Structure, functions, performance and gaps of event-based surveillance (EBS) in Sudan, 2021: a cross-sectional review.

BACKGROUND: Event-based surveillance (EBS) is an essential component of Early Warning Alert and Response (EWAR) as per the International Health Regulations (IHR), 2005. EBS was established in Sudan in 2016 as a complementary system for Indicator-based surveillance (IBS). This review will provide an overview of the current EBS structure, functions and performance in Sudan and identify the gaps and ways forward.  METHODS: The review followed the WHO/EMRO guidelines and tools. Structured discussions, observation and review of records and guidelines were done at national and state levels. Community volunteers were interviewed through phone calls. Directors of Health Emergency and Epidemic Control, surveillance officers and focal persons for EBS at the state level were also interviewed. SPSS software was used to perform descriptive statistical analysis for quantitative data, while qualitative data was analysed manually using thematic analysis, paying particular attention to the health system level allowing for an exploration of how and why experiences differ across levels. Written and verbal consents were obtained from all participants as appropriate. RESULTS: Sudan has a functioning EBS; however, there is an underestimation of its contribution and importance at the national and states levels. The link between the national level and states is ad hoc or is driven by the need for reports. While community event-based surveillance (CEBS) is functioning, EBS from health facilities and from non-health sectors is not currently active. The integration of EBS into overall surveillance was not addressed, and the pathway from detection to action is not clear. The use of electronic databases and platforms is generally limited. Factors that would improve performance include training, presence of a trained focal person at state level, and regular follow-up from the national level. Factors such as staff turnover, income in relation to expenses and not having a high academic qualification (Diploma or MSc) were noticed as inhibiting factors. CONCLUSION: The review recommended revisiting the surveillance structure at national and state levels to put EBS as an essential component and to update guidelines and standard operation procedures SOPs to foster the integration between EBS components and the overall surveillance system. The need for strengthening the link with states, capacity building and re-addressing the training modalities was highlighted.

Strengthening event-based surveillance (EBS): a case study from Afghanistan.

The sustained instability in Afghanistan, along with ongoing disease outbreaks and the impact of the COVID-19 pandemic, has significantly affected the country.During the COVID-19 pandemic, the country's detection and response capacities faced challenges. Case identification was done in all health facilities from primary to tertiary levels but neglected cases at the community level, resulting in undetected and uncontrolled transmission from communities. This emphasizes a missed opportunity for early detection that Event-Based Surveillance (EBS) could have facilitated.Therefore, Afghanistan planned to strengthen the EBS component of the national public health surveillance system to enhance the capacity for the rapid detection and response to infectious disease outbreaks, including COVID-19 and other emerging diseases. This effort was undertaken to promptly mitigate the impact of such outbreaks.We conducted a landscape assessment of Afghanistan's public health surveillance system to identify the best way to enhance EBS, and then we crafted an implementation work plan. The work plan included the following steps: establishing an EBS multisectoral coordination and working group, identifying EBS information sources, prioritizing public health events of importance, defining signals, establishing reporting mechanisms, and developing standard operating procedures and training guides.EBS is currently being piloted in seven provinces in Afghanistan. The lessons learned from the pilot phase will support its overall expansion throughout the country.

Achieving integrated disease surveillance in the Eastern Mediterranean Region.

Access to reliable and timely information is key for healthcare decision-making at the regional, national and sub-national levels. However, lack of access to such information hampers to progress towards achievement of the Sustainable Development Goals (SDGs) in the Eastern Mediterranean Region (EMR), as indicated in the Regional Progress Report on Health-Related Sustainable Development Goals.

Enhanced event-based surveillance: Epidemic Intelligence from Open Sources (EIOS) during FIFA World Cup 2022 Qatar.

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.