling these encumbrances, we should apply the Zero-inflated Mixed Model (ZIMM).

Objective

January 24, 2018

Use of Control Bar Matrix for Outbreak Detection in Syndromic Surveillance System

Aberration detection methods are essential for analyzing and interpreting large quantity of nonspecific real-time data collected in syndromic surveillance system. However, the challenge lies in distinguishing true outbreak signals from a large amount of false alarm (1). The joint use of surveillance algorithms might be helpful to guide the decision making towards uncertain warning signals.

Objective

To develop and test the method of incorporating different control bars for outbreak detection in syndromic surveillance system

July 06, 2018

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Email: syndromic@cste.org

 

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