Machine learning to refine decision making within a syndromic surveillance service

Background: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical alarms highlighting potential activity of public health importance. All alarms must be assessed to confirm whether they are of public health importance. In England, approximately 100 alarms are generated daily and, although their analysis is formalised through a risk assessment process, the process requires notable time, training, and maintenance of an expertise base to determine which alarms are of public health importance. The process is made more complicated by the observation that only 0.1% of statistical alarms are deemed to be of public health importance. Therefore, the aims of this study were to evaluate machine learning as a tool for computer-assisted human decision-making when assessing statistical alarms. Methods: A record of the risk assessment process was obtained from Public Health England for all 67505 statistical alarms between August 2013 and October 2015. This record contained information on the characteristics of the alarm (e.g. size, location). We used three Bayesian classifiers- naïve Bayes, tree-augmented naïve Bayes and Multinets - to examine the risk assessment record in England with respect to the final ‘Decision’ outcome made by an epidemiologist of ‘Alert’, ‘Monitor’ or ‘No-action’. Two further classifications based upon tree-augmented naïve Bayes and Multinets were implemented to account for the predominance of ‘No-action’ outcomes. Results: The attributes of each individual risk assessment were linked to the final decision made by an epidemiologist, providing confidence in the current process. The naïve Bayesian classifier performed best, correctly classifying 51.5% of ‘Alert’ outcomes. If the ‘Alert’ and ‘Monitor’ actions are combined then performance increases to 82.6% correctly classified. We demonstrate how a decision support system based upon a naïve Bayes classifier could be operationalised within an operational syndromic surveillance system. Conclusions: Within syndromic surveillance systems, machine learning techniques have the potential to make risk assessment following statistical alarms more automated, robust, and rigorous. However, our results also highlight the importance of specialist human input to the process

Exploring Campylobacter seasonality across Europe (2008-2016) using The European Surveillance System TESSy

Background: Campylobacteriosis is the most commonly reported food-borne infection in the European Union, with an annual number of cases estimated at around 9 million. In many countries, campylobacteriosis has a striking seasonal peak during early/ mid-summer. In the early 2000s, several publications reported on campylobacteriosis seasonality across Europe and associations with temperature and precipitation. Subsequently, many European countries have introduced new measures against this foodborne disease. Aim: To examine how the seasonality of campylobacteriosis varied across Europe from 2008–16, to explore associations with temperature and precipitation, and to compare these results with previous studies. We also sought to assess the utility of the European Surveillance System TESSy for cross-European seasonal analysis of campylobacteriosis. Methods: Ward’s Minimum Variance Clustering was used to group countries with similar seasonal patterns of campylobacteriosis. A two-stage multivariate meta-analysis methodology was used to explore associations with temperature and precipitation. Results: Nordic countries had a pronounced seasonal campylobacteriosis peak in mid-to late summer (weeks 29–32), while most other European countries had a less pronounced peak earlier in the year. The United Kingdom, Ireland, Hungary and Slovakia had a slightly earlier peak (week 24). Campylobacteriosis cases were positively associated with temperature and, to a lesser degree, precipitation. Conclusion: Across Europe, the strength and timing of campylobacteriosis peaks have remained similar to those observed previously. In addition, TESSy is a useful resource for cross-Euro-pean seasonal analysis of infectious diseases such as campylobacteriosis, but its utility depends upon each country’s reporting infrastructure

Environmental factors associated with general practitioner consultations for allergic rhinitis in London, England: a retrospective time series analysis

Objectives: To identify key predictors of general practitioner (GP) consultations for allergic rhinitis (AR) using meteorological and environmental data. Design: A retrospective, time series analysis of GP consultations for AR. Setting: A large GP surveillance network of GP practices in the London area. Participants: The study population was all persons who presented to general practices in London that report to the Public Health England GP in-hours syndromic surveillance system during the study period (3 April 2012 to 11 August 2014). Primary measure: Consultations for AR (numbers of consultations). Results: During the study period there were 186 401 GP consultations for AR. High grass and nettle pollen counts (combined) were associated with the highest increases in consultations (for the category 216-270 grains/m3, relative risk (RR) 3.33, 95% CI 2.69 to 4.12) followed by high tree (oak, birch and plane combined) pollen counts (for the category 260–325 grains/m3, RR 1.69, 95% CI 1.32 to 2.15) and average daily temperatures between 15°C and 20°C (RR 1.47, 95% CI 1.20 to 1.81). Higher levels of nitrogen dioxide (NO2) appeared to be associated with increased consultations (for the category 70–85 µg/m3, RR 1.33, 95% CI 1.03 to 1.71), but a significant effect was not found with ozone. Higher daily rainfall was associated with fewer consultations (15–20 mm/day; RR 0.812, 95% CI 0.674 to 0.980). Conclusions: Changes in grass, nettle or tree pollen counts, temperatures between 15°C and 20°C, and (to a lesser extent) NO2 concentrations were found to be associated with increased consultations for AR. Rainfall has a negative effect. In the context of climate change and continued exposures to environmental air pollution, intelligent use of these data will aid targeting public health messages and plan healthcare demand

Timing of nasogastric tube insertion and the risk of postoperative pneumonia: an international, prospective cohort study

Aim: Aspiration is a common cause of pneumonia in patients with postoperative ileus. Insertion of a nasogastric tube (NGT) is often performed, but this can be distressing. The aim of this study was to determine whether the timing of NGT insertion after surgery (before versus after vomiting) was associated with reduced rates of pneumonia in patients undergoing elective colorectal surgery. Method: This was a preplanned secondary analysis of a multicentre, prospective cohort study. Patients undergoing elective colorectal surgery between January 2018 and April 2018 were eligible. Those receiving a NGT were divided into three groups, based on the timing of the insertion: routine NGT (inserted at the time of surgery), prophylactic NGT (inserted after surgery but before vomiting) and reactive NGT (inserted after surgery and after vomiting). The primary outcome was the development of pneumonia within 30 days of surgery, which was compared between the prophylactic and reactive NGT groups using multivariable regression analysis. Results: A total of 4715 patients were included in the analysis and 1536 (32.6%) received a NGT. These were classified as routine in 926 (60.3%), reactive in 461 (30.0%) and prophylactic in 149 (9.7%). Two hundred patients (4.2%) developed pneumonia (no NGT 2.7%; routine NGT 5.2%; reactive NGT 10.6%; prophylactic NGT 11.4%). After adjustment for confounding factors, no significant difference in pneumonia rates was detected between the prophylactic and reactive NGT groups (odds ratio 1.03, 95% CI 0.56\u20131.87, P = 0.932). Conclusion: In patients who required the insertion of a NGT after surgery, prophylactic insertion was not associated with fewer cases of pneumonia within 30 days of surgery compared with reactive insertion