PADI-web: A multilingual event-based surveillance system for monitoring animal infectious diseases

Valentin, Sarah; Arsevska, Elena; Falala, Sylvain; Goër, Jocelyn de; Lancelot, Renaud; Mercier, Alizé; Rabatel, Julien; Roche, Mathieu

doi:10.1016/j.compag.2019.105163

Cited by 22 publications

(21 citation statements)

References 18 publications

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“…syndromic surveillance). The Platform for Automated extraction of Disease Information from the web (PADI-web 5 ) is an automated surveillance system for monitoring the emergence of animal infectious diseases, including zoonoses [1,38]. PADI-web monitors Google News through specific really simple syndication (RSS) feeds, targeting diseases of interest (e.g.…”

Section: Case Study: Epidemic Intelligencementioning

confidence: 99%

ITEXT-BIO: Intelligent Term EXTraction for BIOmedical analysis

Kafando

Decoupes

Valentin

et al. 2021

Health Inf Sci Syst

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Here, we introduce ITEXT-BIO, an intelligent process for biomedical domain terminology extraction from textual documents and subsequent analysis. The proposed methodology consists of two complementary approaches, including free and driven term extraction. The first is based on term extraction with statistical measures, while the second considers morphosyntactic variation rules to extract term variants from the corpus. The combination of two term extraction and analysis strategies is the keystone of ITEXT-BIO. These include combined intra-corpus strategies that enable term extraction and analysis either from a single corpus (intra), or from corpora (inter). We assessed the two approaches, the corpus or corpora to be analysed and the type of statistical measures used. Our experimental findings revealed that the proposed methodology could be used: (1) to efficiently extract representative, discriminant and new terms from a given corpus or corpora, and (2) to provide quantitative and qualitative analyses on these terms regarding the study domain.

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Section: Case Study: Epidemic Intelligencementioning

confidence: 99%

ITEXT-BIO: Intelligent Term EXTraction for BIOmedical analysis

Kafando

Decoupes

Valentin

et al. 2021

Health Inf Sci Syst

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“…The B/S system framework does not require the installation of traditional software, and most of the work is conducted by the server [ 41 , 42 ]. The costs to users and the workloads of system maintenance and management are directly reduced, which results in improved independence, adaptability, scalability, and security [ 43 , 44 ].…”

Section: System Analysis and Designmentioning

confidence: 99%

Antimicrobial Resistance Risk Assessment Models and Database System for Animal-Derived Pathogens

Liang

et al. 2020

Antibiotics

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(1) Background: The high use of antibiotics has made the issue of antimicrobial resistance (AMR) increasingly serious, which poses a substantial threat to the health of animals and humans. However, there remains a certain gap in the AMR system and risk assessment models between China and the advanced world level. Therefore, this paper aims to provide advanced means for the monitoring of antibiotic use and AMR data, and take piglets as an example to evaluate the risk and highlight the seriousness of AMR in China. (2) Methods: Based on the principal component analysis method, a drug resistance index model of anti-E. coli drugs was established to evaluate the antibiotic risk status in China. Additionally, based on the second-order Monte Carlo methods, a disease risk assessment model for piglets was established to predict the probability of E. coli disease within 30 days of taking florfenicol. Finally, a browser/server architecture-based visualization database system for animal-derived pathogens was developed. (3) Results: The risk of E. coli in the main area was assessed and Hohhot was the highest risk area in China. Compared with the true disease risk probability of 4.1%, the result of the disease risk assessment model is 7.174%, and the absolute error was 3.074%. Conclusions: Taking E. coli as an example, this paper provides an innovative method for rapid and accurate risk assessment of drug resistance. Additionally, the established system and assessment models have potential value for the monitoring and evaluating AMR, highlight the seriousness of antimicrobial resistance, advocate the prudent use of antibiotics, and ensure the safety of animal-derived foods and human health.

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“…EBS uses unstructured data from unofficial sources such as online news to improve early detection of emerging infectious diseases (EIDs). Several free‐access EBS systems have been supporting epidemic intelligence since the late 1990s, such as the Program for Monitoring Emerging Diseases (ProMED; Woodall, 2001), HealthMap (Brownstein, Freifeld, Reis, & Mandl, 2008) and the recently developed PADI‐web (Valentin, Arsevska, et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Both HealthMap and ProMED monitor a list of human and animal diseases and syndromes thereof. The Platform for Automated extraction of animal Disease Information from the web (PADI‐web) was created in 2016 to monitor online animal health‐related news for the French Epidemic Intelligence System (FEIS) (Arsevska et al., 2018; Valentin, Arsevska, et al., 2020). Both HealthMap and PADI‐web automatically retrieve health‐related news from Google News using customized Really Simple Syndication (RSS) feeds.…”

Section: Introductionmentioning

confidence: 99%

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

Valentin

Mercier

Lancelot

et al. 2020

Transbound Emerg Dis

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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.

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PADI-web: A multilingual event-based surveillance system for monitoring animal infectious diseases

Cited by 22 publications

References 18 publications

ITEXT-BIO: Intelligent Term EXTraction for BIOmedical analysis

ITEXT-BIO: Intelligent Term EXTraction for BIOmedical analysis

Antimicrobial Resistance Risk Assessment Models and Database System for Animal-Derived Pathogens

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

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