Event-based Surveillance Research Articles

Toward Public Health Resilience in the Eastern Mediterranean Region: Findings From the Seventh Eastern Mediterranean Public Health Network Regional Conference.

The resilience of public health in the Eastern Mediterranean Region (EMR) varies from country to country, mostly based on the governmental and financial situation of the countries. With the theme of Towards Public Health Resilience in the EMR: Breaking Barriers, the seventh Eastern Mediterranean Public Health Network regional conference, held from November 14 to 18, 2021, was dedicated to exploring ways for achieving public health resilience. A total of 101 oral presentations and 13 poster presentations were presented on various public health topics. The conference included 6 keynote sessions, 10 roundtable sessions, and 5 preconference workshops. The preconference workshops were conducted on border health; the mobilization of Field Epidemiology Training Program (FETP) residents and graduates and rapid responders in EMR countries; continuous professional development for the public health workforce; brucellosis surveillance using the "One Health" approach; and strategies to integrate and use noncommunicable diseases data sources. The roundtable sessions included discussions on the following topics: the role of FETPs in responding to COVID-19, institutionalization of rapid response to public health emergencies, health systems resilience, integration of early warning and response with event-based and indicator-based surveillance, sustaining international health regulations, strengthening the "One Health" approach, the anticipated future of public health in the post COVID-19 era, supporting public health research capacity in a diverse region, and COVID-19 vaccines and routine immunization synergies and drawbacks. The keynote speaker sessions covered topics on essential public health functions and the universal health coverage challenge in the EMR, lessons from the US COVID-19 public health response, learning from COVID-19, reshaping public health after the pandemic era, COVID-19 resilient primary health care, and the cohesion of society during and after a pandemic. The conference sessions provided highly promising opportunities to explore ways to achieve such goals in the EMR and shed light on the latest scientific findings, important lessons learned, and discussions on the ways in which current barriers can be broken down through coordination and collaboration.

Event-based surveillance: Providing early warning for communicable disease threats

Event-based surveillance: Providing early warning for communicable disease threats

Acute Kidney Injury Among Children Likely Associated with Diethylene Glycol-Contaminated Medications - The Gambia, June-September 2022.

On July 26, 2022, a pediatric nephrologist alerted The Gambia's Ministry of Health (MoH) to a cluster of cases of acute kidney injury (AKI) among young children at the country's sole teaching hospital, and on August 23, 2022, MoH requested assistance from CDC. CDC epidemiologists arrived in The Gambia, a West African country, on September 16 to assist MoH in characterizing the illness, describing the epidemiology, and identifying potential causal factors and their sources. Investigators reviewed medical records and interviewed caregivers to characterize patients' symptoms and identify exposures. The preliminary investigation suggested that various contaminated syrup-based children's medications contributed to the AKI outbreak. During the investigation, MoH recalled implicated medications from a single international manufacturer. Continued efforts to strengthen pharmaceutical quality control and event-based public health surveillance are needed to help prevent future medication-related outbreaks.

An Evaluation Framework for Comparing Epidemic Intelligence Systems

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.

Digital surveillance in Latin American diseases outbreaks: information extraction from a novel Spanish corpus

BackgroundIn 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.ResultsWe 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.ConclusionsThe 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.

The Forms, Challenges and Strength of the Monkeypox Surveillance System in Nigeria

Monkeypox is now a disease of global public health concern, making it cut across boundaries into different countries, continents and spread worldwide. However, it originated in the Democratic Republic of Congo as a human pathogen in 1970, with the first case reported in Nigeria in 1971. The World Health Organization recently declared Nigeria the country with the highest burden of monkeypox-confirmed cases and deaths in Africa for the current outbreak. This study aimed to identify forms, challenges, strengths, and ways to further strengthen the surveillance system of monkeypox in Nigeria. We conducted a rapid narrative review of articles published in English on monkeypox between January 2018 and October 2022. Google Scholar and PubMed were searched with the following terms: "Monkeypox", "Surveillance system", "Strengthening", "Challenges" "Nigeria" and relevant publications were reviewed. The forms of surveillance systems in Nigeria include Indicator-based and Event-based surveillance, contact tracing, laboratory-based surveillance, sero-surveillance, and mortality surveillance. Shortage of highly skilled staff in public health interventions, insufficient testing capacities, power instability, poor healthcare systems and stigmatization from communities with misinformation, and co-epidemic surveillance burden in Nigeria are some of the challenges contributing to weak surveillance in the country. The Nigerian governments must focus on investing in surveillance systems and bolster preparedness to stem the rapid spread of infectious diseases. Strengthening the surveillance system in the country as a response intervention for monkeypox is no longer a matter of option in Nigeria but of necessity to prevent the forecasted effect the incidence portends.

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

BackgroundEvent-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. MethodsThe 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.ResultsSudan 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.ConclusionThe 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.

Implementation Level of Event-Based Surveillance (EBS) as Surveillance Core Capacity Under International Health Regulation in Sudan, 2020: Cross-Sectional Study

Background: Surveillance system of infectious diseases and event is recognized as the cornerstone of public health decision-making and practice additionally, the international health regulation requested counties to implement other type of surveillance to support the routine surveillance system and to increase the detection rate and sensitivity in reporting the diseases, event, or any public health emergency with international concern (PHEIC). The aim of this study to assess the implementation level of event-based surveillance systems to ensuring that the system implemented efficiently and effectively. Methods: descriptive cross sectional institutional based study conducted for all 18 surveillance officer at states to assess the implementation level of event-based surveillance system as core capacity under the international health regulation 2005 (IHR), Data was collected using a per-prepared and pretested questionnaire followed WHO/EMRO tools for surveillance staff at state level felt through field visit and phone calls, data collection also cover the community based surveillance and surveillance system at point of entry as part of event based surveillance, interview done for surveillance focal person at federal level. Data were analyzed using Statistical Packages for Social Sciences (SPSS) (version 20). Written and verbal consents were obtained from all participants as appropriate. Results: Event based surveillance started in 2016 endorsement and approval of guidelines SOPs and training materials has been develop in 2017 so the study showed significant positive changes in implementation of this system for that the results showed the system implemented in all 18 states, availability of guidelines and SOPs at state level 72.2%, completeness, and timeliness of system data 94.4%, designated focal person in the surveillance structure at state level 94.4%. community Based Surveillance (CBS) implementation Results at states level -Sudan from 2017 – 2020 the result showed the system has been implemented in 17 states (94.4%), the percentage of assigned focal person for the system was 94.1 – trained volunteer at community level 94.4% and availability of system guidelines was 94.1%, the availability of system SOPs 88.2%. The study results also showed the percentage of 94.4 for definition of CBS syndromes, immediate response for event reported was 94.4%, Daily and weekly reports completed send by community volunteers was 94.4% and availability of reporting forms was 94.1% also percentage of 70.6% for system data base and shared the report with the partners. Point of entry Surveillance (PoE) implementation at the states level Results showed that the surveillance at points of entry has been fully implemented in 6 state 46.1% which it had point of entry and it has been designated by IHR, the system had focal person, the training done for all staff with availability of system guidelines and SOPs all this done by 100% 83.3% of point of entry reported Daily and weekly reports, the percentage of report completeness and timeliness was 66.7% with 83.3% for the zero report when no event of cases reported, availability of system data base and documentation for the events and cases reported through the system was 83.3%. Conclusion: The study showed significant positive changes in implementation of event-based surveillance system under the international health regulation, based on the finding the study recommended that, rapid and early response for the reported cases and rumors or any other event from the locality and state level, Regular refresh, and basic training for surveillance staff internally and external training and strengthen the data management mechanism.

Global Variations in Event-Based Surveillance for Disease Outbreak Detection: Time Series Analysis.

Robust and flexible infectious disease surveillance is crucial for public health. Event-based surveillance (EBS) was developed to allow timely detection of infectious disease outbreaks by using mostly web-based data. Despite its widespread use, EBS has not been evaluated systematically on a global scale in terms of outbreak detection performance. The aim of this study was to assess the variation in the timing and frequency of EBS reports compared to true outbreaks and to identify the determinants of variability by using the example of seasonal influenza epidemic in 24 countries. We obtained influenza-related reports between January 2013 and December 2019 from 2 EBS systems, that is, HealthMap and the World Health Organization Epidemic Intelligence from Open Sources (EIOS), and weekly virological influenza counts for the same period from FluNet as the gold standard. Influenza epidemic periods were detected based on report frequency by using Bayesian change point analysis. Timely sensitivity, that is, outbreak detection within the first 2 weeks before or after an outbreak onset was calculated along with sensitivity, specificity, positive predictive value, and timeliness of detection. Linear regressions were performed to assess the influence of country-specific factors on EBS performance. Overall, while monitoring the frequency of EBS reports over 7 years in 24 countries, we detected 175 out of 238 outbreaks (73.5%) but only 22 out of 238 (9.2%) within 2 weeks before or after an outbreak onset; in the best case, while monitoring the frequency of health-related reports, we identified 2 out of 6 outbreaks (33%) within 2 weeks of onset. The positive predictive value varied between 9% and 100% for HealthMap and from 0 to 100% for EIOS, and timeliness of detection ranged from 13% to 94% for HealthMap and from 0% to 92% for EIOS, whereas system specificity was generally high (59%-100%). The number of EBS reports available within a country, the human development index, and the country's geographical location partially explained the high variability in system performance across countries. We documented the global variation of EBS performance and demonstrated that monitoring the report frequency alone in EBS may be insufficient for the timely detection of outbreaks. In particular, in low- and middle-income countries, low data quality and report frequency impair the sensitivity and timeliness of disease surveillance through EBS. Therefore, advances in the development and evaluation and EBS are needed, particularly in low-resource settings.

Elaboration of a new framework for fine-grained epidemiological annotation

Event-based surveillance (EBS) gathers information from a variety of data sources, including online news articles. Unlike the data from formal reporting, the EBS data are not structured, and their interpretation can overwhelm epidemic intelligence (EI) capacities in terms of available human resources. Therefore, diverse EBS systems that automatically process (all or part of) the acquired nonstructured data from online news articles have been developed. These EBS systems (e.g., GPHIN, HealthMap, MedISys, ProMED, PADI-web) can use annotated data to improve the surveillance systems. This paper describes a framework for the annotation of epidemiological information in animal disease-related news articles. We provide annotation guidelines that are generic and applicable to both animal and zoonotic infectious diseases, regardless of the pathogen involved or its mode of transmission (e.g., vector-borne, airborne, by contact). The framework relies on the successive annotation of all the sentences from a news article. The annotator evaluates the sentences in a specific epidemiological context, corresponding to the publication date of the news article.

Public Health Workforce training Laboratorium: Pilot e-Learning course on CBE and PBL models

Abstract Background The National Institute of health (ISS), within the G20 Health Working Group, launched at March 2021 an innovative training Laboratorium, to strengthen the capacity and competencies of the Public Health Workforce (PHW) on prevention, preparedness and response to health crises. It was recognised in the G20 Declarations of Ministers of Health and Leaders and it was aimed to the development of training tools suitable for distance learning. ISS proposed the design of e-Learning courses based on an integration of WHO’s Competency-Based Education (CBE) and Problem Based Learning (PBL) models. Objectives Describe the design of a pilot e-Learning course based on CBE- PBL models, focused on Epidemic Intelligence (EI). Results The pilot e-Learning course “Use of Epidemic Intelligence systems with a particular focus on event-based surveillance for pandemic preparedness” will be delivered by ISS e-Learning platform https://www.eduiss.it. By the end of the course participants will be able to evaluate the potential use/applicability of EI systems, focusing on event-based surveillance for preparedness and early warning at country/institutional level. CBE is the basis for articulating the outcomes and identifying the required competencies and PBL for creating learning activities associated to learning outcomes. Interactive tools (exercise, web pages, quiz and other activities) are associated to learning objectives. The course is offered to public health professionals free of charge, in English language. About 16 hours are required to complete all the activities and receive attendance certification. Conclusions Continuously updated training of PHW is a hallmark to better face health challenges. In our proposal, the learning methodology integrates CBE vision with PBL approach, adapting both to e-Learning context. Aknowledement Pietro Carbone, Debora Guerrera, Federica Regini, Licia Bacciocchi, Stefania Bocci, Silvia Stacchini, Giovanna Failla - ISS, Rome Italy Key messages • Design an innovative e-learning course through synergic integration of two educational models crucial in public health, CBE and PBL. • Adapt e valorize CBE and PBL models in the context of e-Learning.

Use of Epidemic Intelligence from Open Sources for global event-based surveillance of infectious diseases for the Tokyo 2020 Olympic and Paralympic Games.

The establishment of enhanced surveillance systems for mass gatherings to detect infectious diseases that may be imported during an event is recommended. The World Health Organization Regional Office for the Western Pacific contributed to enhanced event-based surveillance for the Tokyo 2020 Olympic and Paralympic Games (the Games) by using Epidemic Intelligence from Open Sources (EIOS) to detect potential imported diseases and report them to the National Institute of Infectious Diseases (NIID), Japan. Daily screening of media articles on global infectious diseases was conducted using EIOS, which were systematically assessed to determine the likelihood of disease importation, spread and significant impact to Japan during the Games. Over 81 days of surveillance, 103 830 articles were screened by EIOS, of which 5441 (5.2%) met the selection criteria for initial assessment, with 587 (0.6%) assessed as signals and reported to NIID. None of the signals were considered to pose a significant risk to the Games based on three risk assessment criteria. While EIOS successfully captured media articles on infectious diseases with a likelihood of importation to and spread in Japan, a significant manual effort was required to assess the articles for duplicates and against the risk assessment criteria. Continued improvement of artificial intelligence is recommended to reduce this effort.

Integrated disease surveillance and response in humanitarian context: South Sudan experience.

Introductiondecades of instability continue to impact the implementation of the Integrated Disease Surveillance and Response (IDSR) strategy. The study reviewed the progress and outcomes of rolling out IDSR in South Sudan.Methodsthis descriptive cross-sectional study used epidemiological data for 2019, 2020, and other program data to assess indicators for the five surveillance components including surveillance priorities, core and support functions, and surveillance system structure and quality.ResultsSouth Sudan expanded the priority disease scope from 26 to 59 to align with national and regional epidemiological trends and the International Health Regulations (IHR) 2005. Completing the countrywide rollout of electronic Early Warning Alert and Response (EWARS) reporting has improved both the timeliness and completeness of weekly reporting to 78% and 90%, respectively, by week 39 of 2020 in comparison to a baseline of 54% on both timeliness and completeness of reporting in 2019. The National Public Health Laboratory confirmatory testing capacities have been expanded to include cholera, measles, HIV, tuberculosis (TB), influenza, Ebola, yellow fever, and Severe Acute Respiratory Syndrome 2 (SARS-COV-2). Rapid response teams have been established to respond to epidemics and pandemics.Conclusionsince 2006, South Sudan has registered progress towards using indicator and event-based surveillance and continues to strengthen IHR (2005) capacities. Following the adoption of third edition IDSR guidelines, the current emphasis entails maintaining earlier gains and strengthening community and event-based surveillance, formalizing cross-sectoral one-health engagement, optimal EWARS and District Health Information Systems (DHIS2) use, and strengthening cross-border surveillance. It is also critical that optimal government, and donors’ resources are dedicated to supporting health system strengthening and disease surveillance.

Evaluation of integrated disease surveillance and response (IDSR) and early warning and response network (EWARN) in South Sudan 2021.

IntroductionSouth Sudan has been implementing the Integrated Disease Surveillance and Response (IDSR) strategy since 2006, along with Early Warning and Alert Response and Network (EWARN). The IDSR/EWARN stakeholders commissioned an independent evaluation to establish performance at national, state, county, health facility, and community levels in the first half of 2021.Methodsthe evaluation was conducted between June and September 2021 (during the COVID-19 pandemic) and was based on the World Health Organization (WHO) protocols for monitoring and evaluating communicable disease surveillance and response systems and the guidelines for evaluating EWARN.Resultsintegrated disease surveillance and response/early warning and alert response and network indicator data showed improving timeliness and completeness from the beginning of 2021 to week 16 and then a slight depression of timeliness by week 32, while completeness remained high. Event-based surveillance was active at the beginning of 2021 and in week 32. However, there was inadequate sample collection to investigate acute watery diarrhea, bloody diarrhea, and acute jaundice syndrome alerts. Respondents in all cadres had substantial experience working in IDSR/EWARN. All respondents performed the various IDSR/EWARN tasks and duties as expected, but needed more resources and training.Conclusionwhile IDSR/EWARN is performing relatively well, confirmation of priority diseases by the laboratories needs to be strengthened. Health facilities need more regular supervision from the higher levels. Community health workers need more training on IDSR/EWARN. The whole IDSR/EWARN system needs more resources, particularly for communication and transport and to confirm priority diseases. Staff at all levels requested more training in IDSR/EWARN.

A Conceptual Framework for Representing Events Under Public Health Surveillance.

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.

Social Network Data and Epidemiological Intelligence: A Case Study of Avian Influenza

Purpose - Event Based Surveillance (EBS) systems detect and monitor diseases by analysing articles from online news papers and reports from health organizations (e.g. FAO, OIE, etc.). However, they partially integrate data from social networks, even though these data are present in large quantities on the web. The purpose of this study is to exploit social network data, such as Twitter and YouTube, to provide epidemiological and additional information for Avian Influenza surveillance. Methods & Materials - In this context, we propose new text-mining approaches combining lexical rules and statistical approaches in order to normalise textual data from Social Net- work ('h5 n8' - 'H5N8') and to correct errors from YouTube transcriptions (e.g. 'birth u' - 'bird u'). Another challenge consists of extracting epidemiological events automatically by identifying spatial entities (Where?), thematic entities (What?), and temporal information (When?). For this, we extended Named Entity Recognition (NER) tools like spaCy. Results - We collected 100 automatic transcripts of YouTube videos and 268 tweets in English dealing with avian influenza with dedicated API. We obtain encouraging results (i.e. accuracy around 0:6) in order to recognise automatically epidemiological information (e.g. hosts, symptoms, etc.) in textual data con- tents. Extraction of spatial information obtains better results (i.e. accuracy around 0:7). Conclusion – The final objective of this study consists of linking social media data based on these entities with official information from health organisations for the improvement of epidemiological monitoring.

Model of COVID-19 Surveillance System for a Community-industry Setting

Abstract This study aimed to design and test a COVID-19 surveillance system model for community-industry population. A prospective cohort study was conducted from May to December, 2020. Researchers designed a COVID-19 surveillance system and presented it to stakeholders from the community-industry setting in Lamphun and Chiang Mai provinces, Thailand. The model was adjusted following feedback and tested. The model was an Active surveillance for early Alert and rapid Action using Big data and mobile phone application technology for a Community-industry setting (3ABC model). The major components were active surveillance, community-based surveillance, event-based surveillance, and early warning and rapid response. A drive-thru testing unit was operated to enable early detection. Alerts and recommended action on individual and administrative levels were sent via an application and networks. In the testing of the model, risk assessment was initially conducted with regard to COVID-19 transmission in the factories. Researchers provided recommendations based on findings. The improvements included human resource management, systems, and structure. The 3ABC model work well as designed. The participants actively reported events daily including prevention and control activities, animal diseases (foot-and-mouth disease in buffalos and hog cholera), human diseases (dengue and chikungunya), and absent of COVID-19 outbreak. Only five quarantined COVID-19 cases whom were monitored. Daily reports of no abnormal event was also high (70.2% to 71.1%). It is practical and feasible to implement the 3ABC model in a community-industry setting. A further study for a longer period to verify its level of effectiveness should be done. Keywords: Infectious disease, Epidemic model, Surveillance, Mobile application, Model evaluation

Winning during a pandemic: epidemiology of SARS-CoV-2 during EURO2020 in Italy.

EURO2020 generated a growing media and population interest across the month period, that peaked with large spontaneous celebrations across the country upon winning the tournament. We retrospectively analysed data from the national surveillance system (indicator-based) and from event-based surveillance to assess how the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) changed in June-July 2021 and to describe cases and clusters linked with EURO2020. Widespread increases in transmission and case numbers, mainly among younger males, were documented in Italy, none were linked with stadium attendance. Vaccination coverage against SARS-CoV-2 was longer among cases linked to EURO2020 than among the general population. Transmission increased across the country, mainly due to gatherings outside the stadium, where, conversely, strict infection control measures were enforced. These informal 'side' gatherings were dispersed across the entire country and difficult to control. Targeted communication and control strategies to limit the impact of informal gatherings occurring outside official sites of mass gathering events should be further developed.

Establishing event-based surveillance system in Nigeria: a complementary information generating platform for improved public health performance, 2016.

Introductionevent-based surveillance (EBS) is a surveillance method involving systematic and prompt data collection on incidents of public health importance, and complements the current indicator-based surveillance system and the Integrated Disease Surveillance and Response System (IDSR). It also promotes a rapid assessment and response to public health emergencies in Nigeria, although there is a lack of information regarding the status of EBS among Public Health Stakeholders in Nigeria; hence our study aimed to assess the awareness, availability, and utility of EBS among Nigerian public health stakeholders.Methodswe conducted a cross-sectional study to assess the awareness, availability, functionality, and utilization of EBS in the 36 States in Nigeria, plus the Federal Capital Territory (FCT). We interviewed 53 stakeholders in disease surveillance and response using a self-administered, semi-structured questionnaire to obtain responses on the awareness of the event-based surveillance system, availability, and functionality. We also assessed the common structures used to report health-related events and the availability of minimum requirements for an event-based surveillance system. We performed descriptive statistics for the data obtained.Resultsthe majority of respondents were males and 37.7% were disease surveillance and notification officers (DSNOs). Awareness of EBS was poor with about half, 49% of the respondents reported hearing of EBS, but only 17% described it correctly. The overall level of availability of the EBS reporting structure was inadequate, 28.2% and poorly utilised in the States.Conclusionthe awareness, availability, and utilization of event-based surveillance systems are low in Nigeria. The government should improve the feasibility and utility of EBS in the States to enhance early disease detection and response.

Global event-based surveillance of chemical incidents

BackgroundThe number of chemicals in our society and in our daily lives continues to increase. Accompanying this is an increasing risk of human exposure to and injury from hazardous substances. Performing regular, structured surveillance of chemical incidents allows a greater awareness of the types of chemical hazards causing injury and the frequency of their occurrence, as well as providing a better understanding of exposures.ObjectiveThe objective of performing event-based surveillance (EBS) and capturing chemical incidents is to use this information to increase the situational awareness of chemical incidents, improve the management of these incidents and to inform measures to protect public health.MethodsThis paper describes a method for EBS for chemical incidents, including the sources used, storing the gathered information and subsequent analysis of potential trends in the data.ResultsWe describe trends in the type of incidents that have been detected, the chemicals involved in these incidents and the health effects caused, in different geographic regions of the world.SignificanceThe methodology presented here provides a rapid and simple means of identifying chemical incidents that can be set up rapidly and with minimal cost, the outputs of which can be used to identify emerging risks and inform preparedness planning, response and training for chemical incidents.