About software

The process used for collecting, managing, analyzing, interpreting, and reporting reliable
information about community patients is referred to as surveillance. Essentially, surveillance is a
continuous process of gathering health data to monitor the health status of communities and
facilitate the provision or revision of necessary services. Disease surveillance systems hold a
special position within the healthcare system. The successful performance of surveillance systems
depends on their ability to timely identify public health threats, such as outbreaks, as this enables
rapid assessment for prevention and containment, making it crucial for implementing control
measures. In recent years, the surveillance system has experienced significant and remarkable
growth in pursuit of this objective, driven by two factors: new concerns regarding large-scale
bioterrorism attacks and increased public awareness of emerging and re-emerging infections.
These advancements have led to the introduction of syndromic surveillance systems, the expansion
of databases, and the development of automated outbreak detection systems to process data on a
vast number of infections.
obdetector.ir is a web application focused on outbreak detection algorithms. By implementing
various types of outbreak detection algorithms on healthcare system data, it assists in timely
identification of different epidemics. This system can generate alerts based on the input of

healthcare professionals, allowing them to load various types of data, such as clinical and non-
clinical data, syndromes, or diseases, without the need for coding or advanced statistical

knowledge. Students working in the field of aberration detection algorithms and healthcare
systems can benefit from this web application. Professors and epidemiology groups can use this
system to practically teach students about healthcare systems and outbreak detection algorithms.
Different types of healthcare system data, including low, moderate, and high-count data, can be
uploaded to this system, where various algorithms can be applied, and input parameters and
arguments can be modified to obtain different results. The algorithms available in this system are
temporal-based algorithms, allowing retrospective data monitoring. The obdetector web-app is
under development, and more diverse algorithms will be added to this system in the future.

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

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.

Developers and funders

This system was developed by Dr. Bushra Zareie, a Ph.D. in epidemiology, in collaboration with
epidemiology and statistics professors at Hamedan University of Medical Sciences.

Who can use this web-app?

Public Health authorities Surveillance staff
Stakeholders
Students working in the field of surveillance
Professors engaged in Surveillance system and outbreak detection algorithms

How can you contact us?

To access the algorithm execution section of this web application, kindly reach out to us, and we
will promptly enable your username and password. You can contact us via email at
obdetector@gmail.com. The usage of the web application will be available to you on a monthly
basis for a very affordable amount. You will have access to all algorithms with a single payment.