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 Nvivoâ 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.
Subject(s)
Digital Health , Disease Outbreaks , Animals , Humans , Europe/epidemiology , Disease Outbreaks/prevention & control , Public Health , IntelligenceABSTRACT
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.
Subject(s)
Disease Outbreaks , Animals , Humans , Cross-Sectional Studies , Disease Outbreaks/prevention & control , Intelligence , Public Health , Surveys and QuestionnairesABSTRACT
Island communities are interesting study sites for microbial evolution during epidemics, as their insular nature reduces the complexity of the population's connectivity. This was particularly true on Reunion Island during the first half of 2021, when international travel was restricted in order to mitigate the risk for SARS-CoV-2 introductions. Concurrently, the SARS-CoV-2 Beta variant became dominant and started to circulate at high levels for several months before being completely replaced by the Delta variant as of October 2021. Here, we explore some of the particularities of SARS-CoV-2 genomic evolution within the insular context of Reunion Island. We show that island isolation allowed the amplification and expansion of unique genetic lineages that remained uncommon across the globe. Islands are therefore potential hotspots for the emergence of new genetic variants, meaning that they will play a key role in the continued evolution and propagation of COVID-19 as the pandemic persists.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/epidemiology , Genomics , PandemicsABSTRACT
In January 2021, after detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, genomic surveillance was established on Réunion Island to track the introduction and spread of SARS-CoV-2 lineages and variants of concern. This system identified 22 SARS-CoV-2 lineages, 71% of which were attributed to the Beta variant.
Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , France/epidemiology , Humans , Reunion/epidemiology , SARS-CoV-2/geneticsABSTRACT
PADI-web (Platform for Automated extraction of animal Disease Information from the web) is a biosurveillance system dedicated to monitoring online news sources for the detection of emerging animal infectious diseases. PADI-web has collected more than 380,000 news articles since 2016. Compared to other existing biosurveillance tools, PADI-web focuses specifically on animal health and has a fully automated pipeline based on machine-learning methods. This paper presents the new functionalities of PADI-web based on the integration of: (i) a new fine-grained classification system, (ii) automatic methods to extract terms and named entities with text-mining approaches, (iii) semantic resources for indexing keywords and (iv) a notification system for end-users. Compared to other biosurveillance tools, PADI-web, which is integrated in the French Platform for Animal Health Surveillance (ESA Platform), offers strong coverage of the animal sector, a multilingual approach, an automated information extraction module and a notification tool configurable according to end-user needs.
ABSTRACT
Event-based surveillance (EBS) systems monitor a broad range of information sources to detect early signals of disease emergence, including new and unknown diseases. In December 2019, a newly identified coronavirus emerged in Wuhan (China), causing a global coronavirus disease (COVID-19) pandemic. A retrospective study was conducted to evaluate the capacity of three event-based surveillance (EBS) systems (ProMED, HealthMap and PADI-web) to detect early COVID-19 emergence signals. We focused on changes in online news vocabulary over the period before/after the identification of COVID-19, while also assessing its contagiousness and pandemic potential. ProMED was the timeliest EBS, detecting signals one day before the official notification. At this early stage, the specific vocabulary used was related to 'pneumonia symptoms' and 'mystery illness'. Once COVID-19 was identified, the vocabulary changed to virus family and specific COVID-19 acronyms. Our results suggest that the three EBS systems are complementary regarding data sources, and all require timeliness improvements. EBS methods should be adapted to the different stages of disease emergence to enhance early detection of future unknown disease outbreaks.
Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , Communicable Diseases, Emerging/diagnosis , Communicable Diseases, Emerging/epidemiology , SARS-CoV-2 , Animals , China/epidemiology , Humans , Population Surveillance , Retrospective StudiesABSTRACT
Pohnpei State's Division of Primary Health Care implemented enhanced surveillance for early warning and detection of disease to support the 8th Micronesian Games (the Games) in July 2014. The surveillance comprised 11 point-of-care sentinel sites around Pohnpei, Federated States of Micronesia, collecting data daily for eight syndromes using standard case definitions. Each sentinel site reported total acute care encounters, total syndrome cases and the total for each syndrome. A public health response, including epidemiological investigation and laboratory testing, followed when syndrome counts reached predetermined threshold levels. The surveillance was implemented using the web-based Suite for Automated Global Electronic bioSurveillance Open-ESSENCE (SAGES-OE) application that was customized for the Games. Data were summarized in daily situation reports (SitReps) issued to key stakeholders and posted on PacNet, a Pacific public health e-mail network. Influenza-like illness (ILI) was the most common syndrome reported (55%, n = 225). Most syndrome cases (75%) were among people from Pohnpei. Only 30 cases out of a total of 408 syndrome cases (7%) presented with acute fever and rash, despite the large and ongoing measles outbreak at the time. No new infectious disease outbreak was recorded during the Games. Peaks in diarrhoeal and ILI cases were followed up and did not result in widespread transmission. The technology was a key feature of the enhanced surveillance. The introduction of the web-based tool greatly improved the timeliness of data entry, analysis and SitRep dissemination, providing assurance to the Games organizers that communicable diseases would not adversely impact the Games.
Subject(s)
Communicable Diseases/epidemiology , Crowding , Public Health Surveillance/methods , Sports , Humans , Micronesia/epidemiology , SyndromeABSTRACT
The Ministry of Health in Samoa, in partnership with the Pacific Community, successfully implemented enhanced surveillance for the high-profile Third United Nations Conference on Small Island Developing States held concurrently with the popular local Teuila festival during a widespread chikungunya outbreak in September 2014. Samoa's weekly syndromic surveillance system was expanded to 12 syndromes and 10 sentinel sites from four syndromes and seven sentinel sites; sites included the national hospital, four private health clinics and three national health service clinics. Daily situation reports were produced and were disseminated through PacNet (the e-mail alert and communication tool of the Pacific Public Health Surveillance Network) together with daily prioritized line lists of syndrome activity to facilitate rapid response and investigation by the Samoan EpiNet team. Standard operating procedures for surveillance and response were introduced, together with a sustainability plan, including a monitoring and evaluation framework, to facilitate the transition of the mass gathering surveillance improvements to routine surveillance. The enhanced surveillance performed well, providing vital disease early warning and health security assurance. A total of 2386 encounters and 708 syndrome cases were reported. Influenza-like illness was the most frequently seen syndrome (17%). No new infectious disease outbreaks were recorded. The experience emphasized: (1) the need for a long lead time to pilot the surveillance enhancements and to maximize their sustainability; (2) the importance of good communication between key stakeholders; and (3) having sufficient staff dedicated to both surveillance and response.
Subject(s)
Chikungunya Fever/prevention & control , Chikungunya virus , Communicable Disease Control/methods , Congresses as Topic , Disease Outbreaks , Public Health Surveillance , Sentinel Surveillance , Chikungunya Fever/epidemiology , Chikungunya Fever/transmission , Chikungunya Fever/virology , Holidays , Hospitals , Humans , Influenza, Human/complications , Public Health , Samoa/epidemiology , Syndrome , United NationsABSTRACT
BACKGROUND: Dengue is a mosquito-borne virus that causes extensive morbidity and economic loss in many tropical and subtropical regions of the world. Often present in cities, dengue virus is rapidly spreading due to urbanization, climate change and increased human movements. Dengue cases are often heterogeneously distributed throughout cities, suggesting that small-scale determinants influence dengue urban transmission. A better understanding of these determinants is crucial to efficiently target prevention measures such as vector control and education. The aim of this study was to determine which socioeconomic and environmental determinants were associated with dengue incidence in an urban setting in the Pacific. METHODOLOGY: An ecological study was performed using data summarized by neighborhood (i.e. the neighborhood is the unit of analysis) from two dengue epidemics (2008-2009 and 2012-2013) in the city of Nouméa, the capital of New Caledonia. Spatial patterns and hotspots of dengue transmission were assessed using global and local Moran's I statistics. Multivariable negative binomial regression models were used to investigate the association between dengue incidence and various socioeconomic and environmental factors throughout the city. PRINCIPAL FINDINGS: The 2008-2009 epidemic was spatially structured, with clusters of high and low incidence neighborhoods. In 2012-2013, dengue incidence rates were more homogeneous throughout the city. In all models tested, higher dengue incidence rates were consistently associated with lower socioeconomic status (higher unemployment, lower revenue or higher percentage of population born in the Pacific, which are interrelated). A higher percentage of apartments was associated with lower dengue incidence rates during both epidemics in all models but one. A link between vegetation coverage and dengue incidence rates was also detected, but the link varied depending on the model used. CONCLUSIONS: This study demonstrates a robust spatial association between dengue incidence rates and socioeconomic status across the different neighborhoods of the city of Nouméa. Our findings provide useful information to guide policy and help target dengue prevention efforts where they are needed most.
Subject(s)
Dengue/epidemiology , Dengue/transmission , Disease Transmission, Infectious , Environment , Socioeconomic Factors , Adult , Cities/epidemiology , Humans , Incidence , New Caledonia/epidemiology , Topography, MedicalABSTRACT
Established in the early 1970 as a participatory wildlife production area, the Nazinga Game Ranch turned into an island of conservation surrounded by cultivation. We asked ourselves how long-term ungulate trends are affected in a context of continuous human pressure. To find out, we compiled and analysed the data of yearly line-transect counts of mammals carried out since 1985. Results showed that large species such as the elephant (Loxodonta africana) and large antelopes increased or showed stable populations. In contrast, medium and small ungulates showed continuously decreasing trends. During the same period, rainfall, water availability from artificial water points and the crop encroaching outside Nazinga Game Ranch increased. After an initial significant reduction, illegal human signs increased. However, we showed that human signs were positively correlated with the abundance of large ungulates but negatively correlated with the abundance of medium and small ones. In conclusion, this study showed that some isolated mammal populations could be restored and maintained in the long term, in spite of being surrounded by highly cultivated areas.