Showing 25 results for Surveillance
Mm Gouya, Sm Zahraei, Gh Moradi, M Karami, S Mahmodi, Sh Shah Mahmoodi , E Ghaderi, F Kaveh, A Norouzinejad , K Hajibagheri, Kh Rahmani,
Volume 16, Issue 2 (8-2020)
Abstract
Background and Objectives: : According to the global strategy for polio eradication, targeted surveillance of the disease is one of the main tasks of the health system. The purpose of this study was to review the status and surveillance of poliomyelitis/acute flaccid paralysis (AFP) in Iran.
Methods: The present study was a review on the processes, structures and achievements of the poliomyelitis/AFP surveillance system in Iran during 2017-2019. The data of this study were obtained from the surveillance system of the Center for Communicable Disease Control; a review of the records, documents, books and published articles; and interviews with process owners and experts of poliomyelitis/AFP surveillance.
Results: The polio eradication program in Iran is based on the action plan of the World Health Organization that was introduced initially in 1988. Currently, the surveillance system of AFP is active at three levels: country, university, and city. The number of poliomyelitis cases in the country decreased from 50 cases per year in 1985 to zero in 2001, and Iran has been a polio-free country since 2001. The final report on polio eradication in Iran was approved by the regional commission on polio detection in April 2006.
Conclusion: The surveillance system of AFP has had a proper effectiveness throughout the country. Maintaining this situation in the country requires an increase in the sensitivity of the surveillance system of the disease, regular monitoring of vaccine coverage, strict implementation of international health regulations, especially on the eastern borders of the country, and providing technical assistance to neighboring countries.
K Sharifolkashani, P Yavari, , R Shekarriz, F Tajdini, N Aghili,
Volume 16, Issue 4 (3-2021)
Abstract
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 outbreak alert threshold of each season and province was determined separately using the average of three years (1393 to 1395) in the same season and province. The dysentery outbreak in each season was exclusively predicted for Isfahan, Khuzestan, and Hamadan provinces in 2017 using the CUSUM method.
Results: In Isfahan Province, the outbreak alert was higher in the spring and summer and lower in the autumn and winter using the current method compared to the CUSUM method. For Khuzestan Province, the current outbreak alert was significantly higher in all seasons compared to the CUSUM method, while the current outbreak alert was lower than the alert predicted by the CUSUM method in Hamadan Province in all the seasons.
Conclusion: Compared to constant threshold-based methods, using the CUSUM method seems to be a better way for reporting outbreaks, especially in areas with a high incidence.
Fatemeh Ershadinia, Elham Rahimi, Bushra Zareie, Hadi Pashapoor, Manoochehr Karami,
Volume 19, Issue 2 (9-2023)
Abstract
Background and Objectives: The disease surveillance system provides essential information about the population at risk and the disease pattern. This review aimed to describe the experiences of countries in establishing COVID-19 school-based surveillance systems.
Methods: We conducted a systematic review. Four databases were searched between January 2019 and December 2022 using relevant keywords. The studies were screened by two people according to the inclusion and exclusion criteria. The findings were extracted using a standard form and aligned to the objectives of the review.
Results: The data from 12 studies were extracted using the standard form. All studies related to the school-based surveillance system of COVID-19. Most of studies were conducted in the United States of America and England. The reports did not conform to the standard. The number of schools covered in surveillance systems ranged from 2 to more than 6000 schools. The age group in these studies was 0 to 19 years. Schools submitted data daily or weekly.
Conclusion: The results of the COVID-19 surveillance systems in schools should be reported according to standard Instructions. This is considered a necessity to monitor and evaluate the surveillance system. It also allows other countries and researchers to share and use the results. In addition, sensitivity, timeliness, and positive predictive value were not reported in implemented surveillance systems.
Manoochehr Karami,
Volume 20, Issue 3 (12-2024)
Abstract
Artificial intelligence (AI) refers to the process in which computers, rather than human intelligence, perform tasks, such as early warning of an epidemic. This editorial aimed to describe the potential applications of digital health and the challenges faced by the health system of Iran concerning the application of artificial intelligence and innovative technology in public health surveillance and early warning of epidemics. The use of new technologies at national and subnational levels for early warning of public health threats requires a suitable platform within the context of disease surveillance systems. The Iran health system currently utilizes a syndromic approach and event-based surveillance to monitor acute respiratory infections. However, the structure of Iran's national communicable disease surveillance system has faced challenges due to the inability to share and exchange data at the level of primary health care data sources. Accordingly, application and integration of AI should be considered as Iran’s health priority to promote infrastructure and technology requirements, including compatibility, interoperability, and strategies for ethical and responsible use by public health authorities. Since pandemics and epidemics have not been limited to the previous ones, such as COVID-19, influenza, SARS, dengue fever, and similar threats, operations planning is required for the integration of artificial intelligence tools to prepare and respond to biological threats promptly by the Iranian Ministry of Health, stakeholders, and other parties.
Bahar Haghdoost, Zhaleh Abdi, Iraj Harirchi, Elham Ahmadnezhad,
Volume 21, Issue 2 (9-2025)
Abstract
The COVID-19 pandemic has highly impacted health systems, and the limitations of the national reporting system have reduced the accuracy of estimating the burden of this disease. This study examined the underreporting of COVID-19 cases and hospitalizations using data from the National Survey on Risk Factors for Non-communicable Diseases (STEPS) in Iran in 2021. In this study, 25,425 individuals from the population aged 18 and above were randomly enrolled. In addition to information on non-communicable disease risk factors, participants were questioned about a history of COVID-19 infection, hospitalization, and intensive care unit admission. The frequency of these events was then compared with registry data at the time of data collection. According to the results, 9.3% (95% CI: 8.56 to 9.44) reported a history of COVID-19 infection. Furthermore, among those infected, 12.71% (11.25 to 14.20) reported a history of hospitalization due to COVID-19. Among those hospitalized, 13.74% (8.25 to 18.9) had been hospitalized in intensive care units. Based on this, it is estimated that the sensitivity of recording symptomatic cases was 61.7% (59% to 65%) and for hospitalized cases was 86% (77% to 97.1%).
As a conclusion, it can be stated that the registered incidence of symptomatic COVID-19 cases in Iran was underreported by nearly 40%, and hospitalizations due to COVID-19 were underreported by about 15%. Compared to data from many other countries, including developed nations, this situation can be considered as acceptable.
