The process used to collect, manage, analyze, interpret and report reliable information about patients in the community is called care; 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. The successful performance of care systems depends on their ability to timely identify public health threats, such as outbreaks; Because a faster investigation enables the prevention and control of outbreaks and is very important for the implementation of control measures. In recent years, the care system in relation to this goal has grown very fast and significantly, which is due to two factors; New concerns about large-scale bioterrorism attacks and increased public awareness of emerging and re-emerging infections. These advances have led to the introduction of syndromic surveillance systems, increased databases, and the creation of automated outbreak detection systems to process data on large numbers of infections.
obdetector.ir is an online system of outbreak detection algorithms, which is designed with the aim of detecting all types of single-source and progressive epidemics. This system compares the best time and single-variable methods for diagnosing disease outbreaks in three categories of low, medium and high incidence in the routine care system and the syndromic care system. And its most important features are as follows:
Introducing an accepted classification system in detecting changes in care system data based on trend and level of incidence
Implementation of various flood identification algorithms
The possibility of changing the parameters associated with each algorithm based on the characteristics of the data or the goals of the researcher
Facilitating the selection of flood detection algorithms from a wide list of available algorithms
The possibility of receiving results from the application of various algorithms immediately after uploading the data of the care system
Providing outputs with the same structure, in order to compare the performance of flood detection algorithms
The possibility of continuous monitoring of known diseases/syndromes under the care system
Facilitating the implementation of protective measures through early detection aimed at limiting the impact of disease outbreaks
Obdetector.ir uses Farrington and Flexible Farrington algorithms, which are based on the family of generalized linear models, ARIMA time series, cumulative sum control chart (CUSUM), initial system deviation report (EARS) and exponential weighted moving average algorithm. (EWMA) uses. For each algorithm, two parts are considered; “Algorithm Introduction” section briefly introduces each method and “Algorithm Usage Guide” section also defines the parameters of each algorithm. The design of the data entry panel and the setting of parameters as well as the calculations related to each algorithm have been done using R software.
Developers and investors
This system is taken from the PhD thesis of Mrs. Bushra Zarei in the field of epidemiology under the title “Designing a set of evaluation tools for outbreak detection algorithms in the timely detection of single-source and progressive epidemics” from the Department of Epidemiology, Hamedan University of Medical Sciences. Dr. Jalal Pouralajl, Dr. Manouchehr Karmi, and Dr. Amin Roshni participated in this thesis as the first, second, and associate supervisors, respectively.
The financial support of this thesis was provided by the Research and Technology Vice-Chancellor of Hamedan University of Medical Sciences.