Using topic modelling for unsupervised annotation of electronic health records to identify an outbreak of disease in UK dogs

A key goal of disease surveillance is to identify outbreaks of known or novel diseases in a timely manner. Such an outbreak occurred in the UK associated with acute vomiting in dogs between December 2019 and March 2020. We tracked this outbreak using the clinical free text component of anonymised electronic health records (EHRs) collected from a sentinel network of participating veterinary practices. We sourced the free text (narrative) component of each EHR supplemented with one of 10 practitioner-derived main presenting complaints (MPCs), with the ‘gastroenteric’ MPC identifying cases involved in the disease outbreak. Such clinician-derived annotation systems can suffer from poor compliance requiring retrospective, often manual, coding, thereby limiting real-time usability, especially where an outbreak of a novel disease might not present clinically as a currently recognised syndrome or MPC. Here, we investigate the use of an unsupervised method of EHR annotation using latent Dirichlet allocation topic-modelling to identify topics inherent within the clinical narrative component of EHRs. The model comprised 30 topics which were used to annotate EHRs spanning the natural disease outbreak and investigate whether any given topic might mirror the outbreak time-course. Narratives were annotated using the Gensim Library LdaModel module for the topic best representing the text within them. Counts for narratives labelled with one of the topics significantly matched the disease outbreak based on the practitioner-derived ‘gastroenteric’ MPC (Spearman correlation 0.978); no other topics showed a similar time course. Using artificially injected outbreaks, it was possible to see other topics that would match other MPCs including respiratory disease. The underlying topics were readily evaluated using simple word-cloud representations and using a freely available package (LDAVis) providing rapid insight into the clinical basis of each topic. This work clearly shows that unsupervised record annotation using topic modelling linked to simple text visualisations can provide an easily interrogable method to identify and characterise outbreaks and other anomalies of known and previously un-characterised diseases based on changes in clinical narratives.

Epidemiological Characteristics and Associated Factors of Imported Respiratory Infectious Diseases in China, 2014 - 2018

Background With the progress of globalization, the international mobility of population is increasing, which facilitates the cross-border transmission of respiratory infectious diseases (RIDs). The aim of this study is to analyze the epidemiological characteristics and relative factors of imported RIDs for using high-tech and wisdom methods to early find and stop the important RIDs spread to China. Methods The imported RIDs cases from 2014 to 2018 enrolled in this study were screened by the inbound sentinel network of customs and national notifiable disease reporting system in China. The spatial, temporal and population distribution of imported respiratory infectious diseases were analyzed. Seasonal index was calculated to describe the seasonality, and Pearson correlation coefficients were assessed to examine associations between independent variables and imported cases. Data analysis and visualization were carried out with R (version 4.0.5). Results Among 1,409,265,253 inbound travelers, 31,302 (2.22/100,000) imported RIDs cases from 143 countries within 5 continents were reported. The incidence of imported RIDs in 2018 (2.77/100,000) was nearly 5 times that of 2014 (0.56/100,000). Among foreigners, the incidences were higher in male (5.11/100,000), 0–14 year old group (14.06/100,000), and Oceania (10.98/100,000). Influenza accounted for the majority of imported RIDs(90.64%), with obvious seasonality. The spatial distribution of imported RIDs was different between Chinese citizens and foreigners. With the increase of inbound travel volume and the number of influenza cases in source countries, the number of imported RIDs cases increased. Conclusions Our study showed RIDs imported into China from 143 countries around the world. Therefore, it has great potential risks of transmitting important RIDs to China. So, it is urgent to strengthen the surveillance at customs for inbound population, and establish the wisdom surveillance and warning systems for preventing and stop imported RIDs spreading to China.

Online Sex-Seeking Among Chinese Heterosexual Men Who Seek Care in Stis Clinics: A Cross-Sectional Study

Background: The Internet has become an important virtual venue for men who have sex with men to seek sexual partners, with a high potential threat to spread sexually transmitted infections (STIs). However,the onlinesex-seeking use and its risk causing STIs spread remain unclear among heterosexual men. We conducted a cross-sectional study to investigate the use of online sex-seeking venues and the related risky sex activities (e.g. condomless sex, quick sex) in STIs clinics in Guangdong, China. Methods: These STIs clinics were involved in the Guangdong governmental sentinel network and we recruited heterosexual men (age >= 18) between March and August 2018. Multivariable logistic regression models were used to identify the factors associated with online sex-seeking use and risky sex activities with online sex partners. Results: 191 of 2,154 participants (8.9%) ever sought sex online. Among users,16.8% met their partners in-person within 24 hours, 31.4% engaged in condomless sex with their last online partner. Online sex-seeking was positively associated with a) previous STIs diagnosis (aOR=3.0, 95%CI:2.0-4.6), and b)having casual partners in the last three months (aOR=3.3, 95%CI 2.4-4.6). Condomless sex with the last online partner was negatively associated with the correct answer of “having only one partner can reduce the risk to infect HIV” (aOR=0.3, 95%CI:0.1-0.8). Conclusion:In China, online sex-seeking and its related risky sexual activities are not rare among heterosexual men. Future prevention strategies to reduce STIs incidence should especially target heterosexual men engaging in online sex-seeking.

Coverage of the national surveillance system for human Salmonella infections, Belgium, 2016-2020

Introduction The surveillance of human salmonellosis in Belgium is dependent on the referral of human Salmonella isolates to the National Reference Center (NRC). Knowledge of current diagnostic practices and the coverage of the national Salmonella surveillance system are important to correctly interpret surveillance data and trends over time, to estimate the true burden of salmonellosis in Belgium, and to evaluate the appropriateness of implementing whole-genome sequencing (WGS) at this central level. Methods The coverage of the NRC was defined as the proportion of all diagnosed human Salmonella cases in Belgium reported to the NRC and was assessed for 2019 via a survey among all licensed Belgian medical laboratories in 2019, and for 2016–2020 via a capture-recapture study using the Sentinel Network of Laboratories (SNL) as the external source. In addition, the survey was used to assess the impact of the implementation of culture-independent diagnostic tests (CIDTs) at the level of peripheral laboratory sites, as a potential threat to national public health surveillance programs. Results The coverage of the NRC surveillance system was estimated to be 83% and 85%, based on the results of the survey and on the two-source capture-recapture study, respectively. Further, the results of the survey indicated a limited use of CIDTs by peripheral laboratories in 2019. Conclusion Given the high coverage and the limited impact of CIDTs on the referral of isolates, we may conclude that the NRC can confidently monitor the epidemiological situation and identify outbreaks throughout the country. These findings may guide the decision to implement WGS at the level of the NRC and may improve estimates of the true burden of salmonellosis in Belgium.

PRINCIPLE trial demonstrates scope for in-pandemic improvement in primary care antibiotic stewardship: a retrospective sentinel network cohort study

BackgroundThe Platform Randomised trial of INterventions against COVID-19 In older peoPLE (PRINCIPLE) has provided in-pandemic evidence that azithromycin and doxycycline were not beneficial in the early primary care management of COVID-19.AimTo explore the extent of azithromycin and doxycycline in-pandemic use, and the scope for trial findings impacting on practice.Design & settingCrude rates of prescribing and respiratory tract infections (RTI) in 2020 were compared with 2019, using the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC).MethodA negative binomial model was used to compare azithromycin and doxycycline lower respiratory tract infections (LRTI), upper respiratory tract infections (URTI), and influenza-like-illness (ILI) in 2020 with 2019; reporting incident rate ratios (IRR) between years, and 95% confidence intervals (95% CI).ResultsAzithromycin prescriptions increased 7% in 2020 compared with 2019, whereas doxycycline decreased by 7%. Concurrently, LRTI and URTI incidence fell by over half (58.3% and 54.4%, respectively) while ILI rose slightly (6.4%). The overall percentage of RTI prescribed azithromycin rose from 0.51% in 2019 to 0.72% in 2020 (risk difference of 0.214% [95% CI = 0.211 to 0.217]); doxycycline rose from 11.86% in 2019 to 15.79% in 2020 (risk difference: 3.93% [95% CI = 3.73 to 4.14]). The adjusted IRR showed azithromycin prescribing was 22% higher in 2020 (IRR = 1.22, 95% CI = 1.19 to 1.26, P<0.0001), for every unit rise in confirmed COVID-19 there was an associated 3% rise in prescription (IRR = 1.03, 95% CI = 1.02 to 1.03, P<0.0001); whereas these measures were static for doxycycline.ConclusionPRINCIPLE demonstrates scope for improved antimicrobial stewardship during a pandemic.

Association between Influenza Vaccine Administration and Primary Care Consultations for Respiratory Infections: Sentinel Network Study of Five Seasons (2014/2015–2018/2019) in the UK

Influenza, a vaccine preventable disease, is a serious global public health concern which results in a considerable burden on the healthcare system. However, vaccine hesitancy is increasingly becoming a global problem. One prevalent misconception is that influenza vaccinations can cause the flu. We carried out this study to determine whether people undertaking influenza vaccination presented less with acute respiratory tract infection (ARTI) and influenza-like-illness (ILI) following vaccination. We utilised the Oxford Royal College of General Practitioners Research and Surveillance Centre sentinel database to examine English patients who received vaccination between 2014/2015 and 2018/2019. Of the 3,841,700 influenza vaccinations identified, vaccination details and primary care respiratory consultation counts were extracted to calculate the relative incidence (RI) per exposure risk period using the self-controlled case series methodology. Results showed a significant increase in the RI of respiratory consultation rates within fourteen days of vaccination across all five years. Less than 6.2% of vaccinations led to consultations for ARTI or ILI in primary care (crude consultation rate 6196 per 100,000). These findings, particularly if confirmed in further research, may reduce the risk of cross-infection between waiting patients and increase uptake of influenza vaccine.