Mojtaba Sepandi; Yousef Alimohamadi; Mousa Imani
Abstract
Background: Outbreak detection algorithms could play a key role in public health surveillance.Objectives: This study aimed to compare the performance of three algorithms (EWMA, Cumulative Sum (CUSUM), and Poisson Regression) using the reported COVID-19 data for outbreak detection.Methods: Three outbreak ...
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Background: Outbreak detection algorithms could play a key role in public health surveillance.Objectives: This study aimed to compare the performance of three algorithms (EWMA, Cumulative Sum (CUSUM), and Poisson Regression) using the reported COVID-19 data for outbreak detection.Methods: Three outbreak detection algorithms were applied to the data of COVID-19 daily new cases in Iran between 19/02/2020 and 20/06/2022, and 344 simulated outbreak days were injected into the data sequences. The Area Under the Receiver Operating Characteristics (ROC) Curve (AUC) and its 95% confidence intervals (95% CI) were also computed.Results: EWMA9 had the lowest AUC (51%). Among the different algorithms, EWMA9 with λ = 0.9 and CUSUM 1 had the highest sensitivity with 100 and 87% (95% CI: 84%-91%), respectively.Conclusion: According to the results, CUSUM, EWMA, and poison regression showed appropriate performance in detecting the COVID-19 outbreaks. These algorithms can be extremely helpful for health practitioners and policymakers in the detection of infectious disease outbreaks.
Seyed Mohammadreza Hashemian; Amir Vahedian Azimi; Mohamad Amin Pourhoseingholi
Roshan Kamal Topno; Krishna Pandey; Banke Bihari Singh; Manas Ranjan Dikhit; Ashish Kumar; Maneesh Kumar; Ganesh Chandra Sahoo; Vidya Nand Rabidas; Niyamat Ali Siddiqui; Wakil Paswan; Arjun Lal; Diwakar Singh Dinesh; Pradeep Das
Abstract
Background: From Gaya and adjoining regions, the trend in patients admitted with acute neurological illness was investigated. Illnesses were identified as sudden outbreaks of Japanese virus encephalitis (JE), Herpes simplex virus encephalitis (HSV-1&2), and other acute encephalitis syndrome (AES). ...
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Background: From Gaya and adjoining regions, the trend in patients admitted with acute neurological illness was investigated. Illnesses were identified as sudden outbreaks of Japanese virus encephalitis (JE), Herpes simplex virus encephalitis (HSV-1&2), and other acute encephalitis syndrome (AES). Objective: In the current study, an investigation was carried out to assess potential infectious pathogens in patients aged 16 years or younger who were admitted to Anugrah Narayan Magadh Memorial Medical College Hospital, Gaya, with encephalitis-like symptoms. Methods: Cross-epidemiological, serological, and molecular biological studies were performed on samples collected from 71 patients below 16 years of age. Patients’ clinical histories, i.e. fever, socio-demographic characteristics, and other clinical data, were extracted from patient files. Results: The results showed confirmed AES cases, including 49.30% JE and 7.04% HSV positive patients. A higher case-fatality rate of 40% in JE and 40% HSV cases below 7 years of age were observed during treatment would become an unavoidable concern. The epidemical sex ratio was observed to be higher in girls than in boys (1.26:1). Conclusion: The results suggested that JE virus was found to be a main causative risk factor responsible for disease transmission in the outbreak area.