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Background: Epidemic intelligence (EI) ensures early detection, assessment, and communication of public health threats. Threat reporting defines priorities and mobilize resources for surveillance, prevention, and control. In Portugal, the Directorate-General of Health (DGS) is responsible for EI and publishes a weekly public health threat report (RONDA). Changes in threats in regular threat reports since COVID-19 have not been previously described. We analysed changes in non-COVID threat reporting in the weekly threat report. Methods: Using the DGS Emergency Operations Centre’s threat reporting database, we compared threats reported in RONDAs from 2016 to 2022 in three sequential periods: P1 before COVID-19 (January 2016–March 2020), P2 during acute COVID-19 restrictions (April 2020–February 2022), and P3 in post-acute COVID-19 phase (February 2022–September 2022). We described the monthly average frequency of reports on non-COVID-19 threats in those periods considering different disease groups, geographical focus, and information sources. We estimated expected non-COVID-19 reports on threats using a forecast model fitted to the time series until March 2020 and compared observed and expected values. Results: Non-COVID-19 threats had a decrease in the monthly average frequency of reporting in period 2 (x¯1: 4.7 vs. x¯: 2.3, p < 0.001) compared to period 1. Using the forecast methods, there were 114 fewer non-COVID threats than the 162 expected (−70%) in period 2. In period 3, there were 105 more threats than expected (+256%). The ECDC and the WHO were the most frequent sources of information followed by national Public Health sources. Conclusions: During COVID-19, there was a decrease in reports on non-COVID threats in Portugal. COVID-19 possibly affected global EI, by shifting attention and resources from other threats to the pandemic. However, the number of threats that warrant follow-up and communication is increasing. Further research is necessary to inform the EI research and development agenda, to ensure that all relevant threats are detected, accessed, and communicated according to evolving EI objectives and priorities while resources and preparedness are guaranteed.

Summary 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.

Abstract Background European epidemic intelligence (EI) systems receive vast amounts of information and data on disease outbreaks and potential health threats. The quantity and variety of available data sources for EI, as well as the available methods to manage and analyse these data sources, are constantly increasing. Our aim was to identify the difficulties encountered in this context and which innovations, according to EI practitioners, could improve the detection, monitoring and analysis of disease outbreaks and the emergence of new pathogens. Methods We conducted a qualitative study to identify the need for innovation expressed by 33 EI practitioners of national public health and animal health agencies in five European countries and at the European Centre for Disease Prevention and Control (ECDC). We adopted a stepwise approach to identify the EI stakeholders, to understand the problems they faced concerning their EI activities, and to validate and further define with practitioners the problems to address and the most adapted solutions to their work conditions. We characterized their EI activities, professional logics, and desired changes in their activities using NvivoⓇ software. Results Our analysis highlights that EI practitioners wished to collectively review their EI strategy to enhance their preparedness for emerging infectious diseases, adapt their routines to manage an increasing amount of data and have methodological support for cross-sectoral analysis. Practitioners were in demand of timely, validated and standardized data acquisition processes by text mining of various sources; better validated dataflows respecting the data protection rules; and more interoperable data with homogeneous quality levels and standardized covariate sets for epidemiological assessments of national EI. The set of solutions identified to facilitate risk detection and risk assessment included visualization, text mining, and predefined analytical tools combined with methodological guidance. Practitioners also highlighted their preference for partial rather than full automation of analyses to maintain control over the data and inputs and to adapt parameters to versatile objectives and characteristics. Conclusions The study showed that the set of solutions needed by practitioners had to be based on holistic and integrated approaches for monitoring zoonosis and antimicrobial resistance and on harmonization between agencies and sectors while maintaining flexibility in the choice of tools and methods. The technical requirements should be defined in detail by iterative exchanges with EI practitioners and decision-makers.

Background: Epidemic intelligence (EI) ensures early detection, assessment, and communication of public health threats. Threat reporting defines priorities and mobilize resources for surveillance, prevention, and control. In Portugal, the Directorate-General of Health (DGS) is responsible for EI and publishes a weekly public health threat report (RONDA). Changes in threats in regular threat reports since COVID-19 have not been previously described. We analysed changes in non-COVID threat reporting in the weekly threat report. Methods: Using the DGS Emergency Operations Centre's threat reporting database, we compared threats reported in RONDAs from 2016 to 2022 in three sequential periods: P1 before COVID-19 (January 2016–March 2020), P2 during acute COVID-19 restrictions (April 2020–February 2022), and P3 in post-acute COVID-19 phase (February 2022–September 2022). We described the monthly average frequency of reports on non-COVID-19 threats in those periods considering different disease groups, geographical focus, and information sources. We estimated expected non-COVID-19 reports on threats using a forecast model fitted to the time series until March 2020 and compared observed and expected values. Results: Non-COVID-19 threats had a decrease in the monthly average frequency of reporting in period 2 ( x ¯ 1 : 4.7 vs. x ¯ : 2.3, p < 0.001) compared to period 1. Using the forecast methods, there were 114 fewer non-COVID threats than the 162 expected (−70%) in period 2. In period 3, there were 105 more threats than expected (+256%). The ECDC and the WHO were the most frequent sources of information followed by national Public Health sources. Conclusions: During COVID-19, there was a decrease in reports on non-COVID threats in Portugal. COVID-19 possibly affected global EI, by shifting attention and resources from other threats to the pandemic. However, the number of threats that warrant follow-up and communication is increasing. Further research is necessary to inform the EI research and development agenda, to ensure that all relevant threats are detected, accessed, and communicated according to evolving EI objectives and priorities while resources and preparedness are guaranteed. [ABSTRACT FROM AUTHOR]

Summary: 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. [ABSTRACT FROM AUTHOR]

Background: European epidemic intelligence (EI) systems receive vast amounts of information and data on disease outbreaks and potential health threats. The quantity and variety of available data sources for EI, as well as the available methods to manage and analyse these data sources, are constantly increasing. Our aim was to identify the difficulties encountered in this context and which innovations, according to EI practitioners, could improve the detection, monitoring and analysis of disease outbreaks and the emergence of new pathogens. Methods: We conducted a qualitative study to identify the need for innovation expressed by 33 EI practitioners of national public health and animal health agencies in five European countries and at the European Centre for Disease Prevention and Control (ECDC). We adopted a stepwise approach to identify the EI stakeholders, to understand the problems they faced concerning their EI activities, and to validate and further define with practitioners the problems to address and the most adapted solutions to their work conditions. We characterized their EI activities, professional logics, and desired changes in their activities using NvivoⓇ software. Results: Our analysis highlights that EI practitioners wished to collectively review their EI strategy to enhance their preparedness for emerging infectious diseases, adapt their routines to manage an increasing amount of data and have methodological support for cross-sectoral analysis. Practitioners were in demand of timely, validated and standardized data acquisition processes by text mining of various sources; better validated dataflows respecting the data protection rules; and more interoperable data with homogeneous quality levels and standardized covariate sets for epidemiological assessments of national EI. The set of solutions identified to facilitate risk detection and risk assessment included visualization, text mining, and predefined analytical tools combined with methodological guidance. Practitioners also highlighted their preference for partial rather than full automation of analyses to maintain control over the data and inputs and to adapt parameters to versatile objectives and characteristics. Conclusions: The study showed that the set of solutions needed by practitioners had to be based on holistic and integrated approaches for monitoring zoonosis and antimicrobial resistance and on harmonization between agencies and sectors while maintaining flexibility in the choice of tools and methods. The technical requirements should be defined in detail by iterative exchanges with EI practitioners and decision-makers. [ABSTRACT FROM AUTHOR]

Abstract Epidemic Intelligence (EI) encompasses all activities related to early identification, verification, analysis, assessment, and investigation of health threats. It integrates an indicator-based (IBS) component using systematically collected surveillance data, and an event-based component (EBS), using non-official, non-verified, non-structured data from multiple sources. We described current EI practices in Europe by conducting a survey of national Public Health (PH) and Animal Health (AH) agencies. We included generic questions on the structure, mandate and scope of the institute, on the existence and coordination of EI activities, followed by a section where respondents provided a description of EI activities for three diseases out of seven disease models. Out of 81 gatekeeper agencies from 41 countries contacted, 34 agencies (42%) from 26 (63%) different countries responded, out of which, 32 conducted EI activities. Less than half (15/32; 47%) had teams dedicated to EI activities and 56% (18/34) had Standard Operating Procedures (SOPs) in place. On a national level, a combination of IBS and EBS was the most common data source. Most respondents monitored the epidemiological situation in bordering countries, the rest of Europe and the world. EI systems were heterogeneous across countries and diseases. National IBS activities strongly relied on mandatory laboratory-based surveillance systems. The collection, analysis and interpretation of IBS information was performed manually for most disease models. Depending on the disease, some respondents did not have any EBS activity. Most respondents conducted signal assessment manually through expert review. Cross-sectoral collaboration was heterogeneous. More than half of the responding institutes collaborated on various levels (data sharing, communication, etc.) with neighbouring countries and/or international structures, across most disease models. Our findings emphasise a notable engagement in EI activities across PH and AH institutes of Europe, but opportunities exist for better integration, standardisation, and automatization of these efforts. A strong reliance on traditional IBS and laboratory-based surveillance systems, emphasises the key role of in-country laboratories networks. EI activities may benefit particularly from investments in cross-border collaboration, the development of methods that can automatise signal assessment in both IBS and EBS data, as well as further investments in the collection of EBS data beyond scientific literature and mainstream media.

Introduction: Event-based surveillance (EBS) is a critical component of Early Warning, Alert and Response (EWAR) capacity needed for outbreak prevention and control. To better understand existing EBS and monitor the progress of capacity-building efforts over time, Africa CDC developed an EBS scorecard as part of a revision to the EBS Framework. Methods: We distributed the scorecard to African Union (AU) Member States (MSs). Survey responses from the MSs’ human health sector were aggregated, cleaned, and analysed. MS, regional, and continental EBS capacity was assessed. Results: Between 21 July 2022 and 4 April 2023, a total of 63 respondents representing 49 (89%) of 55 MSs completed the survey. Given Africa CDC’s public health mandate, we acknowledged the importance of One Health collaboration in MSs but focused on and analysed only the human health sector responses. Thirty-four (71%) MSs stated having EBS in place; hotline was the most common type of EBS implemented (76%). Seventeen (50%) MSs reported multisectoral, One Health collaboration as part of EBS implementation. Scorecard outcomes showed a minimal (score of

Epidemic Intelligence (EI) encompasses all activities related to early identification, verification, analysis, assessment, and investigation of health threats. It integrates an indicator-based (IBS) component using systematically collected surveillance data, and an event-based component (EBS), using non-official, non-verified, non-structured data from multiple sources. We described current EI practices in Europe by conducting a survey of national Public Health (PH) and Animal Health (AH) agencies. We included generic questions on the structure, mandate and scope of the institute, on the existence and coordination of EI activities, followed by a section where respondents provided a description of EI activities for three diseases out of seven disease models. Out of 81 gatekeeper agencies from 41 countries contacted, 34 agencies (42%) from 26 (63%) different countries responded, out of which, 32 conducted EI activities. Less than half (15/32; 47%) had teams dedicated to EI activities and 56% (18/34) had Standard Operating Procedures (SOPs) in place. On a national level, a combination of IBS and EBS was the most common data source. Most respondents monitored the epidemiological situation in bordering countries, the rest of Europe and the world. EI systems were heterogeneous across countries and diseases. National IBS activities strongly relied on mandatory laboratory-based surveillance systems. The collection, analysis and interpretation of IBS information was performed manually for most disease models. Depending on the disease, some respondents did not have any EBS activity. Most respondents conducted signal assessment manually through expert review. Cross-sectoral collaboration was heterogeneous. More than half of the responding institutes collaborated on various levels (data sharing, communication, etc.) with neighbouring countries and/or international structures, across most disease models. Our findings emphasise a notable engagement in EI activities across PH and AH institutes of Europe, but opportunities exist for better integration, standardisation, and automatization of these efforts. A strong reliance on traditional IBS and laboratory-based surveillance systems, emphasises the key role of in-country laboratories networks. EI activities may benefit particularly from investments in cross-border collaboration, the development of methods that can automatise signal assessment in both IBS and EBS data, as well as further investments in the collection of EBS data beyond scientific literature and mainstream media. [ABSTRACT FROM AUTHOR]

Event-based surveillance (EBS) is a core component of early warning surveillance. In 2018, Africa CDC developed the first edition of an event-based surveillance framework to guide African Union Member States in implementing EBS. Country experiences during the COVID-19 pandemic demonstrated the value of data from non-traditional sources for real time situational awareness; at the same time revealed the huge gaps in strengthening this arm of surveillance. Learning from these lessons and to begin to close those gaps, Africa CDC convened subject matter experts from African Union Member States and technical partners to develop the second edition of the EBS framework, 2023 and its training materials. The revised version includes additional sections such as, the multi-sectoral one health collaboration in EBS, monitoring and evaluation, cross border EBS, and use of event management systems. The current manuscript provides an overview of the 2023 Africa CDC EBS framework and highlights experience in two countries that have successfully employed this resource in their implementation efforts. [ABSTRACT FROM AUTHOR]

In the context of Epidemic Intelligence, many Event-Based Surveillance (EBS) systems have been proposed in the literature to promote the early identification and characterization of potential health threats from online sources of any nature. Each EBS system has its own surveillance definitions and priorities, therefore this makes the task of selecting the most appropriate EBS system for a given situation a challenge for end-users. In this work, we propose a new evaluation framework to address this issue. It first transforms the raw input epidemiological event data into a set of normalized events with multi-granularity, then conducts a descriptive retrospective analysis based on four evaluation objectives: spatial, temporal, thematic and source analysis. We illustrate its relevance by applying it to an Avian Influenza dataset collected by a selection of EBS systems, and show how our framework allows identifying their strengths and drawbacks in terms of epidemic surveillance.

Abstract Background In order to detect threats to public health and to be well-prepared for endemic and pandemic illness outbreaks, countries usually rely on event-based surveillance (EBS) and indicator-based surveillance systems. Event-based surveillance systems are key components of early warning systems and focus on fast capturing of data to detect threat signals through channels other than traditional surveillance. In this study, we develop Natural Language Processing tools that can be used within EBS systems. In particular, we focus on information extraction techniques that enable digital surveillance to monitor Internet data and social media. Results We created an annotated Spanish corpus from ProMED-mail health reports regarding disease outbreaks in Latin America. The corpus has been used to train algorithms for two information extraction tasks: named entity recognition and relation extraction. The algorithms, based on deep learning and rules, have been applied to recognize diseases, hosts, and geographical locations where a disease is occurring, among other entities and relations. In addition, an in-depth analysis of micro-average F1 metrics shows the suitability of our approaches for both tasks. Conclusions The annotated corpus and algorithms presented could leverage the development of automated tools for extracting information from news and health reports written in Spanish. Moreover, this framework could be useful within EBS systems to support the early detection of Latin American disease outbreaks.

Abstract 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.

Event-based surveillance (EBS) is a core component of early warning surveillance. In 2018, Africa CDC developed the first edition of an event-based surveillance framework to guide African Union Member States in implementing EBS. Country experiences during the COVID-19 pandemic demonstrated the value of data from non-traditional sources for real time situational awareness; at the same time revealed the huge gaps in strengthening this arm of surveillance. Learning from these lessons and to begin to close those gaps, Africa CDC convened subject matter experts from African Union Member States and technical partners to develop the second edition of the EBS framework, 2023 and its training materials. The revised version includes additional sections such as, the multi-sectoral one health collaboration in EBS, monitoring and evaluation, cross border EBS, and use of event management systems. The current manuscript provides an overview of the 2023 Africa CDC EBS framework and highlights experience in two countries that have successfully employed this resource in their implementation efforts.

The coronavirus disease 2019 pandemic served as a compelling modern-day reminder of the value of early warning against communicable disease threats in public health. As countries exit the acute phase of the pandemic, there remains a continued need to be vigilant for potential communicable disease threats, particularly as the risk of animal-to-human spillover events is increasing due to climate and land use change. Early warning of emerging threats facilitates earlier public health response, which affords more time to implement public health measures that can help minimize the impact of a particular health threat and protect the health and well-being of the population. One approach to providing early warning for communicable disease and other threats is through event-based surveillance (EBS). However, EBS is not often discussed in the context of public health surveillance. This overview introduces EBS and how it might contribute to providing early warning for communicable disease threats. [ABSTRACT FROM AUTHOR]

Background: In order to detect threats to public health and to be well-prepared for endemic and pandemic illness outbreaks, countries usually rely on event-based surveillance (EBS) and indicator-based surveillance systems. Event-based surveillance systems are key components of early warning systems and focus on fast capturing of data to detect threat signals through channels other than traditional surveillance. In this study, we develop Natural Language Processing tools that can be used within EBS systems. In particular, we focus on information extraction techniques that enable digital surveillance to monitor Internet data and social media. Results: We created an annotated Spanish corpus from ProMED-mail health reports regarding disease outbreaks in Latin America. The corpus has been used to train algorithms for two information extraction tasks: named entity recognition and relation extraction. The algorithms, based on deep learning and rules, have been applied to recognize diseases, hosts, and geographical locations where a disease is occurring, among other entities and relations. In addition, an in-depth analysis of micro-average F1 metrics shows the suitability of our approaches for both tasks. Conclusions: The annotated corpus and algorithms presented could leverage the development of automated tools for extracting information from news and health reports written in Spanish. Moreover, this framework could be useful within EBS systems to support the early detection of Latin American disease outbreaks. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

ObjectiveTo determine the epidemiological characteristics of infectious disease related public health bud-events in Shanghai and assess the effects of bud-event surveillance， so as to provide scientific evidence for improving the surveillance system.MethodsSurveillance data of infectious disease related public health bud-events were collected from 16 districts of Shanghai from 2017 through 2020. Then the data were analyzed and compared with infectious disease related public health emergencies during the same period.ResultsA total of 6 376 infectious disease related public health bud-events were documented in Shanghai in 2017‒2020， which involved 29 792 cases. There were two seasonal peaks， April through June and November through December. Clustered events accounted for 38.85%， mainly caused by chickenpox （14.10%）， hand，foot and mouth disease （11.17%） and norovirus-associated infectious diarrhea （6.54%）. The 36.73% of the bud-events occurred in school settings， which involved 24 718 cases （accounting for 83.00% of all cases）. Median time duration between onset date of the first cases and report date of the events was 4 days， and median duration of the events was 14 days， demonstrating positive correlation. In addition， all the infectious disease related public health emergencies（n=77） from 2017 through 2020 were classified as common events or unclassified. The proportion of infectious disease related public health emergencies in the bud-events during the same period was 1.21%， and that of infectious disease related public health emergencies in the bud-events in school settings was 2.48%.ConclusionTwo peaks of infectious disease related public health bud-events are observed in spring as well as autumn and winter in Shanghai from 2017 through 2020. Schools should be prioritized for control and prevention of infectious diseases. Bud-event surveillance system has been contributable to the prevention and control of public health emergencies， especially in the early detection， reporting and control of clustered events in schools. Bud-event surveillance system should be further improved and assessed comprehensively.

BackgroundWest Nile virus (WNV) has an enzootic cycle between birds and mosquitoes, humans being incidental dead-end hosts. Circulation of WNV is an increasing public health threat in Europe. While detection of WNV is notifiable in humans and animals in the European Union, surveillance based on human case numbers presents some limitations, including reporting delays.AimWe aimed to perform risk mapping of WNV circulation leading to human infections in Europe by integrating two types of surveillance systems: indicator-based and event-based surveillance.MethodsFor indicator-based surveillance, we used data on human case numbers reported to the European Centre for Disease Prevention and Control (ECDC), and for event-based data, we retrieved information from news articles collected through an automated biosurveillance platform. In addition to these data sources, we also used environmental data to train ecological niche models to map the risk of local WNV circulation leading to human infections.ResultsThe ecological niche models based on both types of surveillance data highlighted new areas potentially at risk of WNV infection in humans, particularly in Spain, Italy, France and Greece.ConclusionAlthough event-based surveillance data do not constitute confirmed occurrence records, integrating both indicator-based and event-based surveillance data proved useful. These results underscore the potential for a more proactive and comprehensive strategy in managing the threat of WNV in Europe by combining indicator- and event-based and environmental data for effective surveillance and public health response.

Background and objectives: Event-based surveillance and rapid risk assessment for acute public health events are essential in emerging infectious disease control. Since detecting the unusual signal in Wuhan in December 2019, Taiwan has been aligning risk management to policy planning via conducting regular risk assessments to combat the coronavirus disease 2019 (COVID-19). This article aims to provide some insights into Taiwan's experiences and corresponding actions for the outbreak. Results: The COVID-19 risk level in Taiwan was raised to “moderate-to-high” in mid-January 2020 when neighboring countries had reported cases and the human-to-human transmission became obvious. The risk level became “high” on 24 January due to China's escalating epidemic situation and imposed a lockdown in Wuhan. We learned that the commander recognized the importance of risk assessments and considered advice from the experts was crucial in making the correct decision at the early stage of the crisis. Conclusions: Given the surge of COVID-19 cases globally, understanding the evidence-driven mobilizations via detailed risk assessments in Taiwan may be an example worth considering for other countries. We believe that strengthening a global epidemic intelligence network and sharing information in a timely and transparent manner are essential for confronting new challenges of COVID-19 and other emerging infectious diseases.

Information integration across multiple event-based surveillance (EBS) systems has been shown to improve global disease surveillance in experimental settings. In practice, however, integration does not occur due to the lack of a common conceptual framework for encoding data within EBS systems. We aim to address this gap by proposing a candidate conceptual framework for representing events and related concepts in the domain of public health surveillance. [ABSTRACT FROM AUTHOR]

Event-based surveillance (EBS) is the organised approach to the detection and reporting of ‘signals,’ defined as information that may represent events of public health importance, often through channels outside of routine surveillance systems. Signals can be designed to detect patterns of disease, such as clusters of similar illness in a community, or clusters of disease or death in animals. Signals can also include single cases of suspected high-priority events such a patient with viral haemorrhagic fever. EBS can be a key component of an effective early warning system, which enables countries to be better prepared for endemic and pandemic illness outbreaks. EBS uses an all-hazards approach that includes the principles of One Health. This review covers the concept and process of EBS, different sources for EBS data, and methods to obtain information from these sources. This overview will aid countries in implementing this important form of surveillance.

Event-based surveillance (EBS) is the organised approach to the detection and reporting of 'signals,' defined as information that may represent events of public health importance, often through channels outside of routine surveillance systems. Signals can be designed to detect patterns of disease, such as clusters of similar illness in a community, or clusters of disease or death in animals. Signals can also include single cases of suspected high-priority events such a patient with viral haemorrhagic fever. EBS can be a key component of an effective early warning system, which enables countries to be better prepared for endemic and pandemic illness outbreaks. EBS uses an all-hazards approach that includes the principles of One Health. This review covers the concept and process of EBS, different sources for EBS data, and methods to obtain information from these sources. This overview will aid countries in implementing this important form of surveillance. [ABSTRACT FROM AUTHOR]

Introduction: Hospitals are a key source of information for the early identification of emerging disease outbreaks and acute public health events for risk assessment, decision-making, and public health response. The objectives of this study were to identify potential facilitators and barriers for reporting of unusual events from the curative sector to the preventive medicine system in Viet Nam. Methods: In 2016, we conducted 18 semi-structured in-depth interviews and 9 focus group discussions with representatives from the curative and preventive medicine sectors in four provinces. We transcribed the interviews and focus group discussions and conducted a thematic analysis of the factors that appeared to affect public health event reporting. Results: We identified five major themes. Firstly, the lack of a legal framework to guide reporting meant there was an over-reliance on internal procedures. Secondly, participants reported the importance of an enabling environment to facilitate reporting such as leadership support and having focal points for reporting. Thirdly, potential benefits for reporting were seen such as support during outbreaks and receiving feedback. Fourthly, some challenges prohibited timely reporting such as not perceiving reporting to be the task of the curative sector and hesitancy to report without laboratory confirmation. Finally, the limited resources and specialist capacities in remote areas hindered timely detection and reporting of unusual events. Discussion: This study identified potential opportunities to promote the detection and reporting of unusual events from health care workers to the public health sector, and thus improving the overall health security system in Viet Nam and beyond.

Abstract Background In 2016–2017, Vietnam’s Ministry of Health (MoH) implemented an event-based surveillance (EBS) pilot project in six provinces as part of Global Health Security Agenda (GHSA) efforts. This manuscript describes development and design of tools for monitoring and evaluation (M&E) of EBS in Vietnam. Methods A strategic EBS framework was developed based on the EBS implementation pilot project’s goals and objectives. The main process and outcome components were identified and included input, activities, outputs, and outcome indicators. M&E tools were developed to collect quantitative and qualitative data. The tools included a supervisory checklist, a desk review tool, a key informant interview guide, a focus group discussion guide, a timeliness form, and an online acceptability survey. An evaluation team conducted field visits for assessment of EBS 5–9 months after implementation. Results The quantitative data collected provided evidence on the number and type of events that were being reported, the timeliness of the system, and the event-to-signal ratio. The qualitative and subjective data collected helped to increase understanding of the system’s field utility and acceptance by field staff, reasons for non-compliance with established guidelines, and other factors influencing implementation. Conclusions The use of M&E tools for the EBS pilot project in Vietnam provided data on signals and events reported, timeliness of reporting and response, perceptions and opinions of implementers, and fidelity of EBS implementation. These data were valuable for Vietnam’s MoH to understand the function of the EBS program, and the success and challenges of implementing this project in Vietnam.

In our inter-connected world, health-care professionals are the first line of defence to identify emerging diseases and public health events for rapid response. In Vietnam, event-based surveillance (EBS), critical for the early detection of emerging disease outbreaks and acute public health events, has been limited to media-based EBS until recently. In 2017–2018, the Ministry of Health of Vietnam, in collaboration with the World Health Organisation and the US Centres for Disease Control and Prevention, designed, implemented, and evaluated a hospital EBS demonstration pilot in six hospitals in two provinces in Vietnam. After the 9-month implementation period, we conducted a logbook review, eight interviews, and six focus group discussions with hospital and preventive medicine staff, and conducted thematic and descriptive analysis. During the implementation period, 11 signals were reported and confirmed as true events. Of the 11 signals, majority (N = 8, 72.7%) were detected in ICU, followed by the outpatient department (N = 2, 18.2%). The most common signal were clusters of food poisoning (N = 4, 36.4%). All (100%) signals were reported, risk-assessed, and responded to within 24 hours of signal detection. The hospital and preventive medicine staff reported that one of the main benefits of the pilot was their improved mutual relationship. This pilot formalised hospital event-based surveillance through a legal framework, standard operating procedures, a formal feedback mechanism to hospitals to facilitate a two-way conversation, and providing additional training and continued sensitisation. Most importantly, it fostered a trusting relationship between the curative medicine and public health sectors, marking an important step towards advancing the national event-based surveillance system in Vietnam.

We describe the process and experience of implementing a Community event-based Surveillance (CEBS) pilot project in one district in Tamil Nadu, India. The project was implemented by National Institute of Epidemiology (NIE) in collaboration with the Tamil Nadu State Public Health Department and US Centres for Disease Control and Prevention. The design and process of implementation of the pilot project was developed in collaboration with the Tamil Nadu State Public Health Department. Training materials and an SMS/phone call-based system was developed for community-level reporting. Data pertaining to signals, verified events and response were collected from April – December 2017 and February – December 2019. The frequency of reported signals, the proportion of verified events and the percentage/type of events responded by the health staff were computed. The stakeholders agreed on seven signals for detection of events. Three hundred health workers, 85 doctors and 8214 volunteers were trained. A total of 144 signals were reported of which the three most commonly reported signals were fever with rash (35%), clusters of similar illness (26%) and death of three or more animals or birds in one week (23%). Among the 25 events requiring action, 16 were not reported from existing surveillance systems. The current project demonstrated that CEBS can add value to the existing surveillance systems by engaging the communities to detect and report. Although the current pilot project was implemented in only one district, many important lessons were learnt including, the challenges that should be mitigated before expansion. The State Level leadership is actively exploring ways to strengthen a culture of reporting by initiating programmes that routinely and publicly acknowledge and appreciate reporters and to actively sensitise communities to reduce stigma of reporting.

Epidemic intelligence activities are undertaken by the WHO Regional Office for Africa to support member states in early detection and response to outbreaks to prevent the international spread of diseases. We reviewed epidemic intelligence activities conducted by the organisation from 2017 to 2020, processes used, key results and how lessons learned can be used to strengthen preparedness, early detection and rapid response to outbreaks that may constitute a public health event of international concern. A total of 415 outbreaks were detected and notified to WHO, using both indicator-based and event-based surveillance. Media monitoring contributed to the initial detection of a quarter of all events reported. The most frequent outbreaks detected were vaccine-preventable diseases, followed by food-and-water-borne diseases, vector-borne diseases and viral hemorrhagic fevers. Rapid risk assessments generated evidence and provided the basis for WHO to trigger operational processes to provide rapid support to member states to respond to outbreaks with a potential for international spread. This is crucial in assisting member states in their obligations under the International Health Regulations (IHR) (2005). Member states in the region require scaled-up support, particularly in preventing recurrent outbreaks of infectious diseases and enhancing their event-based surveillance capacities with automated tools and processes. [ABSTRACT FROM AUTHOR]

• Aligning risk management to timely policy planning via rapid risk assessments led to effective response to COVID-19. • Robust event-based surveillance system contributed to early detection of the COVID-19 outbreak. • A whole-of-government approach achieved policy coherence and increased efficiency in COVID-19 control. Event-based surveillance and rapid risk assessment for acute public health events are essential in emerging infectious disease control. Since detecting the unusual signal in Wuhan in December 2019, Taiwan has been aligning risk management to policy planning via conducting regular risk assessments to combat the coronavirus disease 2019 (COVID-19). This article aims to provide some insights into Taiwan's experiences and corresponding actions for the outbreak. The COVID-19 risk level in Taiwan was raised to "moderate-to-high" in mid-January 2020 when neighboring countries had reported cases and the human-to-human transmission became obvious. The risk level became "high" on 24 January due to China's escalating epidemic situation and imposed a lockdown in Wuhan. We learned that the commander recognized the importance of risk assessments and considered advice from the experts was crucial in making the correct decision at the early stage of the crisis. Given the surge of COVID-19 cases globally, understanding the evidence-driven mobilizations via detailed risk assessments in Taiwan may be an example worth considering for other countries. We believe that strengthening a global epidemic intelligence network and sharing information in a timely and transparent manner are essential for confronting new challenges of COVID-19 and other emerging infectious diseases. [ABSTRACT FROM AUTHOR]

Copyright of Eastern Mediterranean Health Journal is the property of World Health Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We describe the process and experience of implementing a Community event-based Surveillance (CEBS) pilot project in one district in Tamil Nadu, India. The project was implemented by National Institute of Epidemiology (NIE) in collaboration with the Tamil Nadu State Public Health Department and US Centres for Disease Control and Prevention. The design and process of implementation of the pilot project was developed in collaboration with the Tamil Nadu State Public Health Department. Training materials and an SMS/phone call-based system was developed for community-level reporting. Data pertaining to signals, verified events and response were collected from April – December 2017 and February – December 2019. The frequency of reported signals, the proportion of verified events and the percentage/type of events responded by the health staff were computed. The stakeholders agreed on seven signals for detection of events. Three hundred health workers, 85 doctors and 8214 volunteers were trained. A total of 144 signals were reported of which the three most commonly reported signals were fever with rash (35%), clusters of similar illness (26%) and death of three or more animals or birds in one week (23%). Among the 25 events requiring action, 16 were not reported from existing surveillance systems. The current project demonstrated that CEBS can add value to the existing surveillance systems by engaging the communities to detect and report. Although the current pilot project was implemented in only one district, many important lessons were learnt including, the challenges that should be mitigated before expansion. The State Level leadership is actively exploring ways to strengthen a culture of reporting by initiating programmes that routinely and publicly acknowledge and appreciate reporters and to actively sensitise communities to reduce stigma of reporting. [ABSTRACT FROM AUTHOR]

In our inter-connected world, health-care professionals are the first line of defence to identify emerging diseases and public health events for rapid response. In Vietnam, event-based surveillance (EBS), critical for the early detection of emerging disease outbreaks and acute public health events, has been limited to media-based EBS until recently. In 2017–2018, the Ministry of Health of Vietnam, in collaboration with the World Health Organisation and the US Centres for Disease Control and Prevention, designed, implemented, and evaluated a hospital EBS demonstration pilot in six hospitals in two provinces in Vietnam. After the 9-month implementation period, we conducted a logbook review, eight interviews, and six focus group discussions with hospital and preventive medicine staff, and conducted thematic and descriptive analysis. During the implementation period, 11 signals were reported and confirmed as true events. Of the 11 signals, majority (N = 8, 72.7%) were detected in ICU, followed by the outpatient department (N = 2, 18.2%). The most common signal were clusters of food poisoning (N = 4, 36.4%). All (100%) signals were reported, risk-assessed, and responded to within 24 hours of signal detection. The hospital and preventive medicine staff reported that one of the main benefits of the pilot was their improved mutual relationship. This pilot formalised hospital event-based surveillance through a legal framework, standard operating procedures, a formal feedback mechanism to hospitals to facilitate a two-way conversation, and providing additional training and continued sensitisation. Most importantly, it fostered a trusting relationship between the curative medicine and public health sectors, marking an important step towards advancing the national event-based surveillance system in Vietnam. [ABSTRACT FROM AUTHOR]

Background: In 2016-2017, Vietnam's Ministry of Health (MoH) implemented an event-based surveillance (EBS) pilot project in six provinces as part of Global Health Security Agenda (GHSA) efforts. This manuscript describes development and design of tools for monitoring and evaluation (M&E) of EBS in Vietnam.Methods: A strategic EBS framework was developed based on the EBS implementation pilot project's goals and objectives. The main process and outcome components were identified and included input, activities, outputs, and outcome indicators. M&E tools were developed to collect quantitative and qualitative data. The tools included a supervisory checklist, a desk review tool, a key informant interview guide, a focus group discussion guide, a timeliness form, and an online acceptability survey. An evaluation team conducted field visits for assessment of EBS 5-9 months after implementation.Results: The quantitative data collected provided evidence on the number and type of events that were being reported, the timeliness of the system, and the event-to-signal ratio. The qualitative and subjective data collected helped to increase understanding of the system's field utility and acceptance by field staff, reasons for non-compliance with established guidelines, and other factors influencing implementation.Conclusions: The use of M&E tools for the EBS pilot project in Vietnam provided data on signals and events reported, timeliness of reporting and response, perceptions and opinions of implementers, and fidelity of EBS implementation. These data were valuable for Vietnam's MoH to understand the function of the EBS program, and the success and challenges of implementing this project in Vietnam. [ABSTRACT FROM AUTHOR]

Background: The International Health Regulations state that early detection and immediate reporting of unusual health events is important for early warning and response systems. Objective: To describe a pilot surveillance program established in health facilities in Yaoundé, Cameroon in 2017 which aimed to enable detection and reporting of public health events. Methods: Cameroon's Ministry of Health, in partnership with the US Centers for Disease Control and Prevention, Cameroon Pasteur Center, and National Public Health Laboratory, implemented event‐based surveillance (EBS) in nine Yaoundé health facilities. Four signals were defined that could indicate possible public health events, and a reporting, triage, and verification system was established among partner organizations. A pre‐defined laboratory algorithm was defined, and a series of workshops trained health facilities, laboratory, and public health staff for surveillance implementation. Results: From May 2017 to January 2018, 30 signals were detected, corresponding to 15 unusual respiratory events. All health facilities reported a signal at least once, and more than three‐quarters of health facilities reported ≥2 times. Among specimens tested, the pathogens detected included Klebsiella pneumoniae, Moraxella catarrhalis, Streptococcus pneumoniae, Haemophilus influenza, Staphylococcus aureus, Pneumocystis jiroveci, influenza A (H1N1) virus, rhinovirus, and adenovirus. Conclusions: The events detected in this pilot were caused by routine respiratory bacteria and viruses, and no novel influenza viruses or other emerging respiratory threats were identified. The surveillance system, however, strengthened relationships and communication linkages between health facilities and public health authorities. Astute clinicians can play a critical role in early detection and EBS is one approach that may enable reporting of emerging outbreaks and public health events. [ABSTRACT FROM AUTHOR]

Copyright of Eastern Mediterranean Health Journal is the property of World Health Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study piloted an event-based surveillance system at the health centre (HC) level in Ethiopia. The system collects rumours in the community and registers them in rumour logbooks to record events of disease outbreaks and public health emergencies. Descriptive analysis was conducted on the events captured at the 59 study HCs in the Amhara Region in north-western Ethiopia between October 2013 and November 2014. A total of 126 rumours were registered at two thirds of the HCs during the study period. The average event reporting time was 3.8 days; response time of the HCs was 0.6 days, resulting in a total response time of 4.4 days. The most commonly reported rumours were measles-related (n = 90, 71%). These rumours followed a similar pattern of measles cases reported in the routine surveillance system. The largest proportion of rumours were reported by community members (n = 38, 36%) followed by health post workers (n = 36, 29%) who were normally informed by the community members about the rumours. This surveillance system was established along with an existing indicator-based surveillance system and was simple to implement. The implementation cost was minimal, requiring only printing and distribution of rumour logbooks to the HCs and brief orientations to focal persons. In countries where routine surveillance is still weak, an event-based surveillance system similar to this should be considered as a supplementary tool for disease monitoring.

Introduction: Event-based surveillance (EBS) is a critical component of Early Warning, Alert and Response (EWAR) capacity needed for outbreak prevention and control. To better understand existing EBS and monitor the progress of capacity-building efforts over time, Africa CDC developed an EBS scorecard as part of a revision to the EBS Framework., Methods: We distributed the scorecard to African Union (AU) Member States (MSs). Survey responses from the MSs' human health sector were aggregated, cleaned, and analysed. MS, regional, and continental EBS capacity was assessed., Results: Between 21 July 2022 and 4 April 2023, a total of 63 respondents representing 49 (89%) of 55 MSs completed the survey. Given Africa CDC's public health mandate, we acknowledged the importance of One Health collaboration in MSs but focused on and analysed only the human health sector responses. Thirty-four (71%) MSs stated having EBS in place; hotline was the most common type of EBS implemented (76%). Seventeen (50%) MSs reported multisectoral, One Health collaboration as part of EBS implementation. Scorecard outcomes showed a minimal (score of <60%) to average (score between 60-80%) level of EBS capacity in 29 and five (5) MSs respectively., Discussion: Current EBS capacity levels need to be strengthened in Africa to ensure the continent remains prepared for future public health threats. The Africa CDC EBS scorecard provides a useful way to measure and track this capacity over time. Results can be used to advocate for and target resources for capacity building to foster public health emergency preparedness efforts., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors. Published by Elsevier Inc.)

Under the International Health Regulations (2005), Member States are required to develop capacity in event-based surveillance (EBS). The Papua New Guinea National Department of Health established an EBS system during the influenza pandemic in August 2009. We review its performance from August 2009 to November 2012, sharing lessons that may be useful to other low-resource public health practitioners working in surveillance. We examined the EBS system’s event reporting, event verification and response. Characteristics examined included type of event, source of information, timeliness, nature of response and outcome. Sixty-one records were identified. The median delay between onset of the event and date of reporting was 10 days. The largest proportion of reports (39%) came from Provincial Health Offices, followed by direct reports from clinical staff (25%) and reports in the media (11%). Most (84%) of the events were substantiated to be true public health events, and 56% were investigated by the Provincial Health Office alone. A confirmed or probable etiology could not be determined in 69% of true events. EBS is a simple strategy that forms a cornerstone of public health surveillance and response particularly in low-resource settings such as Papua New Guinea. There is a need to reinforce reporting pathways, improve timeliness of reporting, expand sources of information, improve feedback and improve diagnostic support capacity. For it to be successful, EBS should be closely tied to response.