Online system of outbreak detection algorithms

With the aim of timely identification of all types of single-source and progressive epidemics

The key features of obdetector web-app are as follows:

  • • Introduction of an accepted classification for detecting changes in healthcare system data based
    on trends and levels of occurrence.
    • Implementation of various aberration detection algorithms.
    • Ability to modify parameters related to each algorithm based on data features or research
    objectives.
    • Facilitating the selection of aberration detection algorithms from an extensive list of existing
    algorithms.
    • Immediate access to results obtained from applying various algorithms after loading healthcare
    system data.
    • Providing outputs with a consistent structure for comparing the performance of outbreak
    detection algorithms.
    • Continuous monitoring of known diseases/syndromes under the healthcare system.
    • Facilitating the implementation of precautionary measures through early detection to limit the
    impact of disease outbreaks

Algorithm usage guide

The purpose of the identification system

A process for collecting, managing, analyzing, interpreting and reporting reliable information about community patients,، Used, care It is called; In fact, care is a continuous process of collecting health data in order to monitor the health status of communities and provide or revise the required services. Disease care systems have a special place in the health system, and in other words, they are considered the eyes and ears of the health system.

Algorithms

Obdetector.ir utilizes the Farrington and Farrington Flexible algorithms, which are based on the
family of generalized linear models. It also employs ARIMA time series, cumulative sum control
chart (CUSUM), early aberration reporting system (EARS), and exponentially weighted moving
average (EWMA) algorithms. For each algorithm, two sections are provided: an “Algorithm
Introduction” section briefly explaining each method, and an “Algorithm User Guide” section
defining the parameters of each algorithm. The design of data input panels, parameter settings, and
relevant computations for each algorithm are implemented using the R software.

Selection and guidance of algorithms