Epidemic intelligence in Europe: a user needs perspective to foster innovation in digital health surveillance.

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.

Epidemic intelligence activities among national public and animal health agencies: a European cross-sectional study.

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.

Crimean-Congo Hemorrhagic Fever Virus Antibodies among Livestock on Corsica, France, 2014-2016.

We conducted a serologic survey for Crimean-Congo hemorrhagic fever virus antibodies in livestock (cattle, sheep, and goats; N = 3,890) on Corsica (island of France) during 2014-2016. Overall, 9.1% of animals were seropositive, suggesting this virus circulates on Corsica. However, virus identification is needed to confirm these results.

Drivers of Rift Valley fever epidemics in Madagascar.

Rift Valley fever (RVF) is a vector-borne viral disease widespread in Africa. The primary cycle involves mosquitoes and wild and domestic ruminant hosts. Humans are usually contaminated after contact with infected ruminants. As many environmental, agricultural, epidemiological, and anthropogenic factors are implicated in RVF spread, the multidisciplinary One Health approach was needed to identify the drivers of RVF epidemics in Madagascar. We examined the environmental patterns associated with these epidemics, comparing human and ruminant serological data with environmental and cattle-trade data. In contrast to East Africa, environmental drivers did not trigger the epidemics: They only modulated local Rift Valley fever virus (RVFV) transmission in ruminants. Instead, RVFV was introduced through ruminant trade and subsequent movement of cattle between trade hubs caused its long-distance spread within the country. Contact with cattle brought in from infected districts was associated with higher infection risk in slaughterhouse workers. The finding that anthropogenic rather than environmental factors are the main drivers of RVF infection in humans can be used to design better prevention and early detection in the case of RVF resurgence in the region.

Tracking Rift Valley fever: From Mali to Europe and other countries, 2016.

On 16 September 2016, the World Health Organization confirmed a Rift Valley fever (RVF) outbreak in Niger. Epidemiological surveillance was reinforced among the French Armed Forces deployed in Niger and bordering countries: Chad, Mali and Burkina Faso. On 26 October, a probable case of RVF was reported in a service member sampled in Mali 3 weeks earlier. At the time the result was reported, the patient was on vacation on Martinique. An epidemiological investigation was conducted to confirm this case and identify other cases. Finally, the case was not confirmed, but three suspected cases of RVF were confirmed using serological and molecular testing. RVF viral RNA was detectable in whole blood for 57 and 67 days after onset of symptoms for two cases, although it was absent from plasma and serum. At the time of diagnosis, these cases had already returned from Mali to Europe. The infectivity of other arboviruses in whole blood has already been highlighted. That RVF virus has been detected in whole blood that long after the onset of symptoms (67 days) raises the question of its potential prolonged infectivity. Because of exposure to tropical infectious diseases during deployment, military populations could import emerging pathogens to Europe.

Mapping landscape friction to locate isolated tsetse populations that are candidates for elimination.

Tsetse flies are the cyclical vectors of deadly human and animal trypanosomes in sub-Saharan Africa. Tsetse control is a key component for the integrated management of both plagues, but local eradication successes have been limited to less than 2% of the infested area. This is attributed to either resurgence of residual populations that were omitted from the eradication campaign or reinvasion from neighboring infested areas. Here we focused on Glossina palpalis gambiensis, a riverine tsetse species representing the main vector of trypanosomoses in West Africa. We mapped landscape resistance to tsetse genetic flow, hereafter referred to as friction, to identify natural barriers that isolate tsetse populations. For this purpose, we fitted a statistical model of the genetic distance between 37 tsetse populations sampled in the region, using a set of remotely sensed environmental data as predictors. The least-cost path between these populations was then estimated using the predicted friction map. The method enabled us to avoid the subjectivity inherent in the expert-based weighting of environmental parameters. Finally, we identified potentially isolated clusters of G. p. gambiensis habitat based on a species distribution model and ranked them according to their predicted genetic distance to the main tsetse population. The methodology presented here will inform the choice on the most appropriate intervention strategies to be implemented against tsetse flies in different parts of Africa. It can also be used to control other pests and to support conservation of endangered species.

Using species distribution models to optimize vector control in the framework of the tsetse eradication campaign in Senegal.

Tsetse flies are vectors of human and animal trypanosomoses in sub-Saharan Africa and are the target of the Pan African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC). Glossina palpalis gambiensis (Diptera: Glossinidae) is a riverine species that is still present as an isolated metapopulation in the Niayes area of Senegal. It is targeted by a national eradication campaign combining a population reduction phase based on insecticide-treated targets (ITTs) and cattle and an eradication phase based on the sterile insect technique. In this study, we used species distribution models to optimize control operations. We compared the probability of the presence of G. p. gambiensis and habitat suitability using a regularized logistic regression and Maxent, respectively. Both models performed well, with an area under the curve of 0.89 and 0.92, respectively. Only the Maxent model predicted an expert-based classification of landscapes correctly. Maxent predictions were therefore used throughout the eradication campaign in the Niayes to make control operations more efficient in terms of deployment of ITTs, release density of sterile males, and location of monitoring traps used to assess program progress. We discuss how the models' results informed about the particular ecology of tsetse in the target area. Maxent predictions allowed optimizing efficiency and cost within our project, and might be useful for other tsetse control campaigns in the framework of the PATTEC and, more generally, other vector or insect pest control programs.

Animal trypanosomosis eliminated in a major livestock production region in Senegal following the eradication of a tsetse population.

African animal trypanosomosis (AAT) was one of the main disease-related constraints to the development of intensive livestock production systems in the Niayes region of Senegal, a 30 km wide strip of land along the coast between Dakar and Saint-Louis. To overcome this constraint, the Government of Senegal initiated an area-wide integrated pest management programme combining chemical control tactics with the sterile insect technique to eradicate a population of the tsetse fly Glossina palpalis gambiensis Vanderplank, 1949 (Diptera, Glossinidae) in this area. The project was implemented following a phased conditional approach, and the target area was divided into three blocks treated sequentially. This study aims to assess the temporal dynamics of the prevalence of Trypanosoma spp. during the implementation of this programme. Between 2009 and 2022, 4,359 blood samples were collected from cattle and screened for trypanosomes using both the buffy coat and ELISA techniques, and PCR tests since 2020. The seroprevalence decreased from 18.9% (95%CI: 11.2-26.5) in 2009 to 0% in 2017-2022 in block 1, and from 92.9% (95%CI: 88.2-97) in 2010 to 0% in 2021 in block 2. The parasitological and serological data confirm the entomological monitoring results, i.e., that there is a high probability that the population of G. p. gambiensis has been eradicated from the Niayes and that the transmission of AAT has been interrupted in the treated area. These results indicate the effectiveness of the adopted approach and show that AAT can be sustainably removed through the creation of a zone free of G. p. gambiensis.

Title: Trypanosomose animale éliminée dans une importante région de production d'élevage au Sénégal suite à l'éradication d'une population de glossines. Abstract: La trypanosomose animale africaine (TAA) était l'une des principales contraintes pathologiques au développement de systèmes de production animale intensifs dans les Niayes du Sénégal, une bande de terre large de 30 km longeant la côte entre Dakar et Saint-Louis. Pour surmonter cette contrainte, le Gouvernement du Sénégal a lancé un programme de lutte intégrée à l'échelle de la zone combinant lutte chimique et technique de l'insecte stérile pour éradiquer une population de Glossina palpalis gambiensis Vanderplank, 1949 (Diptera, Glossinidae). Le projet a été mis en œuvre selon une approche conditionnelle progressive, et la zone cible a été divisée en trois blocs, traités de manière séquentielle. L'objectif de cette étude était d'évaluer la dynamique temporelle de la prévalence de Trypanosoma spp. au cours de la mise en œuvre du programme. Entre 2009 et 2022, 4 359 échantillons de sang ont été prélevés sur des bovins et ont fait l'objet d'un dépistage des trypanosomes à l'aide des techniques du buffy-coat et ELISA, ainsi que de test PCR depuis 2020. Dans le bloc 1, la séroprévalence est passée de 18,9 % (IC 95 % : 11,2­26,5) en 2009 à 0 % entre 2017­2022 et de 92,9 % (IC 95 % : 88,2-97) en 2010 à 0 % en 2021 pour le block 2. Les données parasitologiques et sérologiques confirment les résultats du suivi entomologique selon lesquels il est très probable que la population de Glossina palpalis gambiensis soit éradiquée des Niayes, et que la transmission de la TAA a été interrompue dans la zone traitée. Elles indiquent l'efficacité de l'approche adoptée, et montrent que la TAA peut être durablement éliminée grâce à la création d'une zone exempte de G. p. gambiensis.

RNA interference against animal viruses: how morbilliviruses generate extended diversity to escape small interfering RNA control.

Viruses are serious threats to human and animal health. Vaccines can prevent viral diseases, but few antiviral treatments are available to control evolving infections. Among new antiviral therapies, RNA interference (RNAi) has been the focus of intensive research. However, along with the development of efficient RNAi-based therapeutics comes the risk of emergence of resistant viruses. In this study, we challenged the in vitro propensity of a morbillivirus (peste des petits ruminants virus), a stable RNA virus, to escape the inhibition conferred by single or multiple small interfering RNAs (siRNAs) against conserved regions of the N gene. Except with the combination of three different siRNAs, the virus systematically escaped RNAi after 3 to 20 consecutive passages. The genetic modifications involved consisted of single or multiple point nucleotide mutations and a deletion of a stretch of six nucleotides, illustrating that this virus has an unusual genomic malleability.

Identifying landscape features associated with Rift Valley fever virus transmission, Ferlo region, Senegal, using very high spatial resolution satellite imagery.

INTRODUCTION: Dynamics of most of vector-borne diseases are strongly linked to global and local environmental changes. Landscape changes are indicators of human activities or natural processes that are likely to modify the ecology of the diseases. Here, a landscape approach developed at a local scale is proposed for extracting mosquito favourable biotopes, and for testing ecological parameters when identifying risk areas of Rift Valley fever (RVF) transmission. The study was carried out around Barkedji village, Ferlo region, Senegal. METHODS: In order to test whether pond characteristics may influence the density and the dispersal behaviour of RVF vectors, and thus the spatial variation in RVFV transmission, we used a very high spatial resolution remote sensing image (2.4 m resolution) provided by the Quickbird sensor to produce a detailed land-cover map of the study area. Based on knowledge of vector and disease ecology, seven landscape attributes were defined at the pond level and computed from the land-cover map. Then, the relationships between landscape attributes and RVF serologic incidence rates in small ruminants were analyzed through a beta-binomial regression. Finally, the best statistical model according to the Akaike Information Criterion corrected for small samples (AICC), was used to map areas at risk for RVF. RESULTS: Among the derived landscape variables, the vegetation density index (VDI) computed within a 500 m buffer around ponds was positively correlated with serologic incidence (p<0.001), suggesting that the risk of RVF transmission was higher in the vicinity of ponds surrounded by a dense vegetation cover. The final risk map of RVF transmission displays a heterogeneous spatial distribution, corroborating previous findings from the same area. CONCLUSIONS: Our results highlight the potential of very high spatial resolution remote sensing data for identifying environmental risk factors and mapping RVF risk areas at a local scale.

Animal disease surveillance: How to represent textual data for classifying epidemiological information.

The value of informal sources in increasing the timeliness of disease outbreak detection and providing detailed epidemiological information in the early warning and preparedness context is recognized. This study evaluates machine learning methods for classifying information from animal disease-related news at a fine-grained level (i.e., epidemiological topic). We compare two textual representations, the bag-of-words method and a distributional approach, i.e., word embeddings. Both representations performed well for binary relevance classification (F-measure of 0.839 and 0.871, respectively). Bag-of-words representation was outperformed by word embedding representation for classifying sentences into fine-grained epidemiological topics (F-measure of 0.745). Our results suggest that the word embedding approach is of interest in the context of low-frequency classes in a specialized domain. However, this representation did not bring significant performance improvements for binary relevance classification, indicating that the textual representation should be adapted to each classification task.

Dissemination of information in event-based surveillance, a case study of Avian Influenza.

Event-Based Surveillance (EBS) tools, such as HealthMap and PADI-web, monitor online news reports and other unofficial sources, with the primary aim to provide timely information to users from health agencies on disease outbreaks occurring worldwide. In this work, we describe how outbreak-related information disseminates from a primary source, via a secondary source, to a definitive aggregator, an EBS tool, during the 2018/19 avian influenza season. We analysed 337 news items from the PADI-web and 115 news articles from HealthMap EBS tools reporting avian influenza outbreaks in birds worldwide between July 2018 and June 2019. We used the sources cited in the news to trace the path of each outbreak. We built a directed network with nodes representing the sources (characterised by type, specialisation, and geographical focus) and edges representing the flow of information. We calculated the degree as a centrality measure to determine the importance of the nodes in information dissemination. We analysed the role of the sources in early detection (detection of an event before its official notification) to the World Organisation for Animal Health (WOAH) and late detection. A total of 23% and 43% of the avian influenza outbreaks detected by the PADI-web and HealthMap, respectively, were shared on time before their notification. For both tools, national and local veterinary authorities were the primary sources of early detection. The early detection component mainly relied on the dissemination of nationally acknowledged events by online news and press agencies, bypassing international reporting to the WAOH. WOAH was the major secondary source for late detection, occupying a central position between national authorities and disseminator sources, such as online news. PADI-web and HealthMap were highly complementary in terms of detected sources, explaining why 90% of the events were detected by only one of the tools. We show that current EBS tools can provide timely outbreak-related information and priority news sources to improve digital disease surveillance.

Labeled entities from social media data related to avian influenza disease.

This dataset is composed by spatial (e.g. location) and thematic (e.g. diseases, symptoms, virus) entities concerning avian influenza in social media (textual) data in English. It was created from three corpora: the first one includes 10 transcriptions of YouTube videos and 70 tweets manually annotated. The second corpus is composed by the same textual data but automatically annotated with Named Entity Recognition (NER) tools. These two corpora have been built to evaluate NER tools and apply them to a bigger corpus. The third corpus is composed of 100 YouTube transcriptions automatically annotated with NER tools. The aim of the annotation task is to recognize spatial information such as the names of the cities and epidemiological information such as the names of the diseases. An annotation guideline is provided in order to ensure a unified annotation and to help the annotators. This dataset can be used to train or evaluate Natural Language Processing (NLP) approaches such as specialized entity recognition.

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.

Optimization of adult mosquito trap settings to monitor populations of Aedes and Culex mosquitoes, vectors of arboviruses in La Reunion.

Competent arbovirus vectors are found in the culicid mosquito fauna of south-west Indian Ocean (SWIO) islands. In La Reunion, Aedes albopictus and Aedes aegypti mosquitoes are known vectors of dengue and chikungunya viruses. Culex quinquefasciatus is a potential vector of Rift Valley fever and West Nile viruses. To prepare a vector-control field trial against Ae. aegypti, this study aimed at identifying the best trapping strategy to catch adult Ae. aegypti, using BG-Sentinel traps (Biogents, Germany). It was implemented in two sites in southern La Reunion. Catches of Ae. albopictus and Cx. quinquefasciatus mosquitoes were also recorded. A Latin square design was used to estimate the detection probability and the apparent daily density-according to the BG-Sentinel trapping strategy: none, carbon dioxide (CO2), a commercial attractant-BG-Lure (Biogents, Germany), or both. The use of CO2 alone was associated with a higher detection probability for Ae. aegypti and Cx. quinquefasciatus mosquitoes, as well as a large increase in their apparent density. Traps with BG-Lure-alone or in combination with CO2, did not improve the detection probability of Ae. aegypti and Cx. quinquefasciatus mosquitoes. The same result was found for male Ae. albopictus. For females, baiting BG-Sentinel traps with CO2 or BG-Lure had no significant effect. The same apparent densities were found for Ae. aegypti and Ae. albopictus mosquitoes in both study sites-where Ae. aegypti mosquitoes were found at very low densities during previous surveys.

Optimization of oviposition trap settings to monitor populations of Aedes mosquitoes, vectors of arboviruses in La Reunion.

Several dengue epidemics recently occurred in La Reunion, an island harboring two dengue viruses (DVs) vectors: Aedes albopictus, and Ae. aegypti, the former being the main local DV vector. Aedes aegypti shows a peculiar ecology, compared to other tropical populations of the same species. This study aimed to provide researchers and public-health users with locally validated oviposition traps (ovitraps) to monitor Aedes populations. A field experiment was performed in Saint-Joseph to assess the effect of different settings on the detection probability and apparent density of Aedes mosquitoes. Black plastic ovitraps were identified as the best choice. Vacoa trees (Pandanus utilis) were the only observed breeding sites for Ae. aegypti, shared with Ae. albopictus. They were the experimental units in a Latin square design with three factors: trap position in the trees (ground vs canopy), oviposition surface in the trap (blotting paper vs. vacoa leaf), and addition of organic matter to the trap water. The latter factor was found unimportant. On the ground, Ae. aegypti eggs were only found with vacoa leaves as the oviposition surface. Their detection and apparent density increased when ovitraps were located in the tree canopy. The main factor for Ae. albopictus was the oviposition surface, with a preference for blotting paper. In all trap settings, their detection was close to 100%. Larval survival was lower for a high egg density, combined with blotting paper as the oviposition surface. When monitoring mixed Aedes populations in La Reunion, we recommend using black plastic ovitraps, placed at 1.50-to-2.00-m high in vacoa trees, with vacoa leaves as the oviposition surface.

The Crimean-Congo haemorrhagic fever tick vector Hyalomma marginatum in the south of France: Modelling its distribution and determination of factors influencing its establishment in a newly invaded area.

We developed a correlative model at high resolution for predicting the distribution of one of the main vectors of Crimean-Congo haemorrhagic fever virus (CCHFV), Hyalomma marginatum, in a recently colonised area, namely southern France. About 931 H. marginatum adult ticks were sampled on horses from 2016 to 2019 and 2021 in 14 southern French departments, which resulted in the first H. marginatum detection map on a large portion of the national territory. Such updated presence/absence data, as well as the mean number of H. marginatum per examined animal (mean parasitic load) as a proxy of tick abundance, were correlated to multiple parameters describing the climate and habitats characterising each collection site, as well as movements of horses as possible factors influencing tick exposure. In southern France, H. marginatum was likely detected in areas characterised by year-long warm temperatures and low precipitation, especially in summer and mostly concentrated in autumn, as well as moderate annual humidity, compared to other sampled areas. It confirms that even in newly invaded areas this tick remains exclusively Mediterranean and cannot expand outside this climatic range. Regarding the environment, a predominance of open natural habitats, such as sclerophyllous vegetated and sparsely vegetated areas, were also identified as a favourable factor, in opposition to urban or peri-urban and humid habitats, such as continuous urban areas and inland marshes, respectively, which were revealed to be unsuitable. Based on this model, we predicted the areas currently suitable for the establishment of the tick H. marginatum in the South of France, with relatively good accuracy using internal (AUC = 0.66) and external validation methods (AUC = 0.76 and 0.83). Concerning tick abundance, some correlative relationships were similar to the occurrence model, as well as the type of horse movements being highlighted as an important factor explaining mean parasitic load. However, the limitations of estimating and modelling H. marginatum abundance in a correlative model are discussed.

Identification of drivers of Rift Valley fever after the 2013-14 outbreak in Senegal using serological data in small ruminants.

Rift Valley fever (RVF) is a mosquito-borne disease mostly affecting wild and domestic ruminants. It is widespread in Africa, with spillovers in the Arab Peninsula and the southwestern Indian Ocean. Although RVF has been circulating in West Africa for more than 30 years, its epidemiology is still not clearly understood. In 2013, an RVF outbreak hit Senegal in new areas that weren't ever affected before. To assess the extent of the spread of RVF virus, a national serological survey was implemented in young small ruminants (6-18 months old), between November 2014 and January 2015 (after the rainy season) in 139 villages. Additionally, the drivers of this spread were identified. For this purpose, we used a beta-binomial ([Formula: see text]) logistic regression model. An Integrated Nested Laplace Approximation (INLA) approach was used to fit the spatial model. Lower cumulative rainfall, and higher accessibility were both associated with a higher RVFV seroprevalence. The spatial patterns of fitted RVFV seroprevalence pointed densely populated areas of western Senegal as being at higher risk of RVFV infection in small ruminants than rural or southeastern areas. Thus, because slaughtering infected animals and processing their fresh meat is an important RVFV transmission route for humans, more human populations might have been exposed to RVFV during the 2013-2014 outbreak than in previous outbreaks in Senegal.

Asian lineage of peste des petits ruminants virus, Africa.

Interest in peste des petits ruminants virus (PPRV) has been stimulated by recent changes in its host and geographic distribution. For this study, biological specimens were collected from camels, sheep, and goats clinically suspected of having PPRV infection in Sudan during 2000-2009 and from sheep soon after the first reported outbreaks in Morocco in 2008. Reverse transcription PCR analysis confirmed the wide distribution of PPRV throughout Sudan and spread of the virus in Morocco. Molecular typing of 32 samples positive for PPRV provided strong evidence of the introduction and broad spread of Asian lineage IV. This lineage was defined further by 2 subclusters; one consisted of camel and goat isolates and some of the sheep isolates, while the other contained only sheep isolates, a finding with suggests a genetic bias according to the host. This study provides evidence of the recent spread of PPRV lineage IV in Africa.

Monitoring online media reports for early detection of unknown diseases: Insight from a retrospective study of COVID-19 emergence.

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.