Bosmana fem: Bosmana fem moved page Analysis of Surveillance Data to Category:Analysis of Surveillance Data

2023-03-22T20:42:01Z

Bosmana fem moved page Analysis of Surveillance Data to Category:Analysis of Surveillance Data

← Older revision	Revision as of 20:42, 22 March 2023
(No difference)

Bosmana fem at 20:37, 22 March 2023

2023-03-22T20:37:20Z

← Older revision		Revision as of 20:37, 22 March 2023
Line 15:		Line 15:
	* Patty Kostkova		* Patty Kostkova
	* Vladimir Prikazsky		* Vladimir Prikazsky


			[[Category:Establishing a Surveillance System]]

Bosmana fem: Created page with "Principles of surveillance emphasize, among others, continuous and systematic processes with the need to collect data from different sources and regular or ad hoc outputs. The..."

2022-12-18T21:40:24Z

Created page with "Principles of surveillance emphasize, among others, continuous and systematic processes with the need to collect data from different sources and regular or ad hoc outputs. The..."

New page

Principles of surveillance emphasize, among others, continuous and systematic processes with the need to collect data from different sources and regular or ad hoc outputs. The validity and accuracy of data are usually ascertained during the collection phase. Data quality has different aspects related to processes generating and delivering the data. Descriptive analysis can show irregularities and deviations from the usual pattern, which should trigger first-quality questions. To analyze surveillance data consists of checking its [[Quality checking|quality]] and performing descriptive epidemiology - to organize data by [[Analysis by time characteristics|time]], [[Analysis by place characteristics|place]], and [[Analysis by person characteristics|person]] - to understand who is ill, where, and when, to detect abnormal health events such as clustering or change in trends requiring investigation and public health action. Analysis of time-series data includes detecting unusual occurrences in relation to [[Methods for setting thresholds in time series analysis|threshold values]]. Long-term trends may reflect the success of preventive or repressive measures or future needs in public health action. For these purposes, [[Smoothing techniques|smoothing techniques]] may clean the data from cyclicities and interfering factors. Spatial data distribution is related to the natural occurrence of people with similar population characteristics and environmental factors, and their correlation with disease occurrence can be evaluated. Death, disease, disability, and any individual health event may be analyzed regularly or on demand in the "response" phase.

==Credits==
===FEM Editors 2007===
* Arnold Bosman
* Denis Coulombier
===Original Authors===
* Christophe Paquet
* Arnold Tarantola
* Philippe Quenel
* Nada Ghosn
===FEM Contributors===
* Denis Coulombier
* Lisa Lazareck
* Patty Kostkova
* Vladimir Prikazsky

Category:Analysis of Surveillance Data - Revision history

Bosmana fem: Bosmana fem moved page Analysis of Surveillance Data to Category:Analysis of Surveillance Data

Bosmana fem at 20:37, 22 March 2023

Bosmana fem: Created page with "Principles of surveillance emphasize, among others, continuous and systematic processes with the need to collect data from different sources and regular or ad hoc outputs. The..."