Determinants of Outbreak Detection Performance
نویسندگان
چکیده
Introduction The choice of outbreak detection algorithm and its configuration can result in important variations in the performance of public health surveillance systems. Our work aims to characterize the performance of detectors based on outbreak types. We are using Bayesian networks (BN) to model the relationships between determinants of outbreak detection and the detection performance based on a significant study on simulated data.
منابع مشابه
Quantifying the determinants of outbreak detection performance through simulation and machine learning
OBJECTIVE To develop a probabilistic model for discovering and quantifying determinants of outbreak detection and to use the model to predict detection performance for new outbreaks. MATERIALS AND METHODS We used an existing software platform to simulate waterborne disease outbreaks of varying duration and magnitude. The simulated data were overlaid on real data from visits to emergency depar...
متن کاملارزشیابی عملکرد الگوریتم میانگین متحرک وزن داده شده نمایی در کشف دو مورد طغیان سرخک، با استفاده از رویکرد آزمون دادههای واقعی
Background & Objectives: Evaluating the performance of outbreak detection methods using real data testing provide the highest degree of validity. The aim of this study was to determine the performance of the Exponentially Weighted Moving Average (EWMA) in real time detection of two local outbreaks in Iran. Methods: The EWMA algorithm (both ƛ= 0.3 and 0.6) applied on daily counts of suspected ca...
متن کاملEarly Detection of Dysentery Outbreaks by Cumulative Sum Method Based on National Surveillance System Data in 1393-1396
Background and Objectives: Correct and timely detection of the outbreaks of diseases with a short incubation period is of great importance in the health system. The aim of this study was to determine the detection of dysentery outbreaks using the cumulative sum method. Methods: This time series study was conducted using the data of the National Surveillance System between 2014 and 2017. The...
متن کاملروندهای فصلی و الگوهای قابل توجیه در دادههای کشوری نظام مراقبت بیماری سرخک: رویکردهای شناسایی و حذف
Background & Objectives: Knowledge of the presence of seasonal trends and other explainable patterns in the prediagnostic data sources and removing such patterns before applying outbreak detection methods seem very important. This study aimed to detect and remove the explainable patterns such as seasonality, day-of-week (DOW) and holiday effects of the daily counts of suspected cases of measles...
متن کاملارزشیابی عملکرد الگوریتم مجموع تراکمی در کشف طغیان
Background & Objectives: Timely response to emerging diseases and outbreaks are a major public health and health systems priority. There are few published studies that evaluate the performance of cumulative sum (CUSUM) on identical data using semi- synthetic simulation approach. This study was undertaken to determine the performance of the CUSUM in timely detection of 831 days of simulated outb...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 5 شماره
صفحات -
تاریخ انتشار 2013