Mohamed Sallam , Raihana Jabbar , Lylu K. Mahadoon , Tasneem J. Elshareif , Mariam Darweesh , Hanaa S. Ahmed , Douaa O.A. Mohamed , Aura Corpuz , Mahmoud Sadek , Muzhgan Habibi , Farida Abougazia , Rula Shami , Montaha Mahmoud , Sara Heikal , Sarah Aqel , Sayed Himatt , Maha Al-Shamali , Hamad Al-Romaihi
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引用次数: 0
Abstract
Background
Public health threats can significantly impact mass gatherings and enhancing surveillance systems would thus be crucial. Epidemic Intelligence from Open Sources (EIOS) was introduced to Qatar to complement the existing surveillance measures in preparation to the FIFA World Cup Qatar 2022 (FWC22). This study estimated the empirical probability of EIOS detecting signals of public health relevance. It also looked at the factors responsible for discerning a moderate-high risk signal during a mass gathering event.
Methods
This cross-sectional descriptive study used data collected between November 8th and December 25th, 2022, through an EIOS dashboard that filtered open-source articles using specific keywords. Triage criteria and scoring scheme were developed to capture signals and these were maintained in MS Excel. EIOS’ contribution to epidemic intelligence was assessed by the empirical probability estimation of relevant public health signals. Chi-squared tests of independence were performed to check for associations between various hazard categories and other independent variables. A multivariate logistic regression evaluated the predictors of moderate-high risk signals that required prompt action.
Results
The probability of EIOS capturing a signal relevant to public health was estimated at 0.85 % (95 % confidence interval (CI) [0.82 %−0.88 %]) with three signals requiring a national response. The hazard category of the signal had significant association to the region of occurrence (χ2 (5, N = 2543) = 1021.6, p < .001). The hazard category also showed significant association to its detection during matchdays of the tournament (χ2 (5, N = 2543) = 11.2, p < .05). The triage criteria developed was able to discern between low and moderate-high risk signals with an acceptable discrimination (Area Under the Curve=0.79).
Conclusion
EIOS proved useful in the early warning of public health threats.
期刊介绍:
The Journal of Infection and Public Health, first official journal of the Saudi Arabian Ministry of National Guard Health Affairs, King Saud Bin Abdulaziz University for Health Sciences and the Saudi Association for Public Health, aims to be the foremost scientific, peer-reviewed journal encompassing infection prevention and control, microbiology, infectious diseases, public health and the application of healthcare epidemiology to the evaluation of health outcomes. The point of view of the journal is that infection and public health are closely intertwined and that advances in one area will have positive consequences on the other.
The journal will be useful to all health professionals who are partners in the management of patients with communicable diseases, keeping them up to date. The journal is proud to have an international and diverse editorial board that will assist and facilitate the publication of articles that reflect a global view on infection control and public health, as well as emphasizing our focus on supporting the needs of public health practitioners.
It is our aim to improve healthcare by reducing risk of infection and related adverse outcomes by critical review, selection, and dissemination of new and relevant information in the field of infection control, public health and infectious diseases in all healthcare settings and the community.