Elena Arsevska

Identification of terms for detecting early signals of emerging infectious disease outbreaks on the web

Integrated approach to identify terms for monitoring disease emergence on the web.Terms are extracted automatically from disease outbreak web pages.Domain experts identify the terms relevant to characterise a disease emergence.Relevant terms are used as queries to mine the web. Timeliness and precision for detection of infectious animal disease outbreaks from the information published on the web is crucial for prevention against their spread. The work in this paper is part of the methodology for monitoring the web that we currently develop for the French epidemic intelligence team in animal health. We focus on the new and exotic infectious animal diseases that occur worldwide and that are of potential threat to the animal health in France.In order to detect relevant information on the web, we present an innovative approach that retrieves documents using queries based on terms automatically extracted from a corpus of relevant documents and validated with a consensus of domain experts (Delphi method). As a decision support tool to domain experts we introduce a new measure for ranking of extracted terms in order to highlight the more relevant terms. To categorise documents retrieved from the web we use Naive Bayes (NB) and Support Vector Machine (SVM) classifiers.We evaluated our approach on documents on African swine fever (ASF) outbreaks for the period from 2011 to 2014, retrieved from the Google search engine and the PubMed database. From 2400 terms extracted from two corpora of relevant ASF documents, 135 terms were relevant to characterise ASF emergence. The domain experts identified as highly specific to characterise ASF emergence the terms which describe mortality, fever and haemorrhagic clinical signs in Suidae.The new ranking measure correctly ranked the ASF relevant terms until position 161 and fairly until position 227, with areas under ROC curves (AUCs) of 0.802 and 0.709 respectively.Both classifiers were accurate to classify a set of 545 ASF documents (NB of 0.747 and SVM of 0.725) into appropriate categories of relevant (disease outbreak) and irrelevant (economic and general) documents.Our results show that relevant documents can serve as a source of terms to detect infectious animal disease emergence on the web.Our method is generic and can be used both in animal and public health domain.

Identifying Areas Suitable for the Occurrence of Rift Valley Fever in North Africa: Implications for Surveillance.

Rift Valley fever (RVF) is a vector-borne zoonotic disease that has caused widespread outbreaks throughout Africa and the Arabian Peninsula, with serious consequences for livestock-based economies and public health. Although there have never been any reports of RVF in Morocco, Algeria, Tunisia and Libya, it is a priority disease in the Maghreb, due to the threat of introduction of the virus through transboundary livestock movements or infected mosquito vectors. However, the implementation of surveillance activities and early warning contingency plans requires better knowledge of the epidemiological situation. We conducted a multicriteria decision analysis, integrating host distribution with a combination of important ecological factors that drive mosquito abundance, to identify hotspots and suitable time periods for RVF enzootic circulation (i.e. stable transmission at a low to moderate level for an extended period of time) and an RVF epizootic event (i.e. a sudden occurrence of a large number of infected animals over a large geographic area) in the Maghreb. We also modelled vector species distribution using available information on vector presence and habitat preference. We found that the northern regions of the Maghreb were moderately suitable for RVF enzootics, but highly suitable for RVF epizootics. The vector species distribution model identified these regions as the most favourable mosquito habitats. Due to the low density of animal hosts and arid conditions, the desert region showed low RVF suitability, except in oases. However, the presence of competent vectors in putative unsuitable areas underlines the need for further assessments of mosquito habitat preference. This study produced monthly RVF suitability maps useful for animal health managers and veterinary services involved in designing risk-based surveillance programmes. The suitability maps can be further enhanced using existing country-specific sources of information and by incorporating knowledge - as it becomes available - on the epidemiology of the disease and distribution of vectors in the Maghreb.

Small animal disease surveillance: GI disease and salmonellosis

Presentation for gastrointestinal (GI) disease comprised 2.2 per cent of cat, 3.2 per cent of dog and 2.2 per cent of rabbit consultations between April 1, 2016 and March 31, 2017 Diarrhoea and vomiting without blood were the most frequently reported GI disease clinical signs (34.4 and 38.9 per cent in cats and 42.8 and 37.3 per cent in dogs, respectively) The mean percentage of samples testing positive for Salmonella in dogs was double that in cats (0.82 per cent and 0.41 per cent, respectively) from January 1, 2011 to December 31, 2016 In dogs, autumn was associated with a greater proportion of Salmonella-positive sample submissions; no clear suggestion of seasonal variation in cats was observed In both cats and dogs, isolates belonging to Salmonella enterica group B serotypes were the most common (68.9 per cent in cats and 55.0 per cent in dogs)

Identification of Associations between Clinical Signs and Hosts to Monitor the Web for Detection of Animal Disease Outbreaks

In a context of intensification of international trade and travels, the transboundary spread of emerging human or animal pathogens represents a growing concern. One of the missions of the national veterinary services is to implement international epidemiological intelligence for a timely and accurate detection of emerging animal infectious diseases (EAID) worldwide, and take early actions to prevent their introduction on the national territory. For this purpose, an efficient use of the information published on the web is essential. The authors present a comprehensive method for identification of relevant associations between terms describing clinical signs and hosts to build queries to monitor the web for early detection of EAID. Using text and web mining approaches, they present statistical measures for automatic selection of relevant associations between terms. In addition, expert elicitation is used to highlight the most relevant terms and associations among those automatically selected. The authors assessed the performance of the combination of the automatic approach and expert elicitation to monitor the web for a list of selected animal pathogens.

[Demo] Integration of Text- and Web-Mining Results in EpidVis.

The new and emerging infectious diseases are an incising threat to countries due to globalisation, movement of passengers and international trade. In order to discover articles of potential importance to infectious disease emergence it is important to mine the Web with an accurate vocabulary. In this paper, we present a new methodology that combines text-mining results and visualisation approach in order to discover associations between hosts and symptoms related to emerging infectious disease outbreaks.

Small animal disease surveillance: pruritus and Pseudomonas skin infections

Report Summary: • Presentation for investigation and/or treatment of gastrointestinal (GI) disease comprised 3.0 per cent, 2.0 per cent and 1.9 per cent of total dog, cat and rabbit consultations respectively between 1 April 2017 and 31 October 2018 • Diarrhoea and vomiting without blood were the most frequently reported GI disease clinical signs (43.0 and 36.6 per cent in dogs, and 35.9 and 37.7 per cent in cats respectively) • The proportion of GI disease consultations which prescribed antibiotics authorised for systemic administration (including oral and injectable formulations) decreased between April 2014 and October 2018 • The proportion of GI disease consultations which dispensed nutraceutical products advertised as being effective at managing primary GI disease (including prebiotics, probiotics etc.) increased between April 2014 and October 2018 • Between January 2011 and August 2018, 13.5 per cent of 20,194 feline faecal samples submitted to UK-based diagnostic laboratories tested positive for presence of Tritrichomonas foetus • The proportion of feline sample submissions testing positive for T.foetus decreased between 2011 and 2018

New approaches to pharmacosurveillance for monitoring prescription frequency, diversity, and co-prescription in a large sentinel network of companion animal veterinary practices in the United Kingdom, 2014–2016

Pharmaceutical agents (PAs) are commonly prescribed in companion animal practice in the United Kingdom. However, little is known about PA prescription on a population-level, particularly with respect to PAs authorised for human use alone prescribed via the veterinary cascade; this raises important questions regarding the efficacy and safety of PAs prescribed to companion animals. This study explored new approaches for describing PA prescription, diversity and co-prescription in dogs, cats and rabbits utilising electronic health records (EHRs) from a sentinel network of 457 companion animal-treating veterinary sites throughout the UK over a 2-year period (2014–2016). A novel text mining-based identification and classification methodology was utilised to semi-automatically map practitioner-defined product descriptions recorded in 918,333 EHRs from 413,870 dogs encompassing 1,242,270 prescriptions; 352,730 EHRs from 200,541 cats encompassing 491,554 prescriptions, and 22,526 EHRS from 13,398 rabbits encompassing 18,490 prescriptions respectively. PA prescription as a percentage of booked consultations was 65.4% (95% confidence interval, CI, 64.6–66.3) in dogs; in cats it was 69.1% (95% CI, 67.9–70.2) and in rabbits, 56.3% (95% CI, 54.7–57.8). Vaccines were the most commonly prescribed PAs in all three species, with antibiotics, antimycotics, and parasiticides also commonly prescribed. PA prescription utilising products authorised for human use only (hence, ‘human-authorised’) comprised 5.1% (95% CI, 4.7–5.5) of total canine prescription events; in cats it was 2.8% (95% CI, 2.6–3.0), and in rabbits, 7.8% (95% CI, 6.5–9.0). The most commonly prescribed human-authorised PA in dogs was metronidazole (antibiotic); in cats and rabbits it was ranitidine (H2 histamine receptor antagonist). Using a new approach utilising the Simpson’s Diversity Index (an ecological measure of relative animal, plant etc. species abundance), we identified differences in prescription based on presenting complaint and species, with rabbits generally exposed to a less diverse range of PAs than dogs or cats, potentially reflecting the paucity of authorised PAs for use in rabbits. Finally, through a novel application of network analysis, we demonstrated the existence of three major co-prescription groups (preventive health; treatment of disease, and euthanasia); a trend commonly observed in practice. This study represents the first time PA prescription has been described across all pharmaceutical families in a large population of companion animals, encompassing PAs authorised for both veterinary and human-only use. These data form a baseline against which future studies could be compared, and provides some useful tools for understanding PA comparative efficacy and risks when prescribed in the varied setting of clinical practice.

Risk factors for cutaneous myiasis (blowfly strike) in pet rabbits in Great Britain based on text-mining veterinary electronic health records

Highlights • Flystrike was recorded in 0.6% of rabbit consultations collected over three years from 389 sentinel practices across the UK.• Fortyfive percent of consultations resulted in the euthanasia or death of the animal.• Rabbits five years of age and over were more than 3.8 times likely to present for blowfly strike.• Female entire rabbits were at greatest risk, being 3.3 times more likely to be affected than neutered females.• For every 1 °C rise in predicted environmental temperature, there was a 33% increase in risk of flystrike.

Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System

Since 2013, the French Animal Health Epidemic Intelligence System (in French: Veille Sanitaire Internationale, VSI) has been monitoring signals of the emergence of new and exotic animal infectious diseases worldwide. Once detected, the VSI team verifies the signals and issues early warning reports to French animal health authorities when potential threats to France are detected. To improve detection of signals from online news sources, we designed the Platform for Automated extraction of Disease Information from the web (PADI-web). PADI-web automatically collects, processes and extracts English-language epidemiological information from Google News. The core component of PADI-web is a combined information extraction (IE) method founded on rule-based systems and data mining techniques. The IE approach allows extraction of key information on diseases, locations, dates, hosts and the number of cases mentioned in the news. We evaluated the combined method for IE on a dataset of 352 disease-related news reports mentioning the diseases involved, locations, dates, hosts and the number of cases. The combined method for IE accurately identified (F-score) 95% of the diseases and hosts, respectively, 85% of the number of cases, 83% of dates and 80% of locations from the disease-related news. We assessed the sensitivity of PADI-web to detect primary outbreaks of four emerging animal infectious diseases notifiable to the World Organisation for Animal Health (OIE). From January to June 2016, PADI-web detected signals for 64% of all primary outbreaks of African swine fever, 53% of avian influenza, 25% of bluetongue and 19% of foot-and-mouth disease. PADI-web timely detected primary outbreaks of avian influenza and foot-and-mouth disease in Asia, i.e. they were detected 8 and 3 days before immediate notification to OIE, respectively.